workshop on medical device interoperability:...
TRANSCRIPT
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WORKSHOP ON MEDICAL DEVICE INTEROPERABILITY:
ACHIEVING SAFETY AND EFFECTIVENESS
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CO-SPONSORED BY FDA/CDRH, CONTINUA HEALTH ALLIANCE, AND CIMIT
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January 25, 2010
9:00 a.m.
FDA White Oak Campus 10903 New Hampshire Avenue Silver Spring, MD 20993
WORKSHOP ORGANIZING COMMITTEE: FDA: JOHN F. MURRAY, JR. FDA/CDRH Office of Compliance SANDY WEININGER, Ph.D. FDA/CDRH/OSEL/DESE CIMIT/MEDICAL DEVICE INTEROPERABILITY PROGRAM: JULIAN M. GOLDMAN, M.D. Director, Medical Device Interoperability Program, CIMIT Medical Director, Partners HealthCare Biomedical Engineering SUSAN WHITEHEAD Medical Device Interoperability Program, CIMIT CONTINUA HEALTH ALLIANCE: MICHAEL ROBKIN Anakena Solutions SCOTT THIEL, M.B.A., M.T.(ASCP), R.A.C. Roche Diagnostics Corp.
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PRESENTERS/MODERATORS: DONNA-BEA TILLMAN, Ph.D. Director, Office of Device Evaluation, FDA/CDRH CHARLES P. FRIEDMAN, Ph.D. Chief Scientific Officer, Office of the National Coordinator for Health IT JEFFREY E. SHUREN, M.D., J.D. Director, FDA/CDRH DOUG ROSENDALE, D.O., F.A.C.O.S. Veterans Health Administration, Office of Health Information, Joint Interoperability Ventures; Doctor of Osteopathic Medicine and Fellow of the American College of Osteopathic Surgeons JULIAN M. GOLDMAN, M.D. Director, MD PnP Program and CIMIT Program on Interoperability; Medical Director, Partners HealthCare Biomedical Engineering; Attending Anesthesiologist, Massachusetts General Hospital/Harvard Medical School DAVE deBRONKART "e-Patient Dave," e-patients.net; Co-Chair, Society for Participatory Medicine BRAD THOMPSON, J.D. Partner, Epstein Becker Green MAUREEN BAKER, C.B.E., D.M., FRCGP Clinical Director of Patient Safety, NHS Connecting for Health, England YI ZHANG Visiting Scientist, CDRH/OSEL/DESE MARY BRADY Associate Office Director, FDA/CDRH/OSB, Home Care Initiatives MICHAEL ROBKIN President, Anakena Solutions DOUG GREY, M.D. Chair, KP Biomedical Device Integration Council, Vice-Chair, KP National Product Council, The Permanente Medical Group
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PRESENTERS/MODERATORS (cont.): TOM JUDD National Project Director, Clinical Technology, Kaiser Foundation Hospitals TOM McGRANE Principal Solution Consultant, Kaiser Foundation Hospitals TIM GEE Principal, Medical Connectivity Consulting JULIAN M. GOLDMAN, M.D. Physician, MGH/PHS/CIMIT FRANK E. BLOCK, JR., M.D. Professor of Anesthesiology, VCU DICK MOBERG President, Moberg Research, Inc. G.M. SAMARAS, Ph.D., D.Sc., P.E., C.P.E., C.Q.E. CEO, Samaras & Associates, Inc. PRADUMAN JAIN CEO, Vignet, Inc. BRIGITTE PINIEWSKI, M.D. CMO, PeaceHealth Labs MIKE PARADIS Wireless Sales Manager, Dynastream Innovations, Inc. BRIAN FITZGERALD Deputy Director, Center for Division and Electronic Software Engineering; Office of Science and Engineering Labs; CDRH/FDA JOHN ZALESKI, Ph.D., CPHIMS Department Head, Biomedical Informatics, Philips Research North America DALE WIGGINS Vice President and CTO, Healthcare Informatics and Patient Monitoring, Philips Healthcare TRACY RAUSCH Founder and CEO, DocBox, Inc.
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PRESENTERS/MODERATORS (cont.): PETER KELLEY Director of QA/RA, Capsule Technology, Inc.
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INDEX PAGE
INTRODUCTION - John F. Murray, Jr. 8 OPENING/LOGISTICS/WELCOME - Donna-Bea Tillman, Ph.D. 9 PRESENTATIONS Device Interoperability and the National Health IT Agenda - Charles P. Friedman, Ph.D. 18 Q&A 45 Safety and Effectiveness Challenges in Interoperability - Jeffrey E. Shuren, M.D., J.D. 51 Setting the Stage: Device, Local, Regional, and National Perspectives on Medical Device Interoperability - Doug Rosendale, D.O., F.A.C.O.S. 60 Q&A 72 Clinical Perspective on Interoperable Medical Device Systems - Julian M. Goldman, M.D. 86 Q&A 114 Consumer and Patient Perspective on Innovation and Interoperability in Healthcare - Dave deBronkart 122 SESSIONS Session 1: Lessons Learned from Existing Regulatory Practices Moderator - Brad Thompson, J.D. 141 NHS - Maureen Baker, C.B.E., D.M., FRCGP 142 Diabetes and Home Management - Yi Zhang 148 FDA - Mary Brady 153
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INDEX (Cont.)
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Q&A 158 Session 2: Enterprise Issues Moderator - Michael Robkin 173 Digital Operating Room - Doug Grey, M.D. 174 Tom Judd 178 Tom McGrane 181 Converged Medical Device and Enterprise Network - Tim Gee 184 Q&A 192 Session 3: Systems-of-Systems Issues Moderator - Julian M. Goldman, M.D. 204 Systems-of-Systems Issues - Frank E. Block, Jr., M.D. 205 Using Standard Communications Protocols to Implement Medical Device Plug-and-Play - Dick Moberg 209 Wrangling the Human Element of Interoperability: Defending Against Reason's Latent Flaws and Dekker's Drift - G.M. Samaras, Ph.D., D.Sc., P.E., C.P.E., C.Q.E. 216 Q&A 226 Session 4: Mass Interoperability Moderator - Brad Thompson 239 Mobile Health - Praduman Jain 239 "Tooling" Communities to Advance Community Resilience - Brigitte Piniewski, M.D. 243
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INDEX (Cont.)
PAGE
The Do's and Don'ts of Creating a ULP Wireless Network - Mike Paradis 253 Q&A 262 Session 5: System Level Risk Analysis Moderator - Brian Fitzgerald 264 Multi-Parameter Data Integration to Support Clinical Decision Making - John Zaleski, Ph.D., CPHIMS 266 FiO2 Control in Preterm Infants - A Case for Device Interoperability - Dale Wiggins 273 The Building Blocks of Clinical Systems - Tracy Rausch 279 Managing Risk in Systems of Systems - Peter Kelley 285 Q&A 290 ADJOURNMENT 303
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M E E T I N G
(9:00 a.m.)
MR. MURRAY: Good morning, everyone. I'm
John Murray. I work in the Center for Devices, in
the Office of Compliance, and I'm in the software
compliance business. I'm a stickler for starting on
time and finishing on time, so I don't know where my
co-host is, but I'm starting without him.
I do things in software compliance like
helping decide whether your software's a device,
helping decide how your software should be
classified, helping decide how your software should
be validated, all kinds of things related to software
compliance issues.
And our first speaking today -- well, the
first thing I have to mention is that everyone in
this room has a cell phone, I'm sure of that, at
least one, or some other teleporting device.
UNIDENTIFIED SPEAKER: Teleporting device?
MR. MURRAY: Teleporting, so we can zap you
out of here. So I ask you to please either turn off
your cell phone or put it on no sound or put it on
vibrate, some form like that.
And our first speaker today is actually the
person that I hold personally responsible for
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starting this workshop. We had a meeting about six
months ago. The people from Continua came and talked
to the Director of the Office of Device Evaluation,
and she listened very patiently, and then she offered
to help them by saying why don't we have a workshop?
And I was in the same room there, and I volunteered
to help her and to help to do this workshop.
So the first speaker this morning is
Dr. Donna-Bea Tillman. She's the Director of the
Office of Device Evaluation here at CDRH, and the
Office of Device Evaluation does pre-market reviews
in the form of IDEs, 510(k)s, PMAs, and all the
things pre-market belong to Donna-Bea. And just to
give you an idea about how big ODE is compared to
CDRH, CDRH has about 1000 people, 1200 people. ODE
has 500 to 600 people. I'm not sure of the exact
number, but I'll say it's on the half. So I'd like
everybody to welcome Donna-Bea. Thank you.
(Applause.)
DR. TILLMAN: Thank you and good morning.
You guys actually had the hard task. I had the easy
task. I'm just the pretty face behind the mike to
welcome you here today and sort of lay out the
charge. But that's one of the things about when you
get into senior management, you get to bring good
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people together and you get to give them a charge,
and then you get to go off and do other things. So
this morning I'm going to give you your charge, and
I'll talk a little bit about what I hope's going to
come out of this, and then I'm going to leave the
incredibly bright people that I see in this room
alone to do the work. All right, let's see. So do I
just click the mouse? Oh no.
UNIDENTIFIED SPEAKER: Try the space bar.
DR. TILLMAN: The space bar, okay.
UNIDENTIFIED SPEAKER: Hold on. The outer
space bar.
UNIDENTIFIED SPEAKER: I don't think this
software's been validated.
DR. TILLMAN: The arrow?
UNIDENTIFIED SPEAKER: Glen is coming.
DR. TILLMAN: No. Is there a clicker?
UNIDENTIFIED SPEAKER: No.
DR. TILLMAN: Do I just say, Next slide?
(Laughter.)
UNIDENTIFIED SPEAKER: That works. Yeah,
let's do that.
DR. TILLMAN: I can do that, too.
UNIDENTIFIED SPEAKER: Yes, we can do that.
DR. TILLMAN: I'm happy to do that. Next
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slide. Oh, I love seeing myself on the video camera
while I talk. This is just really -- all right,
still waiting on the next slide.
UNIDENTIFIED SPEAKER: He's downloading
something.
DR. TILLMAN: Okay. Welcome to White Oak,
and for many of you, I suspect this is your first
visit to your lovely campus. The Center for Devices
and Radiological Health has been here since the
spring, and I hope that you all didn't have too much
trouble finding parking and finding your way around.
This is really exciting. To move to White Oak was a
really big deal for CDRH because it enabled us to be
in closer proximity to the other people in the
center. A lot of the work we're doing crosses Center
boundaries, and we hope you enjoy our lovely
facilities. Next slide.
So why are we here today? Well, we're here
today to develop a more in-depth discussion about
some of the many challenging issues around the safety
and effectiveness of interoperable medical devices.
Next slide.
So just to tell you what I think is
probably painfully obvious to many people in this
room, and that is that interoperability and the
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opportunity to interconnect medical devices clearly
can have a significant positive health -- positive
impact on the health of the American public. There
is a tremendous amount of opportunity that faces us
today with IT technology, with the advent of more
complicated and sophisticated medical devices. With
all we know, we really are standing at the cusp of an
era where we're going to be able to revolutionize how
healthcare is delivered in this country.
But the tricky thing is it has to be done
right, and I think there are a lot of challenges, as
you all know, with doing this right. I also think
that there's a lot of demand, and I think you know
that there's a lot of demand for interoperable
systems. We've got the President's healthcare
agenda. We've got the increasing complexity of
medical devices. We've got the rising cost of
healthcare. How can we continue to deliver world-
class healthcare in this country and yet be able to
afford to pay for it?
And I think all of these factors are things
that influence the need for interoperable medical
systems and for systems that talk to each other and
for ways in which we can bring all of the disparate
pieces that are out there today together. Next
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slide.
So this is a really complicated and hard
issue, and in order to make it happen, there are a
number of very disparate groups that we really need
to get together in one place to have a conversation.
And it's very exciting today because we have
representatives from the IT industry, we have
representatives from the medical device industry, we
have representatives from different alliances. We've
got CIMIT, and we've got FDA here today. We've got
my colleagues that are involved in the Office of the
National Coordinator here today. We have all of the
right people here in this room, and this really is a
unique opportunity to bring all of these people
together and have a discussion about these issues and
try to develop a path forward.
So the number one agenda for this meeting
is really simply to get everybody to get together in
a room and to have the kind of dialogue that we had
in the planning and putting this meeting together,
and that's already happened. And somebody said to
me -- Julian said to me just a few moments ago, and I
agree with him, that even if nothing else happens,
this meeting has already been a tremendous success.
So let's give ourselves a hand for the success we've
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already had so far.
(Applause.)
DR. TILLMAN: Okay. So we've already had
that first success, but I think frankly there's the
potential to have even more of a success to go
through the discussions that you all are going to
have, to break off into the small working groups, and
to address the questions that are on the next two or
three slides. Next slide.
So in the FR notice that we put out, there
are, I think, a number of questions that we said that
we need the answers to, and these really form the
framework of what we hope that you will be discussing
today, presentations and the work that you're going
to be doing in the breakout sessions. Next slide.
And the next slide. I don't need to read
these two. You already know them. But we need to do
more than that. Yeah, it would be great to bring all
you people together to have this robust discussion,
but at the end of the day, we really need to be able
to have something that identifies a framework and a
path for moving forward.
In order to be able to actually make this
vision that I talked about a few moments ago a
reality, we need a regulatory framework that provides
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regulatory consistency, predictability to the
industry so that the industry can feel that this is
healthcare and a space that they can get into. We
need something that fosters innovation because
clearly the technology that we have today is going to
be -- the technology that we have in 10 years is not
going to be the same technology we have today.
Things are growing by leaps and bounds. And we also
need an approach and a framework that fosters and
supports safety and effectiveness because obviously
at the end of the day, what this is all about is
promoting and protecting public health.
So what we're hoping is that you all are
going to have a robust scientific conversation,
you're going to have these presentations, and at the
end of the day we're going to be able to develop a
conference report and some concrete recommendations
for how we're going to move forward from some steps
that we need to take.
This isn't going to happen overnight, and I
don't suspect that you all are going to come out with
all of the answers, but at least if we can come up
with a few initial steps and maybe some ideas about
the broader framework in which we need to move
forward, I think that that would just add another
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success on top of the success we already have had.
So next slide.
So that being said, I want to encourage you
all to take this opportunity to meet people you
haven't met, to have a great meeting, and I'm really
looking forward to the results from this conference.
Thank you very much for coming today.
(Applause.)
DR. GOLDMAN: Good morning, and thank you
to Donna-Bea. She's already gone. My name is
Julian Goldman, and I'm here standing here in front
of you to introduce our next speaker. Our next
speaker is Dr. Charles Friedman, and he will be
speaking about device interoperability and the
national health IT agenda.
Dr. Friedman is Chief Science Officer in
the Office of the National Coordinator for Health
Information Technology. And this is a new role for
Dr. Friedman, and in this role he is responsible for
matters related to research, innovation, evaluation,
and education in international programs, a pretty
broad portfolio. Previously, he was the Deputy
National Coordinator for Health IT, and in that role
he worked to build collaborations in the public and
private sector.
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He has a long and interesting and varied
academic background, and I'll just give you a little
snapshot of some of things that he's done. Prior to
joining the Office of the National Coordinator,
Dr. Friedman was Institute Associate Director for
Research Informatics and Information Technology at
the National Heart, Lung and Blood Institute, so the
NIH, and functioned as the Institute's Chief
Information Officer. From 1963 to 2003 he was
Professor and Associate Vice Chancellor for
Biomedical Informatics at the University of
Pittsburgh.
He's also been busy publishing over 150
articles in scientific journals, a textbook that's
quite well known, and is past President of the
American College of Medical Informatics, and he
currently serves as Associate Editor of the Journal
of the American Medical Informatics Association.
I'm really pleased that Dr. Friedman was
able to get away from his busy schedule. There's a
lot going on in the Office of the National
Coordinator today, and we're fortunate to have him
make a commitment before he got pulled away to some
other pressing matters. So thank you for taking the
time to be here, and we look forward to hearing what
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you have to say.
(Applause.)
DR. FRIEDMAN: So good morning, everybody.
I'm delighted to be here. The topic of this meeting
is a topic of great interest to me and to the office.
I do need, in addition to thanking Julian for that
wonderful introduction, to correct one thing. I may
be old, but I could not have been a professor at the
University of Pittsburgh starting in 1963. I don't
know what that date's supposed to be, but I'm old
enough. I don't need to be any older.
DR. GOLDMAN: Now I'm disappointed.
(Laughter.)
DR. FRIEDMAN: Will I be able to advance
the slides myself?
UNIDENTIFIED SPEAKER: You can if you want.
DR. FRIEDMAN: Okay, using what mechanism?
UNIDENTIFIED SPEAKER: Well, we're going to
have change the setup in just a little bit.
UNIDENTIFIED SPEAKER: I can do it. Just
say next slide and --
DR. FRIEDMAN: Because I've got some
builds, and it's going to be kind of weird. Will it
take too much time?
UNIDENTIFIED SPEAKER: One second.
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DR. WEININGER: While they're setting up,
why don't I just make a few quick logistical
announcements.
MR. MURRAY: Speak into the microphone.
DR. WEININGER: While they're setting up,
why don't I make a quick few logistical
announcements. There are coat racks right outside
the door here, so if you want to hang up your coat,
hopefully the temperature will change. I ordered
good weather. Some of it came, and something else
came along with it, so you'll just have to bear with
me. The restrooms are down the hall here and on the
right, and if those are busy and full, there's
restrooms on the symmetric side of the building, on
the other side, so you can use either one. Please
try to stay in the conference center. This is a
relatively secure facility.
There are sign-up sheets for the breakout
sessions on the benches outside, so please sign up in
the category that you think is most interesting. We
have more categories than we have space, and so we'll
do some consolidation, and you might not get your
first pick but, you know, we'll appreciate your
input.
And I want to say that this is a workshop
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and not a conference. The intention here is for us
to bring up the ideas and have lots of good
discussion and try to get a handle on what the issues
are. So please don't feel like it's the folks up
here preaching at you. This is our workshop, and we
should all participate as much as possible.
So thank you very much. I'm Sandy
Weininger. Sorry. John Murray and I are local FDA
hosts, and you can see that we're not professional
workshop organizers, but we'll get through it.
Thanks.
DR. FRIEDMAN: Okay, thank you, thank you.
Thank you. Perfect timing. Absolutely terrific. So
let me launch into my presentation now and begin by
saying what I very much need to say for policy
reasons but also because it's true, that what we are
doing in the Office of the National Coordinator, in
collaboration with a very, very large number of
wonderful people who are supporting us in various
ways in this endeavor, is a work in progress.
The film is still very much in the cutting
room, and there are pieces of film in the final,
going into the final, and the floor is also covered
with outtakes, some of which will be seen eventually
and some of which probably won't. Because of this, a
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lot of what I'm going to tell you today is a
description of work in progress.
What I'm also going to find myself in a
position today is one where, because we have
regulations out on the street and that are in an
open-public comment period, I cannot say anything
that could be construed as a commentary or an
interpretation of that regulation. So if it seems
like I'm doing a little bit of a dance here in terms
of what I say, it's because I am, but it's also the
way it needs to be at this point. I cannot share my
own ideas about these regulations. I can't say
anything that's interpretative in any way with regard
to these things. Just the facts.
With this talk, I think it might be the
best use of a very limited amount of time to frame
your work in a bit of a policy and technology context
that derives from the activities that are ongoing
under this rubric of the national health IT agenda.
And, in fact, I will begin by talking about what I
mean when I use this term national health IT agenda.
So I'll talk about what is going on, the
recent changes that have occurred -- I guess they're
not so recent anymore -- that have set changes in
motion. I'll talk about where we are right now. I
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will introduce this concept that I'm sure you have
all heard about, called meaningful use. Is there
anyone who has not run into this term somewhere along
the line?
And I will describe the plan that has been
put forward, to the extent that it exists right now,
for achieving meaningful use of health information
technology in the country, and I'll say something
about our progress. I think all of this will create
a useful context.
Then, in my closing few slides, I will
bring the theme of this meeting together with the
general national health IT agenda and try to call out
some significant points of intersection which I hope
will provide useful guidance to you all going
forward.
So what do I mean by a national health IT
agenda? Well, if you have to go back in time, and
this seems like a long time ago, you can go back to
April 2004 when former President Bush signed an
executive order that created the position of a
National Coordinator for Health Information
Technology, and along with that executive order and
the creation of the position, a goal was put forward
that a majority of Americans should have their care
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supported by interoperable health records, electronic
health records, by 2014.
An office, as these things tend to happen,
grew up around the position of the National
Coordinator, that office called the Office of the
National Coordinator, charged to provide leadership
for the nation toward this implementation of
interoperable health information technology and an
infrastructure supporting it and, from a historical
perspective, one might call April 2004 and these
events the beginning of a national health IT agenda.
This agenda was, of course, completely
supported by the new administration. It was
referenced by the new President Obama then on January
24th of the previous year, just about a year ago, and
the goal there was to computerize the nation's health
records in five years. That's a quote from his first
radio address. Take note that it isn't a literal
doubling of the goal, but it certainly can be
construed as one. The previous president had said a
majority, and clearly by implication, his successor
said everyone. So the goal on the same timeframe was
considerably accelerated.
Another event happened early in 2009, in
February, on February 17th. The Congress passed and
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the President signed the Recovery Act, which
contained within it an act, a sub-act, if you will,
known as HITECH, and among other things, HITECH
authorized the sum of $2 billion to the Office of the
National Coordinator to support the advancement of
this national health IT agenda. It also called for,
in a separate section of HITECH, a program of
incentives to be paid to eligible providers and
hospitals who attain the state of meaningful use of
health information technology.
A point to emphasize, of course -- and
probably this is not necessary, but I think it's
important to say it anyway -- is that the end goal of
this effort is not technology. We anticipate that
through adoption and meaningful use of health IT
there will result -- other things have to happen as
well, tremendously improved healthcare and population
health for the nation. Donna-Bea referred earlier to
the unsustainability of the cost and growth in the
cost of healthcare in this country and clearly
greater efficiency as well as safety of healthcare
are goals that are envisioned through health IT and
meaningful use.
So just to show you what lies ahead of us,
let's take a look at where we are right now. One of
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the things we do at ONC is survey the nation on the
state of health IT adoption or EHR adoption. And we
have not quite reached the point of being ready to
release the 2009 figures, but here are figures for
late 2008, and you will see that adoption of at least
a basic system in physician offices in the country
stands at 21 percent right now. Seventeen percent
have what's called a basic system. An additional
four percent have what's called a fully functional
system.
The situation in hospitals, again, based on
2008 data that were published in 2009, suggest that
adoption of at least a basic EHR across all units of
hospitals in the United States stands at something
like 11 percent. Now that's a little bit misleading.
I'm not telling you that if you walk into nine out of
10 hospitals, you won't see a single computer in use
in support of patient care. What this statistic
reports is the number that have at least a basic
system installed on all clinical units. If you break
out some of the date in this article -- and I would
suggest you take a look at this article to see the
details -- you will see, for example, some figures
more in line with what the casual observer in a
hospital would observe, laboratory and radiology
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reports being supported by electronic technology in
about three-quarters of the hospitals, across all
units, drug allergy and interaction alerts in about
half, and an electronic medication list in about
half.
So those figures that look low with regard
to hospital adoption does not mean that many
hospitals are not along the pathway to adoption. It
reflects the number of hospitals that meet all of a
set of criteria for adoption with the technology
reported installed across all units.
We have also made progress, and many of you
either know about or maybe have even been directly
involved in the effort in building a so-called
Nationwide Health Information Network. I'll return
to this in a little bit of detail later. It is a
pillar of an interoperability agenda for the nation.
I just want to say for the moment that the NHIN, as
it is known, is not a separate physical pipe for the
movement of electronic health information. It sits
on top of the internet, uses most, if not all, of the
internet protocols. What it is is a system of
standards, services, and agreement for secure and
trusted connections that lies on top of the internet,
and it is a project that we have been working on for
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several years. So that's kind of where we are now.
Let's move a little bit into the realm of
policy, exploring what meaningful use is and what
progress we have made along this pathway.
One way to look at what we have been asked
to do by Congress in the HITECH law is to take the
law itself, the statute, and take it apart into
components. And this is a useful way to start. And
one can see that HITECH, if you take the law apart,
really consigns ONC to do four things.
One could be listed under the topic of
national coordination through an office that is now
in statute as opposed to being the product of an
executive order. ONC is now established through an
act of Congress, not through an act of the
presidential pen. It would take an act of Congress
to uncreate ONC now that an act of Congress has put
it in statute.
A second component of HITECH, based on the
law, is this program of payment incentives to
eligible providers and hospitals who achieve this
status of meaningful use of certified EHRs. That's
another key point, that meaningful use can't be
meaningful use of any EHR. It has to be meaningful
use of a certified EHR.
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There have been various estimates of what
this program will cost. These are all estimates of
net costs after taking into account the savings that
will be realized for meaningful use, in addition to
the amount of the incentives that will actually be
paid. The incentive payments begin in 2011, and they
can be paid through either Medicare or Medicaid.
There are several supportive grant programs
authorized in HITECH, and then there are enhanced
privacy and security provisions also called out. So
if you want a kind of very high-level way to think
about HITECH, you can divide it into these four
categories. I'm going to run you very quickly
through each one now.
Under national coordination, I mentioned
ONC becoming a permanent organization. The law
created two new federal advisory committees, one for
policy and one for standards. We are required to and
are in the process of beginning to revise the health
IT strategic plan. We are to adopt an initial set of
standards and certification criteria, we are to
establish a certification process, and we are to
establish a governance of the Nationwide Health
Information Network that I mentioned before, in
addition to many other things, but this is sort of
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the highlights under national coordination.
I mentioned payment incentives and
meaningful use as the second component. An important
point to highlight here is that meaningful use really
is a game-changer in the way information technology
is conceptualized. Meaningful use changes the focus
from a technologically oriented focus, rooted in
adoption, is the technology there, is it turned on,
to a focus on behavior. Meaningful use is all about
what clinicians are doing with the technology, not
whether it's there and whether it's turned on.
The law also specifies some significant
aspects of meaningful use. I mentioned that a
meaningful user must use a certified EHR. A
meaningful user must also exchange health
information. This brings in, explicitly, the
interoperability agenda that is a focus of this
meeting, and meaningful users must also be able to
report -- must actually report if they are a
meaningful user of quality measures.
We have implemented -- and I think many of
you know about these programs -- a whole set of grant
programs that were authorized under HITECH, a program
of implementation assistance that is being realized
through the creation of a program of regional
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extension centers. There is a grants program with
awards to states and territories to promote health
IT. These grants are focusing on emphasizing health
information exchange, another major connection to
interoperability.
There are actually four separate grant
programs that are directed at building the health IT
workforce. We have on the street a funding
opportunity announcement to create a set of beacon
communities which are to be examples of exemplary
application and meaningful use of health IT. And we
have on the street -- applications are actually due
tonight. So if you're planning to write one and
haven't started, I'm not sure why you're sitting
here.
(Laughter.)
DR. FRIEDMAN: There is a program of health
IT research activities with four focus areas, many of
which touch on the topic of this meeting, that is
underway and will be implemented. We have just
privacy provisions. There are many called out in
HITECH, one that's very, very important. We are
required to and will and are in the process of
recruiting a national chief privacy officer. All of
this, of course, goes to the essential element of
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trust, that the public must trust that their data in
electronic form are protected. And I will, in the
interest of time, probably not elaborate on that. I
think that point is clear and important.
So let me now say a few comments about the
progress we have made toward implementing the
programs that are mentioned in the HITECH Act and
that I reviewed before.
In order to describe our progress, I'm
going to take a slightly different tack in describing
what we are doing. Instead of parsing the law point
by point, I'm going to talk about how some of these
activities come together. And one way to think about
this is that the movement toward meaningful use can
be seen as having two key strategic elements.
The first element is adoption of health IT
systems. The second element is the establishment of
a trusted pathway for health information exchange.
If you superimpose these two elements, you then have
the infrastructure in place that is necessary to
enable meaningful use, adoption of technology, and
the ability to move information, the essential
information mobility, in a trusted fashion that is a
requirement for meeting, then, all of the statutory
components of meaningful use, adoption of certified
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EHRs, health information exchange, and quality of
reporting.
So, what are we doing to build Element 1,
adopted health IT systems? I'll remind you where we
stand with regard to progress. If this were the
United Way, our campaign at the moment would not be
in very good shape. There are many things we were
doing, but we can call out four primary initiatives
that relate to adoption and can be seen as movers of
the nation to adoption, and we have made significant
progress along each of these areas.
With regard to the payment incentives for
meaningful use, it is necessary first to establish a
legal definition for what meaningful use would be, in
other words, to establish a clear criterion that must
be attained before an eligible provider or a hospital
would be able to receive these payment incentives.
As I mentioned at the very beginning of
this talk, there is a NPRM, a Notice of Proposed Rule
Making, on the street in a public comment period.
That is a proposed regulation that would define the
first stage of meaningful use. That was released on
December 30th and is in a two-month public comment
period. It is great reading, and I encourage you to
look at it and please do comment on it because we are
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very dependent on having your comments.
I should add that HITECH gave CMS, not ONC,
primary responsibility for developing the regulation.
We, of course, were very closely involved in a
collaborative role with CMS in developing this.
The regional extension centers grants are a
major catalyst for addressing Element 1, that is,
moving the nation toward higher levels of adoption of
health IT systems as a foundation for meaningful use.
The funding opportunity for the first round of
regional extension centers was issued on August 20th,
and that process of identifying the first set of
regional extension centers is well along.
A number of health IT workforce grant
opportunities were issued in November and December.
There are many, many estimates on the street of the
number of additional trained health IT workers that
will be needed to support a national movement to
meaningful use. One estimate that we have been using
is approximately 50,000 over and above what the
system at its projected rate of growth would produce
if unamplified. So these funding opportunities will
amplify the system and build workforce capacity.
With regard to a certification program to
establish what are the criteria for these systems to
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achieve that status of certification which is
required as a basis of meaningful use, there is an
interim final rule expressing an initial set of
certification criteria that has been issued and that
was issued on December 30th.
Element 2 goes to this trusted pathway to
exchange information. The primary initiatives to
support this can be seen as standards, the grants to
the states that I mentioned before, the Nationwide
Health Information Network, and privacy and security.
I will mention, just to call out some of the progress
we have made, the same interim final rule that
propounds an initial set of certification criteria
that was issued on December 30th also advances an
initial set of standards that are primarily designed
to support that first stage of meaningful use.
Grants to states funding opportunity was
also issued on August 20th, and the selection and
award to recipients of these grants is at a very
advanced stage.
The Nationwide Health Information Network
is, at the moment, being redesigned and reformulated
but also is entering, at the same time, into very
limited early production. So progress is being made
with the NHIN, and there are a number of activities
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underway relating to privacy and security. I saw you
have time sheets there. How much time do I have?
UNIDENTIFIED SPEAKER: You have plenty of
time.
DR. FRIEDMAN: I have plenty of time?
UNIDENTIFIED SPEAKER: Yeah. Fifteen
minutes.
DR. FRIEDMAN: Okay. Pardon me?
UNIDENTIFIED SPEAKER: Fifteen.
DR. FRIEDMAN: Okay.
MR. MURRAY: We're just preparing for the
end.
DR. FRIEDMAN: You're just preparing for
the end.
MR. MURRAY: But you have plenty of time.
Twenty minutes.
DR. FRIEDMAN: So I'm at the end of the
beginning now.
MR. MURRAY: We're just learning how to do
this.
DR. FRIEDMAN: Okay.
MR. MURRAY: Bear with us.
DR. FRIEDMAN: So just a little bit of
sidebar. And I think it's important just to mention
this, and I you have more questions about it, we can
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address this perhaps in the question and answer
period. You may have come to your own conclusion as
you've listened to me talk about this Element 1 and
Element 2 adoption and a mechanism of trusted
information exchange, that Element 1 and Element 2 by
themselves will not get the nation where it needs to
go.
Elements 1 and 2 by themselves will not
support the development of a learning healthcare
system or a system of population health, which -- all
of which are dependent on the ability to aggregate
information, again, in a trusted and secure way, and
perform analyses on data that are aggregated in some
way so decisions about the state of populations,
looking across individual patients, can be made.
So there is, although our plans to develop
it are not nearly so well formulated, also an Element
3. Element 3 are the additional components of a
national infrastructure that are going to be
necessary to move the nation to a learning healthcare
system, a system that can collect data about care and
data from other sources, put it together, figure out
what's working, figure out what's not working, and in
that way generate knowledge that can be used to drive
improvements. Element 3 is also required for
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population health activities to support basic and
clinical research, taking advantage of the
capabilities that will be put in place through the
other two elements, to do post-market drug
surveillance, to do biosurveillance, epidemic
detection and tracking.
And you can think of Element 3 as requiring
three underlying components, what can be called
gridware, that which puts the data that are needed
together and moves it from where it is to where it's
needed, learningware, which are the analytics
necessary to discover new knowledge to make sense out
of the data once aggregated, and what Craig Mundie
from Microsoft persuaded me to call cool apps, which
are the component of the system that end-users
actually interact with and do have a value for them.
So three elements, two of which I described
in some detail and a third which is conceptually
important but not yet the focus of an ONC-oriented
coherent program yet, can be seen as the elements
which together comprise the national health IT
agenda.
So let me know, as I draw this presentation
to a close, bring that policy and technology and
statutory framework that I described into some
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juxtaposition with the device interoperability
concepts that are the themes of this meeting. So to
begin, let me direct you to places where there are
resources where you can track the process of
meaningful use being defined. The first document I
would call your attention to is a set of
recommendations that came forward from the Health IT
Policy Committee in August of 2009. All of these can
be found on our website, healthit.hhs.gov/
meaningfuluse. Excuse me. And the second document
is the proposed rule which came forward formally from
CMS and was published on December 30th of 2009.
These documents are a very important
foundation to give you a sense of how the definition
of meaningful use is evolving. Meaningful use, as it
evolves, as it is defined and as it evolves, is going
to be an important policy framework and foundation, I
believe, for the device community to be aware of and
to engage with in order to pursue the agenda, I
believe, you are about at this meeting.
When you look at the policy priorities for
meaningful use, which are expressed both in the
recommendations of the policy committee and also in
the Stage 1 proposed rule, which builds heavily on
those recommendations, you will see that there are
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four policy priorities. These policy priorities, you
will notice, are not IT priorities. They are not IT
goals. They are health goals. The first is to
improve the quality, safety, efficiency of healthcare
and reduce disparities. The second is to engage
patients and families. The third is to improve care
coordination. The fourth is to improve population
and public health. And the fifth is to ensure
adequate privacy and security. So meaningful use is
use of health IT in pursuit of these goals.
Another key point to recognize about
meaningful use as it is unfolding is that meaningful
use will not be defined once and remain defined as
such forevermore. The definition of meaningful use
will follow an escalation path, and right now three
stages of meaningful use definitions are envisioned.
Stage 1 -- and the emphasis of the proposed
rule on the street right now is Stage 1 -- will
articulate the criteria for meaningful use that will
take effect in the first year for which hospitals and
eligible providers are eligible to receive incentive
payments. That was a mouthful. Did that make sense?
So align Stage 1, even though the rule
making process is starting earlier, so the rule would
be in place by the time it is needed, align Stage 1
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with 2011 because that is the first year any eligible
provider or hospital can be deemed a meaningful user.
The Stage 1 proposed meaningful use criteria are
multifaceted, but if you have to put a word or a
label on them to summarize them, it would be an
emphasis on the capture and storage and sharing of
data. Stage 1 is Stage 1.
Stage 2, as envisioned by the policy
committee -- and the slide I'm showing you here is
directly from the recommendations of the policy
committee -- as you would expect, envisions and
anticipates more sophisticated use of health IT in
support of those five policy priorities. And a label
you can put on the Stage 2 criteria is advanced care
and processes with decision support.
And Stage 3, which you can align with the
year 2015, are criteria that envision improved
outcomes. So it is a graduated process beginning in
2011 and culminating in 2015. That is the vision for
meaningful use and the evolution of this definition.
So when Julian and I were talking about
this talk and how it might be helpful to you all, one
of the things we talked about was the relationship
between these meaningful use policy priorities and
the device interoperability themes that are the foci
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of this meeting. So Julian and I worked together to
develop this crosswalk, and I think it's pretty clear
that the various policy priorities underlying
meaningful use relate quite clearly and closely to
the requirements that might be realized through
increased and improved device interoperability.
Under improved quality, safety and
efficiency, and disparity reduction of healthcare, it
can be seen that accurate, complete, and automated
data capture, through devices and of course
everything else that feeds data to electronic health
record systems, is necessary to achieve these goals.
With regard to engaging patients and
families, relating this back to the theme of this
meeting, home-based medical device data acquisition
is important to engage patients and family
participation in care. So there's a relationship
there. Improved care coordination also requires
accurate, complete, and automated data capture, back
to bullet one.
Improvement of population and public health
connects because a national infrastructure that
supports interoperable devices will clearly also
support comprehensive population and medical
surveillance. And, finally, with regard to privacy
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and security, a device data security model must be
part of a modern medical device development
regulation and certification environment. So at a
conceptual level, what you are to be addressing at
this meeting clearly relates to the policy priorities
of meaningful use.
So in the previous slide I described a
conceptual relationship between meaningful use and
the development of device interoperability. What
would we see if we actually looked at the documents
that are on the street? Well, if you search the
Health IT Policy Committee recommendations for
meaningful use -- and particularly a wonderful
document. It's a 10-page document that I couldn't
show you on a slide, and it's a whole matrix laying
out the policy committee's vision of meaningful use
for 2011, 13, and 15, and I highly recommend that you
take a look at it.
But if you search that document for
interoperability or any kind of reasonable substring
of interoperability, you'll find that that word
appears once and you will find that the word device
appears four times. But that's really not what's
important. What's important is that medical device
interoperability in the policy vision put forward by
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the policy committee is specifically envisioned for
2015. You will see it right there in the matrix.
You will also see, in the vision of
meaningful use for 2013, that data feeds from home-
monitoring devices under -- relating to the engaging
patients and families policy priority is a specific
objective envisioned for 2013.
So the string matches might be a little bit
misleading there, in terms of their frequency, and
point of fact, there are two clear connections
between these policy recommendations and medical
device interoperability.
In the CMS proposed rule, the NPRM that is
on the street for comment, interoperability appears
18 times and device appears two times, and the
context in which device appears is in relation to the
definition of computerized provider order entry and
really isn't device in the context that I think this
meeting is focused on. But remember that the
meaningful use regulation, proposed rule that is on
the street now, is focused on Stage 1 or the 2011
criterion.
So to bring this to a close -- and again, I
have to be careful about being seen as commenting on
the proposed rule. But I think it is a descriptive
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statement to say that the conceptual connection
between meaningful use and interoperability is
illustrated by the proposed rule, seen particularly
in the proposed rule's emphasis on interoperability
as a key important component of meaningful use. If
you look at ONC's agenda, as I outlined it with these
elements, interoperability goes directly to Element 2
and Element 2 to many activities that we are
currently engaged in.
A second comment I would leave you with is
that interoperable devices, as what might be seen as
a domain, have significant potential to advance the
policy priorities of meaningful use, and the signal
for this is the specific reference in the policy
committee's recommendations, which are only
recommendations but important nonetheless, that
specifically call out topics of direct interest to
this meeting for -- as recommendations for the 2013
and 2015 definitions of meaningful use, which will be
determined in the future.
So what I've tried to outline for you
today, bringing this to a close, is what we are doing
in the Office of the National Coordinator, what the
policy framework is that guides what we are doing,
where we are, the enormous amount of work that we
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have left that we will need your help to bring to
completion, and also the existence as what might be
seen as a convergence path between what you all are
about here today and where meaningful use, if one can
read the signs that are out there, is quite possibly
going to be headed.
So I think we are singing in the same key.
We have not yet joined the choirs, but I think there
is enormous potential for that to happen. So we are
enormously interested in the work you all will be
doing here over the next few days, and I hope my
participation in this meeting can be one foundation
for future interaction between us. Thank you very
much.
(Applause.)
DR. FRIEDMAN: Did I leave time for some
questions?
DR. GOLDMAN: Yeah, please.
DR. FRIEDMAN: Do you want people to use
the microphone?
UNIDENTIFIED SPEAKER: Yes, please.
DR. GOLDMAN: Yeah, please use the
microphone and introduce yourself.
UNIDENTIFIED SPEAKER: You've used the word
quality a number of times, Dr. Friedman, throughout
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your talk. Have you gotten to the point where you
have operationalized it or begun to operationalize
it? How are we going to measure whether you've
achieved quality in this context?
DR. FRIEDMAN: Okay, that's a great
question. I think if you access the proposed rule,
you will see many of the Stage 1 criteria for
meaningful use, proposed Stage 1 criteria for
meaningful use laid out and specific quality measures
to be reported are included in that proposed rule.
So it's there, and it couldn't be more explicit.
Again, this is open for public comment. If you have
comments on what's there, we'd love to hear from you.
DR. GOLDMAN: A very shy audience.
DR. FRIEDMAN: Well, you must have a
question.
DR. GOLDMAN: Well, I actually would like
to just clarify. I want to say, from here, I want to
correct what I said because I misspoke and you
pointed that out. So for the record, because of, you
know, where we are, that your position as Associate
Vice Chancellor was 1996 to 2003, apparently. So the
error was mine.
DR. FRIEDMAN: And while you're making that
statement, change my hair color?
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DR. GOLDMAN: Yes. You're looking younger
right now.
So are there any other questions for
Dr. Friedman? Yes, please come up to the microphone.
MS. BORRELLI: Good morning, Dr. Friedman.
I'm Alice Borrelli from Intel.
DR. FRIEDMAN: Hi, Alice.
MS. BORRELLI: I feel enlightened now that
I happened to read the fine print pages. But I do
have a specific question about how many -- I think
you got at this to a very good degree, but if you
could go a little deeper on how do the 2011 -- and as
outlined in the order, really lay the groundwork to
ensure that there's interoperability and that home
devices will be able to be formed in as 2013 and 2015
rollout? Is there -- work being done to ensure that
that happens?
DR. FRIEDMAN: That's a very good question.
I think that the important thing to say in responding
is that Stage 1 is Stage 1 and you build the edifice
from the ground up. And I think, again, if you look
at the meaningful use requirements and particularly
the certification criteria which are contained in
what can be seen as a kind of companion document in
the interim final rule, you will see how we have
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built Stage 1, the conception of Stage 1, CMS and us,
to be that from both a policy and technology
perspective, that foundational element.
While you won't see devices mentioned, what
you will see are the concepts of interoperability
that apply not just to devices but to any information
exchange process which must have a set of features in
order for the goal -- that ultimately that data in
computable form can move from where it is accurately
to where it's needed, with the data at the receiving
end having the same meaning as it did at the
transmission point. You will see how those general
concepts are being baked into this foundation.
So I think if this plays out as we all
envision it, and I very much believe it will, this
community, as it thinks specifically about devices
and how they play into this, will be able to build on
this solid foundation which not only enables the
specific functionality required for Stage 1
meaningful use but also creates the potential for the
next and more sophisticated stages to follow.
DR. ZALESKI: Good morning, Dr. Friedman.
John Zaleski from Philips Research. In attributes in
your Element 3, it looked like, in some regard
related to clinical decision support, was that the
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intent? I mean, obviously it extends beyond that
but --
DR. FRIEDMAN: Um-hum.
DR. ZALESKI: -- there is a clinical
decision support flavor to some of those
applications, the coolware, as an example, which you
were referring to.
DR. FRIEDMAN: Um-hum.
DR. ZALESKI: Is that a correct assumption
or is that -- am I off the mark?
DR. FRIEDMAN: Clinical decision support,
in its most sophisticated and fully elaborated form,
requires Element 3 because you can envision, in a
learning healthcare system, the studies that are done
which generate new knowledge, can then find their way
into the knowledge bases that are the drivers of
clinical decision support, and you have a kind of
continuous quality improvement cycle enabled by
Element 3. So, yes, the nirvana of clinical decision
support requires Element 3.
But I think it's also the case that
decision support, to be -- that is effective to a
significant degree, does not require that automated
creation of knowledge. So there are also elements --
there are also significant components of decision
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support. Call it as part of Element 1, as well. And
if you read the Stage 1 NPRM or look at the
meaningful use matrix from the policy committee,
you'll see decision support called out there, but not
of that most sophisticated nature.
DR. ZALESKI: I've been reading it. I've
been going through it. My reason for asking that is,
frequently, when clinical decision support is thrown
out there, specifically in the context of CPOE or in
EMR systems as opposed to real-life device, and
that's what I was referring to.
DR. FRIEDMAN: Right. And I understand the
distinction, and it's the same scenario. You start
basic in a way that lays the potential for greater
sophistication, and you add the sophistication over
time.
DR. GOLDMAN: Thank you very much,
Dr. Friedman.
DR. FRIEDMAN: Thank you.
(Applause.)
MR. MURRAY: Last Wednesday here at CDRH,
we had a very exciting day. We were all gathered to
hear the Center Director tell us our strategic plan
for 2010, and we were all sitting there quietly and
patiently waiting for him, and who showed up but the
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Commissioner of the FDA, and she had some really
great news for us at CDRH.
We now have a permanent Center Director,
Dr. Jeffrey Shuren, who received his juris doctorate
degree from the University of Michigan, has a medical
doctor degree from Northwest University. He's board-
certified in neurology, he's been an assistant
professor of neurology, and he's worked for the FDA,
I think, for about 11 or 12 years. He's worked in
Medicare/Medicaid, he was in the Office of Policy, he
was an Associate Commissioner, and I think it's great
that we have him today to speak to us, and I'd like
to welcome Dr. Shuren to the podium. Thank you.
(Applause.)
DR. SHUREN: Good morning. Well, thank you
for coming to discuss this important topic, and I can
see clearly by the number of people in attendance
here that it's an important issue for FDA, the
medical device industry, and the healthcare
community. I understand that this topic has been
under discussion for many years, and it's my hope
that this workshop can provide the necessary impetus
to make medical device interoperability a reality.
The commercial marketplace has already
created many capable interoperable systems. All
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around us, technology provides products that work
together, ranging from your computer, to your TV, to
your car. Interoperability is everywhere, and it's
created huge benefits for millions of people. It's
improved productivity, efficiency, and jobs. We have
new things like automated and web-bill payments.
We've got safer things like traffic reports. And we
even have some new problems like texting while
driving.
We at FDA believe that the technology and
the knowledge are currently available to design,
develop, and implement a safe and effective medical
device interoperability system. What we need to do
is to pull it all together first by answering several
critical questions. That's why we're here today.
Today, for the most part, the majority of
medical devices are not interconnected and hence not
interoperable. In this environment, each device is
represented by a single standalone product or entity.
Data from each individual device is presented
separately to the practitioner. It has been the
responsibility of the practitioner to integrate the
data from these independent sources.
These individual medical devices provided
by many medical device manufacturers are generally
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designed to operate independently. They do not
address interfacing with other devices and therefore
generally are reviewed and regulated by FDA on an
individual basis. As a result, the integration of
device data and interoperability of devices has
become the responsibility of the operator of the
device, often the clinical practitioner.
For example, a pulse oximeter won't work
downstream from a blood pressure cuff because no
pulses get through. It's the responsibility of the
practitioner to understand how to use the devices
properly.
In another case, a patient's ventilator was
shut off to allow an X-ray to be taken without motion
artifact. However, the X-ray film got jammed and the
medical team worked diligently to get it out, but no
one remembered to turn the ventilator back on, and so
the patient died.
In some advanced systems, several
manufacturers have created integrated and somewhat
interoperable devices that only include their own
proprietary product line. This partial integration
is achieved through proprietary interfaces that are
manufacturer specific. These proprietary interfaces
modify the original FDA-approved products. In these
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instances, the modifications are typically reviewed
by FDA.
The partially integrated clinical
environment performs some of the synthesis and
integration that was typically performed by the
practitioner. In some situations the practitioner
gives up to the integrated device some responsibility
for safety.
MR. MURRAY: Can you go one slide ahead?
DR. SHUREN: What's that?
MR. MURRAY: One more slide ahead.
DR. SHUREN: Oops, didn't click it. There
we go. So as interoperability increases, we see a
possible transfer of safety responsibility from the
practitioner to the machine or the system. And
several examples come to mind, like alarm integration
and prioritization, automated blood pressure tracking
correlated with ECG and trending leading to an alarm
condition, and automated remote practitioner
notifications.
As a clinical device environment becomes
completely interoperable, the ability for truly
integrated plug-and-play will emerge. This
interoperable clinical environment can be described
as follows: it contains open and nonproprietary,
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manufacturer-independent interfaces; it provides for
autonomous integration, operability, and
communication between multiple vendor devices; it
provides the ability to deliver enhanced patient care
and safety systems through customized synthesis and
integration and automated safety interlocks; it
provides for the implementation of safety interlocks
in a multi-vendor environment; and it allows for the
flexible clinical application of devices in a multi-
vendor environment.
Just as interoperability in the commercial
world has achieved great success and impact, the
focus of device interoperability should be to achieve
beneficial clinical impact. This slide identifies
several examples or types of potential clinical
impact. And here's how an interoperable clinical
environment can improve patient care.
First, the ability to interchange sensors
and actuators, based on clinical need, allows us to
transition from an equipment-centric environment to
one that is more patient centric. The practitioner
will have the ability to unplug an existing module
and select a new module that may provide more
appropriate functionality for the patient without the
traditional restrictions of proprietary or legacy
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standalone device systems.
Secondly, greater availability and cost
competitiveness of devices may be achieved by the
reuse and reduction of costly infrastructure that
would traditionally have been designed and developed
by each individual manufacturer. Ideally, this leads
to increased patient accessibility to device-based
care.
Third, these systems will allow for the
implementation of patient-centric safety interlocks
across a broad spectrum of devices and device
manufacturers. For example, interoperability could
allow for automatic synchronization between a
ventilator and imaging equipment designed to take a
picture during the ventilatory pause.
Fourth, these systems can allow for the
implementation of functionality that may result in
improved quality assurance, such as assurance that
patient-specific data is recorded and transmitted in
appropriate and consistent units. So, for example,
it could prevent patient weight recorded in pounds
from being sent to a pump that computes the dosage in
kilograms.
Fifth, the practitioner has the ability to
combine device functionality and data in a way that
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best suits the specific patient clinical need.
And sixth, the practitioner can automate
protocols to perform device readiness checks and
automate setup of clinical applications and safety
interlocks.
It should be no surprise here that the
number one challenge to assure the safety and
effectiveness in an environment of interoperable
devices is what's prominent in FDA's mind. But
before we can even begin to take on that challenge,
we need to assure that we ask all the right questions
and address those questions with valid science.
Answering these questions will help us identify what
tools we need to develop to facilitate and assure the
safety and effectiveness of interoperable devices.
These tools may include standards, guidance, test
methods, protocols, and certifications.
At a minimum, FDA traditionally examines
these issues to assure the safety and effectiveness
of devices, namely clinical, engineering, risk, and
management. We will need to examine the specific
clinical scenarios to understand the intended uses,
clinical applications, and their effect on public
health. In addition, clinical scenarios and
applications can be used as a basis for determining
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intended use and for identifying potential
contraindications.
The quality and safety of these systems is
highly dependent on proper design. Assuring proper
design includes a well-defined system. The list
above identifies a set of design elements that should
be defined. This applies not only to the individual
devices but also to the system in which the devices
interface, namely a system of systems.
Identification of the involved risks is
critical. It can drive engineering design as well as
the regulatory review process. Such risk includes
those inherent in individual devices, those inherent
in the multiple-device environment, and those present
in the clinical environment.
And, lastly, there are many unanswered and
yet unposed questions related to the management and
control of these types of systems. Establishing the
appropriate management control system will be
necessary to assure the initial and continuing safety
and effectiveness of these interoperable systems.
Important questions to be addressed include who is
going to develop and maintain the tools, who's going
to implement the tools, and who is going to decide if
the tools are efficient to assure safety and
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effectiveness.
So with that, let me end by thanking all of
you for attending today's workshop and for what we
hope is going to be a lively dialogue. Thank you.
(Applause.)
DR. GOLDMAN: Thank you very much,
Dr. Shuren. I know you have to run off to another
meeting. We appreciate you taking the time today.
DR. SHUREN: I actually can stay for a
little bit.
DR. GOLDMAN: Okay. Well, I'd like to
introduce our next speaker. There he is,
Dr. Doug Rosendale. I'll tell you a little bit about
Dr. Rosendale. He's the Director of Joint
Interoperability Ventures within the Veterans Health
Administration, Office of Health Information, OHI,
and he's also a board-certified general surgeon. And
I won't even make any jokes about that. He's the
Chair of the Surgery Discipline for the American
College of Osteopathic Surgeons and was previously
Chief of Staff in the private sector and Chief of
Surgery at Grand Junction VA Medical Center in
Colorado, and he trained in medical informatics and
is an affiliate faculty at the Harvard Medical School
Decision Support Group.
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Dr. Rosendale's health IT background spans
many aspects. He's been active, I think one way to
characterize it is in health IT that relates to
patient safety initiatives, especially around
surgical care. And he's received awards for that
from the American College of Osteopathic Surgeons.
He's widely published and has been working this past
couple of years with the White House on a number of
initiatives also that relate to interoperability for
public health. And for that, I'm very pleased to be
able to welcome Dr. Rosendale.
(Applause.)
DR. ROSENDALE: Okay. Well, audiovisual
never stops me.
DR. GOLDMAN: What happened?
DR. ROSENDALE: Oh, they're trying to load
my deck.
DR. GOLDMAN: It'll just take a minute.
DR. ROSENDALE: Yeah. But I'm good. I can
do it without.
DR. GOLDMAN: So how's the weather in
Colorado?
DR. ROSENDALE: You know, I haven't been
there in a week. I decided to spend two weeks here
in the Beltway, so now I'm learning about rain.
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Thank you for having me, by the way. I'm Doug
Rosendale. I'm a surgeon from Western Colorado. If
you haven't noticed the boots, I wear them a lot, and
I'm considered the Colorado cowboy for that reason.
Just for interest, I'm curious what the
target audience is. My military guys tell me that
there's always a target for something, and so --
(Laughter.)
DR. ROSENDALE: So I need to understand who
I'm talking to. So by raising your hand, can you
tell me -- and by the way, I don't do well behind
podiums. I want to move, and if that camera would
follow me, that'd be great. How many people here are
policy makers? Any policy people? How many people
here are clinicians, like doctors, nurses, allied
health professionals? And how many people here are
technology-oriented individuals? Oh my, now I'm in
deep trouble. That's why I wear these boots.
(Laughter.)
UNIDENTIFIED SPEAKER: High boots.
DR. ROSENDALE: High boots, that's right.
All right. Well, I've got a pretty good idea of who
we're talking to, and I think this is a very exciting
discussion, something that Julian and Sandy and I
have been talking about for a long time.
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My primary goal is to talk about levels of
interoperability. It's not just interoperability.
And by the way, nobody I know in Western Colorado
knows what that word means, and I refuse to give up
on it because it's a very important word.
Interoperability means that things talk to each
other, and we don't do that too well, and when my
daughters were 13 and 14, they didn't talk well at
all to me, so I know what's that about.
By way of introduction, first of all, I was
trained in general surgery, and I come from the
Veterans Affairs. And I know I'm going to get
through this without that slide back. I'm going to
try my best. The idea is that we come from Veterans
Affairs. There's about 150-plus hospitals and 13
clinics. How many folks are familiar with the
electronic medical record that Veterans Affairs uses?
You're pretty familiar with that. So you know it's
really integrated. It's an integrated solution where
the ancillary services like lab and rad and pharm and
the EMR itself are all integrated. And so now we're
on this beacon horizon of opportunity with things
like OR systems and ICU systems. And I heard the
gentleman here from Philips.
So all of those physiologic tracking
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solutions have to be managed within the point of
care, so in the ICU, ER, OR, those areas. We're
good. Okay, let's see how many slides I got through
without using them. See, I'm not a slide guy, so I
like to use a lot of pictures. So I just hit the
button?
UNIDENTIFIED SPEAKER: Go ahead.
DR. ROSENDALE: Can you hit buttons for me?
UNIDENTIFIED SPEAKER: You go forward and
back with the arrows.
DR. ROSENDALE: Okay, got it. I have to
read that? Okay. All right. So basically Julian
introduced some of these things. I'll catch up on
the slide deck. You know, VA has been working --
we've done this for about 20 years, working on
integrating our electronic medical record. What I do
now is I run the Joint Interoperability Venture
portfolio for Veterans Health Affairs' Office of
Information. What does that mean? It means that we
are trying to reach out and integrate with our
military colleagues, and so there are about 50 -- I
was talking about the numbers of hospitals. There's
about 50 Army, Navy, and Air Force hospitals that we
work with. We have what we call sharing environments
or joint ventures.
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And so in North Chicago there's a specific
pilot where the Navy hospital is integrating with the
VA hospital into a single building, and if you know
anything about moving in with your in-laws, it's not
easy. And so there are challenges with trusted
partnerships and infrastructure and firewalls and
fiber between the systems, and what we discovered is,
from a business architect perspective -- and I'm a
wannabe business architect -- the business
architecture is really what drives all of the
infrastructure architects -- architectures.
And so what we discovered is, as you need
to have identity management, first, you need to make
sure you're reconciling the patient. How many folks
here are working on specifically identifying
management solutions with device interoperability
with probabilistic matching solutions? Anybody doing
that? One guy. So that's very telling, and so I got
to tee this up. So I need to tell a story about the
pathologist and the private care doctor and the
surgeon. And they all in part of the world -- and
it's like every doggone morning somebody's goose
hunting.
And so these three docs decide to go goose
hunting, and they're in their duck blind, which is
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really a goose blind, and a flock of geese fly over,
and the pathologist goes, well, you know, the surgeon
and the primary care doc, the family doc, brought me
out here, so they must be geese, so I guess I'll
shoot one and then I'll dissect it and find out for
sure. And boom, boom, boom, he shoots the goose and
he gets one and he's happy.
And then another flock of geese fly over
and the internist -- or the primary care doctor says,
well, I'm not sure what they are, but I've been
looking at the droppings and I did a few tests, and
it looks like it's probably a goose and not a duck
and not an eagle. So blam, blam, blam, and he shoots
these geese out of the sky. And they're all happy.
And then the surgeon sees the next flock of
geese fly over, and he goes, blam, blam, blam. What
the hell were those, anyway?
(Laughter.)
DR. ROSENDALE: And the reason this is an
important point -- and I've told this joke a thousand
times, but not quite like that, in the context of
identity management. You want to make sure that was
a goose because if you don't have a license for a
goose and you shot a duck, or what I do at my back
deck is I shoot woodpeckers and that's really
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illegal --
(Laughter.)
DR. ROSENDALE: -- is you have to make sure
you've got the right bird, the right patient. And
why is that important for device interoperability?
It's important because when you're looking at the
North Chicago environment, a patient comes into the
hospital, the first thing they're going to do is go
up to that clerk and they're going to get registered
into the system.
Well, guess what? They're not registered
in the DoD system. They're only registered in the VA
system. Or they come up and they talk to the DoD
clerk and they're not registered in the VA system.
All of a sudden you have a mismatch. You don't have
the right patient. So you got to the duck, you don't
have a goose, and that's a problem.
And so the first thing we had to manage is
the identity management circumstance and registering
patients jointly in the two electronic records.
Well, that's no different for a device. The device
has to know that you've got the right patient. Why
this is pervasive and critical is if you start at the
point of care in the ICU, once you get registered and
you're in an EMR, and then you want to think about
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how that information is ultimately going to be shared
through the NHIN -- I guess we can't call it the
N-HIN anymore. It's now the NHIN, which sounds like
ninny, and I can't even deal with that.
But the point being is you have to make
sure that that identity of that patient transcends
from the point of care, the device, and -- oh, by the
way, the devices need to be talking to each other.
That's what the smart guys have already talked about
here today. And then if that information, that
physiologic information is an analytic data store, it
needs to be stored in the EMR in such a way -- I got
to catch up with my slides now.
By the way, this is our landscape. This is
what we have to deal with with federal healthcare.
This is VA, DoD, and HHS. And so that's a lot of
docs. And then if you add on probably 10 times that
amount for private care, it's very huge.
Let me jump ahead. I have a lot of
pictures here, but this really speaks about, you
know, the complexity of where we are today. And this
speaks to the levels of interoperability. So if
you're dealing with a device, that information, that
identity has to transcend all the way through the
EMR, and then if you're a doctor at Kaiser or at DoD
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and you want to have a C-32 travel over, if that
identity is not matched up, then you got the wrong
patient. And if you don't have -- how many people
here know what deterministic identity management is
versus probabilistic? And so that's the key point.
All I really want you to learn today is
that I'm not a goose hunter and that identity
management is the most important thing that I can
have everybody take away. If we don't get identity
management right and we don't use probabilistic
matching as the mechanism to do so, we are not going
to get any kind of interoperability between the
devices and NHIN. It just won't happen. So that's
how critical this is.
And so how many folks here are actually
working on devices? I've been to the University of
Pennsylvania groups and the high confidence groups,
and I know that Helen Gill is here. And we talked
about this a long time ago, and everybody wanted to
have test environments to actually test the
interoperability of the sharing between devices and
those test environments have been very slim to none.
If we could concentrate on probabilistic matching of
identities, we could make a huge difference. And
what we found in VA and we found with our NHIN
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project in San Diego is that there's really about
five identities that you need. You need your first
name, middle name, last name, Social Security number,
date of birth, and there's all of this twitterbating
about whether or not to use Social Security numbers.
In my mind it's relatively irrelevant. It's not a
matter of one identity. It's a matter of five or six
attributes about the individual.
And so we found that if you have five
attributes on the VA side and you have five
attributes on the DoD side but three of them are
wrong, they got the last name wrong, she got married
or changed her name or somebody mistyped or fat-
fingered a Social Security number, as long as you can
match up three of the five or three to three in a
probabilistic matching solution, then you've got the
right patient 99.99 percent of the time.
And so that's the missing piece in my mind,
is nobody has been effectively taking that on. And
so single sign-on, identity management, initiate with
a company. I think that was just picked up by
Microsoft, and there are other companies that do this
sort of work. I can't really mention those names,
but there's a lot of people that are working on this.
And one last point, and it's about the
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architecture. I said I wanted to be an architect.
There's really the business architecture, and then
there's the platform upon which all of this works.
And I know Dr. Friedman mentioned that we didn't
really want to talk about technology, we wanted to
talk about the business of medicine. And not so much
the business of medicine, but the active taking care
of patients.
All the electronic environment is, is a
reflection of the actual dialogue between patients
and providers. That's all it is. It's a mere image
of that. And as a surgeon I became disgruntled with
the fact that I had to operate and then I had to go
do all of this paperwork and dictate the op report
and do all of these orders and all of these things in
the electronic environment. What we need is a
mechanism so the devices that are part or agents like
these are part of what we do every day, and so part
of our workflow capturing the data along that path.
If we do that, then we will have a much more
efficient methodology for taking care of patients.
So with that, I'll open it up for any
questions. I didn't really mention much about our
project in North Chicago. We have multiple joint
facilities in Pensacola, Honolulu, in Anchorage and
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all over the country, like the map shows. It's
really foundational work because it's boots-on-the-
ground work. It's where you really don't ethereally
talk about these concepts of trying to create
interoperability and creating incentives. It's
really the real work. And so that's what we do, is
we're more a pragmatic entity. We actually develop
the true business requirements for the users, and we
translate that into technology solutions.
We have a hundred million dollars going
toward just a few things, single sign-on and identity
management, joint registration, order portability.
That's the other piece. And EMR is basically read,
write, and order. That's all an EMR really is. And
then you need to do the business intelligence of
knowing what your workload is and what your financial
reconciliation is. For the military it's operational
readiness. And then you have to be able to schedule
patients within the medical center.
And so those are the five key areas we're
concentrating on because nobody's ever done it
before. Everybody talked ethereally about how it
should be done, but nobody ever did it. And so the
NHIN project and the work that we're doing with joint
ventures is foundational for that work. So thank you
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very much. I appreciate it.
(Applause.)
DR. ROSENDALE: Oh, one more thing. Before
we go to break, I need everybody to stand up just
real quick. Just stretch a little bit and help me
out. Wave your hands and stretch like this, and let
me take a picture.
(Laughter.)
DR. ROSENDALE: Because what's really
important to me is to get a standing ovation at every
meeting.
(Laughter.)
UNIDENTIFIED SPEAKER: I've got a question
for you.
DR. ROSENDALE: Yes, sir.
UNIDENTIFIED SPEAKER: I'm real glad to
hear the folks --
DR. GOLDMAN: Please use the microphone.
UNIDENTIFIED SPEAKER: I'm sorry.
DR. GOLDMAN: We have a lot of folks on the
web, on our webcast, so we want to stay on the mikes.
UNIDENTIFIED SPEAKER: I'm real glad to
hear the folks on the western slope are doing good
work. I've got a question about trust for you, not
in the context of the upper strategic levels but at
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the point where we're talking about individual
devices that you would like to plug and play
together. For the most part, no device trusts the
other at this point. It's a classic business problem
in the commercial interoperability world. How is the
VA dealing with that issue, if you've made the
progress that you talked about in the slides? And I
think it's a fundamental problem.
DR. ROSENDALE: Right-O. I mean, the trust
issue is actually the number one issue. Like I said,
when you move in with your in-laws, you have to trust
them that they're going to let you, you know, use the
kitchen. And the reality is, is that that trusted
partnership is one of the greatest challenges.
We've had, at the medical center level,
take that down now to the device level. In VA what
we've done is we have a team in Hines in Chicago who
have actually worked with a number of companies in
trying to make sure that the messaging and the
security standards are adhered to so that when that
device plugs into our network, that those standards
are met. And particularly the security and the
messaging. And those are, you know, the technical
services that are necessary for this
interoperability. And so what we've done is we
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worked with those vendors and created an environment,
a testing environment to show that sort of plug-and-
play capability. But it was not easy. I can tell
you, it took many years for that to occur. There
were a lot of technical discussions, a lot of policy
discussions that had to occur, and then there were
the testing, the true technical testing to make sure
that the device didn't tank our system. And that has
happened too.
And so those are really tough things to
manage, and like I said, it's not ethereal; it's real
boots on the ground. Does it work? Does it connect?
Does it transfer the data properly? So we've had to,
through trial and error and a lot of hard elbow
grease, work through that. And we've had great
success.
MS. RANDALL: Good morning, Doctor. I'm
Debra Randall. Thank you for your comments. And
speaking of boots on the ground, the VA has one of
the most advanced home medical device systems for the
veterans. Is there any particular experiences you've
seen on the topic area you've been discussing,
interoperability and identification of the
individual, that came out of that work that you could
point out to us?
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DR. ROSENDALE: Right. A good friend and
colleague of mine and an Englishman who likes the
same kind of beer I do, Adams dark, is head of that
program. And so he has done a magnificent job in
working with vendors and developing the care
coordination and telehealth program within VA. And
I've watched his challenges and his successes along
that path, and it's the same situation, it's the
trusted partnership.
Now, the issue is you can create
environments that are relatively siloed, that sort of
pseudo-interoperate with your enterprise. And so by
doing so you can send faxes, you can send PDFs, you
can send that sort of information. The VA is so far
advanced in its integration and interoperability
level, I think Kim says that we're probably Level 7
out of Level 7.
And so we have done great work in showing
that the HL7 or the messaging that comes from those
devices integrates into our telehealth applications
in the medical center and then that information can
be ported to our electronic medical record. That
last part has been a bit of a challenge. Any time we
try to write back to our EMR, everybody gets twitter-
witty. Anytime you want to read from our EMR, it's
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relatively easy.
And so the right back component or the
transactional interoperability with messaging and
security with orders is the challenge. Nobody's done
that that well, but it's necessary. And I don't
understand it when most private sector communities
can take from their EMR and write a prescription at
CVS or Wal-Mart or any other pharmacy. They already
have order portability. Somehow they've broken that
trusted partnership challenge. Does that answer your
question? Yes, sir.
MR. ZAKIAN: Vaughan Zakian from Nuvon. I
have a question about identity and the portability of
the identity through departments because as it stands
today in most areas and EMRs, it's all location-
based. So how are you addressing the fact of
location-based systems and identification of
parameters that you're talking about?
DR. ROSENDALE: Yeah. So as I mentioned,
the attributes of an individual. One of the
attributes of an individual is where they're located.
I'm in FDA, which was a real pain to get into today,
let me tell you. But the attribute is location and
who you are, based on the issues I mentioned, and a
number of other factors.
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When you break up the architecture, you
decouple the architecture, and you've got not just a
tightly coupled architecture but an application on a
database, and you break this apart where you've got
the middle tier that's actually allowing the
flexibility of communication between the applications
and the database. Everybody has an iPhone, I bet.
Well, iPhones are simply a platform upon which
anybody can build an application for purpose. My
favorite is Shazam, so I can tell what music I'm
listening to. The idea is, is those applications
then talk through that middleware, the enterprise
system bus, and they reconcile the identity using
services like the one I mentioned.
It's a service-oriented architecture where
those services are provided, not tightly integrated
with the current technology in architecture, but
they're outside of it as an engine that actually you
subscribe to. And so a device is no different than
an EMR. And the guy over here at Philips is my
favorite guy because he's shaking head like this and
he hasn't shaken his head like this, so I must be on
to something. Right? Right? Right?
(Laughter.)
DR. ROSENDALE: Yes, sir.
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MR. ZAKIAN: However, you know, when you're
putting these parameters together to identify the
patient, right, in a system where you're talking a
middleware that's managing that --
DR. ROSENDALE: Yeah.
MR. ZAKIAN: -- then you must be issuing
another token that's an identifier of --
DR. ROSENDALE: Yeah.
MR. ZAKIAN: -- data for that.
DR. ROSENDALE: Yeah, sure. Yeah. I mean,
there's no reason why you can't share tokens of
sharing specific to your device. In fact, if you're
looking at device -- if you're looking at devices
that go south and you need to contact all of the
patients that had that device, that were managed by
that device, you need to be able to track that.
So that metadata is absolutely necessary
and there's no reason why -- I mean, it's the Google
opportunity. And I don't mean Google Google, I mean
Googleplex. You can add as much metadata to our
current data platforms as you need to to make sure
identities are square. I don't think anybody's doing
it that well, particularly at the device level.
MR. ZAKIAN: We're getting closer.
DR. ROSENDALE: Okay, that's the challenge,
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by the way.
DR. BAKER: I'm Maureen Baker. I'm
Clinical Director for Patient Safety at NHS
Connecting for Health in England. I do -- of correct
patient identification and particularly if you were
talking about -- between -- networks. Now, we have
something called the NHS number and across the NHS,
which is a unique identifier, and usually in our
system we struggled to implement that,
particularly -- however, what you were explaining
about probabilistic matching, if I were to think of a
scenario of twin boys born to a Muslim family, they
have the same gender, the same date of birth, the
same address, the same middle name, the same surname,
then I just don't see that that level would give us
the reliability that we would look for and -- is it
reliable enough in the first place? Is there a
possibility that a generation of unique identifier
either in the --
DR. ROSENDALE: A very good question. And
you actually just revealed that .0001 percent error
that I didn't talk to. I didn't say 100 percent.
Now, we are 95 percent with our master patient index
in VA. If we have probabilistic matching, we will be
99.99 percent. Your question is, Is there an
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opportunity for creating a unique identifier that's
all trusted? I argue that even the unique identifier
is not ideal because you can still fat-finger and
make a mistake with that single number. And so you
have to have solutions --
UNIDENTIFIED SPEAKER: -- then the
probability of entering an invalid number would be --
DR. ROSENDALE: So as Chuck Friedman said,
this is not all a technology discussion. This is a
business process discussion. The business process is
such that you can actually build the technology so
that when you get an error, when it does -- when none
of them match and you think you've got the right
patient, the way we manage that is we manage that so
that there's a list of those that are fallouts.
There's a fallout. Then you have to do manual
investigation to make sure that you're finding that
person, which could include the very identifier
you're talking about.
I mean, all that identifier is in my mind
is a metadata component of what you've accumulated as
a list of attributes about the individual. And so I
think we're smart enough in science and probabilistic
and statistical matching that we can create the
models that fit the business process, not just hope
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and pray that the technology does all the work for
us. I don't know if I answered that. But I'm a
surgeon and I'm very practical. If it doesn't work,
I just find a bigger knife.
(Laughter.)
DR. ROSENDALE: Yes, sir, in the back.
DR. BLOCK: Frank Block. I'm an
anesthesiologist at VCU.
DR. ROSENDALE: There we go.
DR. BLOCK: I'm losing my voice here.
DR. ROSENDALE: I've got your Wall Street
Journal here if you need it.
DR. BLOCK: Oh, thank you. At our Society
of Technology in Anesthesia meeting a couple of weeks
ago, Don Dettler (ph.) spoke to this ID, whereas as a
physician, I have a national practitioner ID.
There's actually no way that a patient can obtain a
national medical record ID even if the patient wants
one.
If our dream is to have a chart that can be
used anywhere in the country, you go to the ER, you
join the service, you go to your private clinic or
whatever, the dream would be that there would be some
sort of national medical record. If it doesn't have
a number, how will we ever get there?
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DR. ROSENDALE: So that's a tough question.
The discussion we've had so far is about the
probabilistic matching. Probabilistic matching means
you add science and statistical probable capabilities
to your electronic environment. And so it's very
similar to the lady from England, is everybody wants
to hang their hat on a single ID because they think
that's the panacea, and I don't know that that's the
case. I know that Don Lindberg, when I went into the
National Library of Medicine, he had me hold my hand
up to a plate, and that was the handprint. That was
yet another attribute about me. And then there was a
fingerprint, and then there's a retinal scan.
There's all of these bio -- what do you call that
again -- biometrics that allow you to have the
attributes. So I'm not convinced that a single
identifier is going to be the panacea. I think we
need to be more -- we need to be smarter than that
and use science and probabilistic matching in order
to do so. Would you help me here? Because that's
the second question on this.
DR. ZALESKI: I stopped nodding. One of
the things --
(Laughter.)
DR. ZALESKI: One of the things from the
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perspective of science -- I won't belabor this -- but
that we look at it as an example is bringing in
a priori data. So this is one reason why medical
information for medical devices is so important,
having a full and complete record. With oncology
patients, many of the oncology patients that we
study, we bring in a priori images in a probabilistic
fashion on calibration and save the patient of those
images to ensure -- not just because we're looking at
the images to look for lesion changes, but we're
looking -- we're assessing the likelihood that this
really is the right patient. This is especially
important when we're talking about follow-up CTs and
MRIs and for radiological treatment of patients. So
that's just one example.
DR. ROSENDALE: Yeah. And that's perfect.
In other words, the attribute of an individual -- I
mentioned that the digital environment is purely a
manifestation of who we are and what care we
received. That's all it is, whether it's an X-ray,
lab studies, or a genetic study. And so first name,
middle name and last name is pretty basic. That's
just your name.
But what you're talking about is
reconciling the information that already exists in
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the electronic environment and say this is actually
the same patient. This is the same chest X-ray he
had in, you know, hospital A versus hospital B. And
so taking it to that level is even more sophisticated
than what I've described. But instead of a single
ID -- and I think we need to be following that, that
path. And so thank you for that support on that
conversation. I've got one minute. Last question.
UNIDENTIFIED SPEAKER: I mentioned earlier
that I thought the best thing to do was ask the
anesthetist to ask the patient their name. While I
agree with what Frank said is the dream, it is only
the dream when you're trying to talk about
identification, and it ceases to be the dream when
you have to add the layer of security on top of it.
You have one ID, one single attribute that's a
deterministic attribute, that's very easy to spoof,
to steal, to do all kinds of things with. When you
go to probabilistic matching, then you make that
security --
DR. ROSENDALE: Yes.
UNIDENTIFIED SPEAKER: -- breach much more
difficult.
DR. ROSENDALE: Absolutely. And I like
your boots, by the way.
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(Laughter.)
UNIDENTIFIED SPEAKER: Yeah, well, I'm not
from the western slope. I'm from Pueblo.
DR. ROSENDALE: Thank you very much.
DR. GOLDMAN: Thank you very much.
(Applause.)
MR. MURRAY: It's break time, right?
DR. GOLDMAN: Right, it's break time, and
the break is right outside, and please return
promptly. Our next session starts at 11:20.
(Off the record.)
(On the record.)
DR. GOLDMAN: Welcome back. So we're going
to need some help from a number of people in the
audience. If you notice that your neighbor is dozing
off, it's because we ran out of coffee, and a lot of
people were really pained by the absence of coffee.
Thank you. So I can't help that, but what I could do
is encourage everyone who's still awake to either use
your right or left elbow, as needed, to stop the
person next to you from snoring.
UNIDENTIFIED SPEAKER: We could start a
caffeine drip.
DR. GOLDMAN: We could start a caffeine
drip. Yeah, that'll be fine. No problem there. Two
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hundred milligrams will get rid of any headache. So
that's it.
And the other announcement that I have is
that you've been signing up outside on the papers for
the first breakout session, but there are two. So
you'll have to go back when those things are ready
for sign-up to sign up. I think it'll start at
lunchtime, where you can sign up for the second
session. So keep in mind that there's another thing
to sign up for. And that's it.
DR. WEININGER: Do you want me to introduce
you?
DR. GOLDMAN: Sandy's going to introduce
me. This is kind of strange. I already know who I
am. So why don't I just get started. And my name is
Julian Goldman. I'm an anesthesiologist at
Massachusetts General Hospital, and I've been working
on interoperability in a program based at CIMIT, the
Center for Integration of Medicine and Innovative
Technology, since 2004. And many of you in the room
have somehow been involved or participated in some of
those activities. My other hat is that I'm the
Medical Director of Biomedical Engineering for
Partners HealthCare.
Now, what I'm going to focus on in my
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presentation are some of the clinical perspectives,
and I think that the prior speakers did a very good
job of hitting some key clinical points. And so
there may be a little bit of overlap and an echo. If
I can get that timing just right, maybe I can get it
to continue and I can stop speaking and it'll just
continue. So maybe I should turn the volume down on
the speaker. All right. So let's get started.
This is going to be my talk. If the coffee
arrives and you have to run out, then you won't miss
anything. So the first point is that innovation
outside of healthcare has changed our expectations
for healthcare, and that's what's different this year
versus 5 years ago or 10 years ago or 15 years ago or
20 years ago. And there are people in this room who
have been looking at addressing interoperability
barriers for two decades or longer.
The second point is that medical devices
are key data sources for electronic medical record
systems. And I'll make that point as I go through
that.
Number three is that safe standalone
devices are not adequate to maintain patient safety.
So in the medical device world and the FDA regulatory
world, the focus has been on the single standalone
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medical device and the user interaction with that
device and the device interaction with the patient.
But that is not adequate to ensure the
safety of patients, and I hope to make that case for
you. And the essence there is that system solutions
are what are required to create error resistance. We
can't make things idiot-proof, but we certainly could
make them error resistant.
And then finally, there's actually
tremendous demand for success and focus on what we're
doing here over the next two and a half days because
we are seeing now that clinicians, clinical
organizations, societies, the public really wants us
to have it, and so the time to do something is now.
Well, it's getting close to lunchtime, and
so it seems that I'll get your stomachs grumbling.
How many of you have ordered Domino's pizza online?
All right, about 15 people will admit it.
(Laughter.)
DR. GOLDMAN: And the rest of you just
won't admit it. So you get online and you build your
pizza, and then you have this pizza tracker and the
pizza tracker starts off with you've got it made,
you've got it heat-waved, you've got it on the way,
you've got it. And there are some intermediate
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steps. And it even tells you the name of the
delivery person who will bring it to your door, and
you know, it tells them, if you like the job they
did, to let them know it with a hug or perhaps a tip.
So that is what we have come to expect in
other places. We have real-time status. We have all
sorts of information that is conveyed through a
website, and we have the data seamlessly available
when we order a pizza.
And when you send a patient down to
radiology for a procedure or a person comes through
the clinic and has to make three other stops for a
blood draw, an X-ray, and something else, you don't
even know if they're still in the hospital, let alone
if anything was done correctly, and therefore the
impact that that might have further on. So maybe
Domino's could start doing it for us in the hospital.
I don't know the answer, and I'm not proposing a
solution.
The iPhone was mentioned before, and I
think the iPhone is a very good example of a
commercially successful platform. It isn't an open
platform, but enough of it is open until you get the
job done. And this is a pretty interesting news
story that came out in September of '09, so a new
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news story. iPhone gets Zipcar drivers on their way.
Now for those of you who, you know, use
Zipcars or those of you who don't, it's like a
library. It's like a rental car that's available, a
shared rental car, in your neighborhood. Usually you
get online and you make a reservation, and then you
have access to the car.
But when they did this, they developed an
application, and you can see towards the bottom of
the screen, it says, "Zipcars app is the first to
control the operation of a car, which is why David
Cole, Chairman of the Ann Arbor, Michigan based
Center for Auto Research, calls it a breakthrough."
And he says, "Once you have this kind of electronic
ability in a cell phone, there's no end to the type
of technology you could bring to cars." Well, it
sort of controls a car. It really just unlocks a
car. But, you know, I guess if you're an insurer,
that's what you care about the most. I don't know.
But it is really significant, and it shows
the power of a platform because when they built the
iPhone, they didn't know -- I'm sure they didn't know
that it would be used to unlock Zipcars. And that is
the power of the ability to standardize a platform
that you then open for innovation. So
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standardization doesn't preclude innovation. It
actually facilitates it in ways that are really quite
powerful, as we're seeing today.
Another example of things in our
environment that work quite well is the warning
system that a pilot has, a smart alarm. If the pilot
tries to land a plane and the landing gear is not
deployed, there's an alarm in the cockpit that is so
loud it could probably wake the dead.
Now, the alarm is a smart alarm. It's a
smart alarm in the cockpit. Why is it smart? Well,
you want to know that the landing gear is not down,
but you don't want to know that when the plane is at
altitude at 30,000 feet. You only want to know that
when it's coming in for a landing. So the plane has
to know it's coming in for a landing for the alarm to
be activated. So the plane does that because it
knows its airspeed, its altitude and attitude, wing
flap position. It depends on the plane. There are
different ways of doing it. But this is an FAA
requirement for all planes. And so that type of
contextual awareness is available to the system
because of the sensors and the integration of the
data, and it does require data from a number of
sensors to provide that augmented vigilance.
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Now, what if a pilot wants to land with the
landing gear up? What if they want to do that? Why
would they want to do that? Well, I call it the
Hudson River override. You don't want your landing
gear down if you're landing in the Hudson River.
So not only can you not deploy the gear,
but you can suppress the alarm because,
appropriately, it was determined that that alarm
would be a distraction and therefore it would be
problematic. So the point is not to take away
control from the pilot. The point is to augment the
pilot's vigilance and still have appropriate control.
And that's really what we need in many areas of
healthcare.
So the first conclusion, going back to the
first slide, other industries have elegant and
effective system solutions. Wouldn't these
capabilities be useful for patient care? Well, let's
look at some challenges and examples.
How about capturing complete data from the
electronic medical record? Now, this is a photo --
these are photos from the operating room, and on the
left there's a patient who was hit by a car and we
were saving the person's life one afternoon. You
have a lot of people in the room taking care of the
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patient. You can see a pile of blood bags that are
being used to be transfuse blood on the bottom left,
a pile of drugs that were open on the right for
resuscitation drugs, and in the upper right there is
an anesthesiologist who's manually entering data into
the electronic medical record system.
So the physiological data goes in
automatically because the devices are connected to
that EMR, but none of the other data goes in, drug
administration, activities in the room. So there's a
lot of manual data entry required. And, in fact,
that is one of the shortcomings, the limitations of
this EMR.
And I would propose that the anesthesia EMR
is the most comprehensive and sophisticated one that
exists in clinical care because it's been around for
a long time, and it has certain features that allow
real-time entry of data under most conditions. But
even that can't keep up with the amount of data
required to have accurate tracking of this. So this
record will not be -- necessarily be complete or
accurate. It'll be a lot better than we had in the
days of paper, but we still can't connect.
Now how about this? On the right are two
photos of a physiological monitor in the operating
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room. And for those of you who are not clinicians,
it just looks like a dizzy oscilloscope, but for
those of you who are used to seeing waveforms, you
can see these are physiological waveforms from the
vascular system. But even very experienced
clinicians -- and probably, I would guess, Frank
Block is probably at the top of that game in this
room -- would have difficulty interpreting exactly
what happened on the screen.
So, Frank, do you have an idea of what's
been going on this room? You don't have to say
anything. No clue. And Frank I know well. He's
brilliant, and he's a very experienced
anesthesiologist. And if all this data is in the
record, it's still hard to tell that in the room you
have a team of people performing CPR on this patient.
The arrow is pointing to the head of the one that's
performing chest compressions. This patient was
having some trouble during a complicated procedure,
and this is a resuscitation.
So think about the challenge ahead of us.
Even if we populate electronic medical records, even
if we send all this data in, if we don't have new and
better ways of gleaning better contextual information
from the environment, we'll just have records full of
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this data that even experts really won't be able to
interpret or use to then improve the quality of care.
And this is a problem that still does not
have a solution, and these are technical solutions
that are required, research that's required, the kind
of things that should be supported and funded by some
of our federal agencies supporting this kind of
research, such as NSF and NIH.
Here's another example. The bottom panel
is a snapshot of our electronic medical record in the
operating room, and the upper left and right screens
are pictures of the physiological monitor at two
times -- just a few minutes apart. If you look at
the top screen, you can see that the heart rate, as
measured by the electrocardiogram, is roughly the
same in both, about 60 to 69. In the bottom of the
monitor, you can see that the pulse rate on the left
is 79 and the pulse rate on the right is 170. So
there's a big discrepancy on the one on the right,
and the reason for this discrepancy is that the heart
rate or pulse rate can be measured different ways.
The electrocardiogram, the top one is measuring it
through electrical activity of the heart. The bottom
waveform is measuring it through the pulsations in
the fingertip that are being measured by the pulse
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oximeter. And because that waveform that you see on
the third waveform from the top is kind of a funny
looking waveform, it doesn't have nice smooth
contours, the instrument is incorrectly calculating
the pulse rate, but it's doing it intermittently.
Now, if you look at the medical record on
the bottom, the permanent record, and you follow the
green dots, you could see that the heart rate jumps.
From down here it's correct, it's 79, then it jumps
up here to 170, and it drops down again.
So the permanent record has documented
incorrectly these alterations in pulse rate, which
could have been correct and could be the result of a
number of different problems, typically cardiac
problems. But in this case they're incorrect.
And we would never know the reason, the
etiology for this, if we didn't have a snapshot of
the waveform, and we wouldn't have had that if I just
hadn't happened to be the operating room with a
camera because our systems don't record that data.
So our systems are incapable of letting us go back
today and actually see the source of the problem and
diagnose or figure out improvements in treatment or
provide information back to the medical device
manufacturer so that they can improve their
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algorithms. And we can't do that today, either.
Now, here's another interesting way to use
the system. So this is an interesting new algorithm
called protocol watch, which has tremendous
capability to add real-time decision support in
physiological monitors. And here's this poor patient
who was kept up all night long. This was in
November. I got his permission to use the photo.
(Laughter.)
DR. GOLDMAN: Who was kept up all night
long by an alarm on the screen because this alarm is
for a protocol watch for severe sepsis screening.
Now, I happen to know that this patient was not
admitted with anything related to severe sepsis, but
with an arrhythmia, and therefore this was an
irrelevant protocol for him.
Furthermore, it alarmed regularly all night
long, and you can see over here it says action
required. Action required. Boy, you know, that's
the monitor that cried wolf, right? There's no
action required. And why was action required?
Because if you look at the boxes, it was missing
data. It did not have data from the lab on white
blood cell count, and it did not have glucose
information, and it didn't have temperature, all
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things that could've been populated automatically if
it was easier to get this data into the system, and
then this poor patient wouldn't have left the
hospital in worse shape than he went in.
So new problems are emerging, and with
broad use of electronic medical record systems, we're
starting to see latent problems with different data
on different systems. So it's not only connectivity
and getting the data, it's with getting some of the
wrong data.
Here's another photo. Let me take you
through this. In the bottom center there's a picture
of a machine that measures coagulation, an ACT
machine. It's a point-of-care device -- excuse me --
and it has an RS-232 output, as you can see on the
bottom left, and then it has -- uses an adapter to
send that data through the clinical information
system. Then it goes downstairs and hops across a
few network cables and goes to places I don't really
know, and then it comes back upstairs and shows up at
the point-of-care electronic medical record, and
there it says ACT and the time is 11:06.
So here's the procedure. You give the
patient a dose of heparin, and then in 30 minutes,
depending upon your protocol, you measure the ACT and
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you see what the number is, and based on that you
decide how to re-dose the drug. I was really puzzled
as to why it seemed that I was waiting 30 minutes by
my wristwatch and by another clock, but the data was
about 25 minutes.
And it took me awhile to figure out how to
get into the right screen on the instrument to find
out that its time was set -- in this example it was
10:54 and my wristwatch was 11:02. So there was an
offset because these devices don't use network time.
They're more like the VCR that just blinks, you know,
and flashes 12:00. And that's the case with medical
devices. They don't consume the common time protocol
that's used for all our other systems.
So this is a very significant source of
error, and one that really had me puzzled for a while
and one I can't do anything about. I can't go and
change the time on these instruments. I'm not
allowed to touch them. I'm not certified.
(Laughter.)
DR. GOLDMAN: It's probably a good thing.
So conclusion number two is that medical devices are
critical data sources as data consumers because we
should've been pushing the time to that device, for
example, and probably pushing the patient identity to
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that device as well. And, therefore, to address the
things I just showed you in terms of the richness of
the data and the context, effective connectivity is
essential to do that, and we're not there yet,
either.
What I'd like to do now is run through some
clinical examples of where interoperability or system
integration could've made a difference to patient
outcome. This horrendous photo shows patients who
were burned during surgery, and because it's fairly
easy to ignite things in a patient environment where
there's enriched oxygen, the patient on the left
upper part died, the one on the right survived.
And, you know, the laser worked just like
it was intended. All the devices in the environment
worked like they were supposed to. These are, of
course, FDA-regulated devices. There were no
problems with the device. But the patient's still
dead. That's the problem.
Now, the most severe injuries are injuries
that are -- typically are blast injuries of the lung
that occur when a breathing tube, an intratracheal
tube is ignited. That's what it looks like if you
hit an endotracheal tube with a laser when you have
oxygen flowing through it. It turns into a
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blowtorch. So what we do is we try to reduce the
oxygen concentration in the breathing system before
the surgeon activates the laser. And so the team, as
a team, has to remember to check with each other and
say -- you know, the surgeon has to say, I want to
start the laser. The anesthesiologist has to say,
Okay, I reduced the oxygen. You have to wait several
minutes for the concentration to fall, and that's a
variable amount of time based upon the system and so
forth.
And remember the airplane. If the pilot
tries to land, they get a klaxon that tells them
there's a problem. But here we're depending on
teamwork for something that can cause as devastating
injury as this.
So why we can't measure the concentration
of oxygen and have a safety interlock that either
prevents the activation of the laser or just warns
the surgeon not to activate the laser until the
concentration drops? Well, the fact is this was
proposed and published in 1999, and it's still not
commercially available because of the difficulty of
the interfaces, because we have no way to
interconnect these systems at the point of care. So
a lot of ideas like this have been proposed over the
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last few decades, and in fact, there's no shortage of
good ideas; there's just no implementation of those
ideas.
Here's a scenario of failure to continue to
ventilate a patient or breathe for the patient.
Normally when a patient goes on cardiopulmonary
bypass, we start off with them on the anesthesia
breathing machine, the ventilator on the right, and
then when we go on bypass, the bypass machine
circulates blood and oxygenates it so you no longer
need the ventilator. And normally we switch back and
forth. When you finish the bypass run, you go back
on the ventilator, except if you forget to turn the
ventilator back on after bypass. And you may think
that's a hard thing to forget, but there's a lot of
stuff going on in the operating room at a time like
that.
And you can look back 13 years in the
literature, and there's older literature that shows
that people forget to turn the ventilator back on
after bypass and patients are either injured or they
have to go -- or they are temporarily injured,
resulting in a longer -- they have to go back on
bypass for the longer bypass run. There's all sorts
of bad things that happen. And it continues to
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happen.
And I've asked thousands of
anesthesiologists around the world, and I'm still
looking for the one who could tell me they never
forgot to turn the ventilator back on. I haven't met
that person yet. They've caught it within a few
minutes, typically, but others haven't and they've
told me about the patients that have died.
So again, the devices worked as intended.
The bypass machine worked correctly, the ventilator
worked correctly, everything worked correctly, except
we still we have dead patients. So why can't we have
a smart alarm that says there's a patient attached to
the system and both the ventilator is off and the
bypass machine is not circulating? It doesn't seem
like rocket science. It's just a basic connectivity
barrier that's prevented people from building these
very reasonable solutions.
Here's another example. This is a patient
who had gallbladder surgery, and during gallbladder
surgery, at times it's necessary to perform an X-ray
during surgery to image the system that drains bile
to see if there's a stone in place, and that
procedure is called the intraoperative cholangiogram.
And what happens is that the surgeon injects that
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contrast agent directly into the structure and then
they roll in an X-ray machine and take an image, and
during that time we turn off the ventilator for about
30 or 40 seconds, which is fine. You can hold your
breath for 30 or 40 seconds. There's no problem.
But, again, if you forget to turn the
ventilator back on, it's quite a serious problem.
These are very rarely reported, but these occur. And
here's a report from the Anesthesia Patient Safety
Foundation newsletter in 2005, and a 32-year-old
woman died because of this very problem. And I've
heard about this problem many times, but it just
hasn't been popularized. So again, all the devices
worked correctly, the X-ray worked correctly, the
procedure worked correctly, but the patient died.
That's a problem.
Now, it's not just those procedures. More
and more so, with increasing frequency, there are now
interventional radiology procedures, other procedures
in remote locations in the hospital, all of which
require cessation or temporarily a ventilation --
stopping a ventilator because of the image quality.
So here's a picture I took in
interventional radiology, and there's an anesthetist
on the right and she's thinking, I better get out of
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here because they're about to start the high-energy
X-ray and they tell us, Get out of here. Turn off
the ventilator and leave the room.
So the next pictures shows there is no
person in there, and we have to remember to go in and
turn the ventilator on, or we go in and we have to
remember to turn it on. This could happen a half a
dozen times in the course of two hours or so. So
this is not an infrequent esoteric problem. This is
becoming more commonplace and even more so as we
start to do robotic surgery and automatic
manipulation of organs with imaging.
Now, what's the alternative? Well, you can
synchronize the X-ray with the ventilator. You can,
say, just like you do with a flash in a camera, you
know, just take the image automatically at the right
phase of respiration. Or you could, say,
automatically stop the ventilator for 10 seconds and
while it's paused take the X-ray and have that
automatic. It doesn't matter if there are subtleties
of how that might be done.
There's research to show different ways of
doing this. The point is that there could and should
be a way to do it. Perhaps different ways, if you
want to take a breath at the peak of inspiration or
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after exhalation. This was published, this was
performed, this was studied in the intensive care
unit with five radiologists comparing X-rays with
different ventilating normally or synchronizing with
an X-ray. It was performed 11 years ago. The data
is really quite good, and it shows the better quality
X-rays. You don't have to retake the X-ray. Again,
we can't do it today. And this is some work we did
in our lab, at our CIMIT lab in Cambridge, where we
implemented some of these examples.
So I want to kind of take you down to
thinking for a moment of what is required for safe
synchronization of the ventilator and X-ray. Well,
it's not safe to just control a ventilator through
another device, if you want to call it control.
Every manufacturer of a ventilator will say quite
clearly, There's no way in the world I'm going to let
some other manufacturer turn my ventilator off, and I
think that's quite reasonable. So that's not going
to happen.
But what could happen is, if the ventilator
could provide a real-time signal to trigger the X-ray
so the X-ray is triggered at the right phase of
ventilation, that's one possible way to do it. And
that's not done today either because we don't have
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the reliable timing on the signals because they're
not intended for this purpose yet.
Or, alternatively, number three, the
ventilator could have a pause feature and an
autonomous restart, and then the X-ray could activate
that feature. So the X-ray machine sends a command
to the ventilator, and it says I want you to pause,
and the ventilator says okay, I'll accept that
command, or it may say no, because the physician told
me I can't, or it may say okay, I'll accept that
command. It pauses for 10 seconds, and then no
matter what, it restarts on its own accord. And that
is a way to do that, and that's some work that we've
done with collaborators both at the University of
Pennsylvania and also at the University of Illinois,
who've looked at safety critical systems and how to
network them in that way.
So the new ventilator standards that are in
draft form are incorporating some of these notions
and requirements in an early form, and if anyone has
questions about that, I'll direct you to Dave Osborn,
who's sitting over there.
So here's another interesting thing. It's
called image-registered gastroscopic ultrasound,
IRGUS. I didn't come up with that acronym. So this
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is a new technique by an investigator at CIMIT, Kirby
Vosburgh, who just sent me these slides, and it shows
that on the left you have ultrasound, on the right
you have CT scan data, on the bottom you have a 3-D
model and then you have -- up on the right you can
see a gastroscope that has special sensors so that
the system knows exactly where that scope is placed
in the esophagus and further down. And therefore you
could have a 3-D model with the probe in place to
show the operator, especially if they're about to do
something that could damage tissue or to get a
precise biopsy.
This is the future. This is a melding of
all the information and the device information to do
things we never could do before. So the burden on
connectivity and what could be achieved, you know,
this is the future. The other examples are
relatively simple, but they're still killing people.
So conclusion number three is that many
longstanding problems cannot be fixed and patients
are being injured. And improvements in patient
safety, clinical care, and healthcare efficiency
require heterogeneous system solutions. And
scalable, versatile integration requires medical
device interoperability. Interfaces must be updated
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to support the required functionality.
So in the X-ray example, if the interface
doesn't allow you to send a command to the ventilator
to pause it, well, then we haven't succeeded. And
the current standards typically don't support that
either. So the standards have to start to include
that capability as well.
I want to mention briefly that clinical
requirements are really the essential driver for most
of these things. They're really necessary to assure
that the solutions are going to be useful. And we
need carefully documented scenarios. In our program,
in our medical device interoperability program, we've
been eliciting requirements for a few years. They're
not enough, but they're a starting point. And so
we've been doing that at various meetings with
surgeons, anesthesiologists, clinical engineers, and
so forth, to help to drive this work.
This is an example of how the data, some of
it's organized, and we've done this with the help of
Sandy Weininger here, who's here at the FDA, and a
number of other collaborators, and Tracy Rausch, who
might in the room, and Rick Schrenker, who's here.
So it's really taken -- I don't want to use the term,
but it's taken the village to do this kind of work
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because it takes the -- really this broad range of
expertise and perspectives from the clinical
engineering, biomedical engineering, systems
engineering, clinical, and so forth.
It's kind of hard to read that overlap on
top. But there's a standard that just published,
called the standard for the integrated clinical
environment. It's ASTM Standard 2761. And in the
standard in Annex B, there are seven clinical
scenarios right in the standard, and I think this
might be -- you know, it's one of the few standards
that include scenarios as a justification for the
requirements.
And some of the things I just presented to
you are some of the requirements that are in that
standard. And, of course, you know, we as a
community have been collecting this to put it into
the standard to accomplish something that everyone
could then share and read.
This is a diagram from the standard, and
the other thing that I'm really pleased about is the
standard shows -- in the diagram it shows a
clinician, it shows a patient, and a whole bunch of
other stuff that help you get the job done. And how
that's all connected and how it's going to work is
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the subject of a fair amount of work, including the
work that's here in front of you today, so that you
can have safe interoperability of the components
required. And some of the notions that are included
here is the idea of a data logger to collect all the
information that's transferred within a system so
that one could go back and analyze -- if there are
problems with the system, one can determine what that
was, and the idea that there's an external interface
to the hospital information system because this data
might be a relatively high bandwidth, fine
granularity and so forth, and you need some kind of,
you know, low bandwidth connection. And so to do
that, that's really essential. And there are several
other notions that are contained in here that there
really isn't time to dig into it in any detail.
The other thing I wanted to point out is,
as I said in the beginning, there's quite a bit of
interest and support now, and that's why now is
different than five years ago. This is a statement
by the American Medical Association that was
formalized at their assembly in the springtime. This
resolution states, as you can see, that the American
Medical Association supports interoperability of
medical devices to improve patient safety and patient
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care. And they're the seventh society to do that.
The Massachusetts Medical Society is one of them as
well. And it just shows that this is no longer
something that's kind of out there and esoteric, but
really needed.
And the other thing that I'd like to bring
to your attention is an agreement between Partners
HealthCare and Johns Hopkins Medicine and Kaiser
Permanente from October of 2008, and this is called
MD FIRE, for medical device free interoperability
requirements for the enterprise. If you don't like
that acronym, talk to Mike Robkin, who came up with
it. This is work that was performed with
stakeholders from the organizations. I'd like to
emphasize that the stakeholders include the legal
departments from these three institutions, clinical
representation, IS, biomedical engineering, and
materials management, and this document describes --
it's a position statement and sample of
interoperability and RFP contract language. It's
freely on the web at mdpnp.org.
This is an example from the first page of
the document. That's a nationwide call to action for
interoperability of medical devices and systems. So
it comes up every now and then that, gee, is there a
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business case? Will people buy it? Do people care?
And the answer is, I would think so at this point.
So conclusion number four is that
clinicians, biomedical engineers, health delivery
organizations, medical societies -- and you could add
a few other things in there if you wish -- want
market access to interoperable devices to enable
innovation and reduce the cost and complexity of
device-to-EMR integration.
And I think this is pretty cool. If you
look at this, it says it all began with a new of way
of thinking. They're standing on their bicycles
while looking over the fence at the plane, and it
does -- it is a new way of thinking. It's a new way
of thinking about healthcare. It's a way of thinking
that we could have a pervasively integrated
environment that then begins to serve as a platform
for decision support and safer systems.
Interoperability is a means to an end. It isn't an
end in and of itself, unless your business is to sell
interoperable things, which is fine. But in
healthcare it's a means to an end.
So with that I'll wrap up, and I may have
time for a question or two. I'm not good at keeping
my own time, so I actually don't know. So let me
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take a couple of questions, and then we'll move on.
But one at a time, please.
(Laughter.)
DR. GOLDMAN: You really miss that coffee,
don't you?
MR. MURRAY: No, I think it was a very
nicely given presentation.
DR. GOLDMAN: All right. You got a
question?
MR. HOYME: Yes. Well, I'm Ken Hoyme with
Boston Scientific. Before that I spent 18 years in
the aviation business building safety critical
systems for commercial aircraft, so I always find
fascination with analogies with the aviation world.
One of the things that's going to be
different about the medical device world and
interoperability is there isn't the equivalent of a
system integrator. There isn't the Boeing that is
putting it all together. So the example of the
auto-landing system and the integration, a regulatory
body imposes on an organization like Boeing the rule
that says you're going to have demonstrate that the
system works together to do this particular function
or you don't get to start selling the airplane and
make your $10 billion investment back.
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Defining interoperability amongst sets of
different device vendors allows the pieces to be
there, but today I think we're more equivalent of
you've been to the Oshkosh flying air show where the
individual builder goes to the vendors and they pick
their navigation system and their radio and they
build their experimental airplane and bolt it
together. And I think of all the different IT
systems we have in the different hospitals, different
physicians putting their EMRs together, we're a
little more in that world than the integrator.
I'd be interested in your thoughts about
how do we fill in that intermediate layer because if
we do it with all the standards, it tends to be
really slow. It takes years to develop the standards
amongst them.
DR. GOLDMAN: Okay. Well, I think that's a
great point, and I think I would look at it as two
ends of the spectrum. So one of the end of the
spectrum are avionics with all the certification, and
one cannot just go shopping and replace what they
want. And if you look at the other end of the
spectrum, you have something like USB memory sticks
that you can buy in Target and plug into any
computer. And five years ago they would frequently
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give you the blue screen of death, and today they
work really well. But they could crash and there
could be a problem.
And so perhaps we don't just say that
medical device interoperability and system
integration is one point on that continuum. Maybe we
say that it's a range on that continuum. And for
some things it's okay to accept the possibility of a
system crash or a failure when one is collecting
intermittent low-acuity information, perhaps from in
a home or a telehealth setting, and one might say
that somewhere else along that continuum, you know
how the system -- where you need greater assurance of
performance because you have robotic control, robotic
integration of X-ray and laser and other things like
that.
And so in the ICE standard, the ICE
standard looks at the higher acuity environment and
then talks about some of the assurances that are
needed before a device will be allowed to
interoperate with the others. So one has to be sure
that the devices are appropriately certified and so
forth and so on. And those are much tighter
requirements than one might have at a lower end. So
I don't think we're just talking about one thing in
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one application, but I think it's a continuum that
could map onto that other continuum.
And then, therefore, it gets to the point
discussed and will be discussed, I think, further,
that if we require that comprehensive pair-wise
testing for all of our interfaces, it does put us at
a point where we're so far away from the USB memory
stick that we just can't build anything.
So we need to somehow come to a balance
where there are appropriate tools and methods that
are available for those system integrators to
integrate in clinical environments. And certainly
our, you know, biomedical engineering department is
prepared to do that and others are as well, and there
are many companies who would love to stand up and do
that, but we probably need to share tools and
resources that the community can build to make that
possible. So those aren't one -- I think, like the
open source movement, you know, we want everyone to
beat those things up and see if they're really safe
and viable. But that's just my answer.
MR. McGRANE: Tom McGrane with Kaiser
Permanente. So you build a very compelling case, and
there's a lot of obviousness to the need for this and
there's a lot of industries that do this. So the
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problem isn't necessarily technology. So what really
is keeping us from getting this reality that I know
you're very passionate about? And what would you
expect timeframe-wise? When do you expect that we
actually start seeing the breakthrough and the
realization mainstream for all of this new stuff?
DR. GOLDMAN: Well, there isn't really much
of a rush. We have until Wednesday. So, you know,
take your time.
(Laughter.)
DR. GOLDMAN: So I think that on the one
hand it seems like this isn't the hard technology or
science question, and that's because for some of
these applications it isn't. I mean, it isn't a
challenge at all. It has to do more with who is
willing to take the risk because you have to build
the community of capabilities and products, and it's
very hard to do that in an organized, synchronized
way.
And I think that's what Continua has done
well, as an example, by getting buy-in and then
having now over 230 companies and healthcare delivery
organizations who all said we'll buy into this at the
same time and made a change. But there are some hard
science and technology questions that haven't been
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answered. We don't know how to certify these systems
at the point of care. We don't know how to integrate
these and swap devices if something fails in a
clinical environment. We don't know how to do that
yet.
And so I think that there's a range of
these harder questions that have to be addressed in a
focused way, and then there's a range of things we
can do now, and there's really no reason to delay and
then -- you know, so there are a number of issues
here. And I think we identified these as streams of
issues within our program in 2004, as issues around
regulatory questions, technology questions, absence
of complete standards, there has to be a business
case, it has to be clinically driven.
So we have to look at all of those streams.
And I think there's been progress in every one of
them, but there are some big gaps, and I think we're
all here together to try to address some of the more
challenging gaps. I think this will be the last
question.
MS. HAILPERIN: Hi, I'm Marilyn Hailperin
from Santa Rosa Consulting, and I think one of the
pieces that's missing here is where healthcare IT
consultancy would work with hospitals. But most of
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our clients are not considered partners, but they are
community based, and they are making these decisions
on the basis of a constituency that's not here, which
is their CHR vendor or their premier device
manufacturer. So they're going with a Philips
solution because I feel safe doing that. Or I'm
going with a solution that ethics says had worked in
some of their places before.
And the innovation may be happening in the
more academic and broader institutions of which
you've spoken. But I think, down at the grassroots
level, there's a lot of people who recognize the
benefits in patient care and are making decisions
that will prevent them from making better decisions
later because they have invested their financial
resources in an infrastructure that they're stuck
with.
DR. GOLDMAN: Yeah, indeed a challenge. I
liken that to that fact that today you can walk into
the checkout aisle at Target and you can buy a USB
memory stick for $15 and you can't even find a floppy
drive anymore, a floppy disk. And what we lack today
is we lack the ability on a purchase order to tick
the box that says I want my device to be
interoperable and to support a whole host of clinical
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use cases. MD FIRE tries to see that thinking, but
there's a long way that we have to go before we get
there. Until we can tick off the box and place the
order, we're going to continue to have this problem.
So I think there's a lot of work to be
done, but once it's available in the marketplace,
then things will move. And so part of being here
together is to figure out how to make it happen in
the marketplace. And we need the community, the
academic community, the regulatory community, and
others, to really make that happen, to partner with
those who can build it. Thank you very much for your
attention.
(Applause.)
MR. ROBKIN: Thank you, Julian, and thanks
for the plug on MD FIRE. If anybody needs some
acronym consulting, I'm available.
(Laughter.)
MR. ROBKIN: I'm Mike Robkin. I'm one of
your steering committee members for this workshop.
I'm up here to introduce e-Patient Dave, Dave
deBronkart. Dave is a high-tech analyst and a high-
tech marketer. He's also a Stage 4 cancer survivor,
and he has been blogging that experience and others
on a blog called, appropriately, e-Patient Dave.
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It's a very insightful and provocative blog.
If you're not aware of it, I would strongly
recommend that you follow it. He brings up many
issues, some of which you're going to hear about now.
And Dave is also founding co-chair of the Society for
Participatory Medicine. And the fact that it took so
long to have a society for participatory medicine is
an indictment of where we have been and a sign of
hope for where we can be. So please welcome Dave.
(Applause.)
MR. deBRONKART: Do I get a keyboard? So I
know this is a great challenge. Speaking right after
lunch, people's bellies are diverting all the blood
away from the brain, and people tend to fall asleep
during a speech that's not vigorous. It's even worse
when we're late for lunch, with no coffee at the
coffee break. So it's my job to make it worth your
time. I'll be as quick as I can. So a punchy little
title here, a little different from what we've seen
so far.
Should this be advancing when I click the
mouse?
UNIDENTIFIED SPEAKER: The space bar.
MR. deBRONKART: What space bar? There's
no computer here.
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DR. GOLDMAN: It's FDA-cleared. It'll
work.
MR. deBRONKART: Science, science, science.
UNIDENTIFIED SPEAKER: The arrows work.
MR. deBRONKART: The arrows work. Great.
Thanks. A quick review of how I came to be here. As
he said, I'm a high-tech marketing data geek. I do
database stuff in the marketing department. I worked
for a software company on Route 128 in Boston. Three
years ago I got sick, then I got better. I became a
blogger. I almost died, and we'll talk about that
very briefly.
The thing I want to convey here, when I
first started talking after I got better, I started
talking at medical conferences, is people talked
about patients as if they were somebody who's not in
the room. Each of the speakers before here today, as
excellent as they were, when they asked how many are
doing this, how many are doing this, nobody even
asked are there any patients here? And this is like
designing consumer products without talking to the
people who are going to use them. We're going to
miss the mark.
And I say this as somebody who's made that
mistake in my career. So your time will come. I'm
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sure some of you have already been through the
experience of being at somebody's hospital bed as
they're approaching death. This is going to be
relevant to somebody you care about sometime in the
predictable future.
I want to point to this. This is
HealthLeaders Magazine, which goes to 40,000 C-level
executives. Their cover story in September was on
the patient of the future, and this is about
participatory medicine. There is a paradigm that
says knowledge exists in the head of industry
professionals, physicians, and so on.
Anything I say about physicians, don't take
it as me saying doctors are crap. Doctors saved my
life, okay? I almost died and they saved my life.
I'm not talking about that. I'm talking about this
new relationship where patients are actively engaged
in being responsible for themselves. That means you
being responsible for your well-being as well.
People ask how I got into this. People
asked JFK how he became a war hero. He said it was
easy; they sank my boat. In my case, I went in for a
shoulder X-ray and they called back the next day and
said your shoulder's going to be fine, you've got a
rotator cuff problem, but there's something in your
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lung. And what that turned out to be, that was a
golf ball sized tumor that we eventually figured out
there were many of them.
This is a CAT scan slice through both of my
lungs. Still didn't know where they were. Had an
ultrasound and found out it was a big hunking tumor
in my kidney. In fact, there were two of them
sticking out two different sides, sticking to
different parts of my innards. That was a grim,
sobering night. That was three years ago this week
when we got that diagnosis confirmed.
I've been online since 1989. I Googled my
butt off to learn everything I could. What I read on
WebMD is the prognosis is poor. Almost all patients
are incurable. And, in fact, then when I talked to
the oncologist and found out the treatment I was
going to get was high-dosage interleukin, I went to
their website, and this just happens to be their
standard diagram of what Stage 4 kidney cancer looks
like, and son of a gun, by coincidence, up there in
that lung, there's that tumor that was there.
There's one in the left femur. I found out
later that I had one growing in my leg because the
leg broke. That's how advanced the cancer was. And
in addition to these, I also had one in my skull. A
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great picture, right? I also had these other ones.
And what I found when I scored my condition was that
my median survival time was 24 weeks after diagnosis,
and at this point two of those weeks had already gone
by. This will get you to focus --
(Laughter.)
MR. deBRONKART: -- and to care about what
works and what doesn't. Now understand also, I went
into this experience as a guy who spent his life in
high tech, watching industries evolve. Okay. So
this was all filtered through my experience. Now, a
chef who goes to eat a restaurant brings a different
experience to that from a chef -- from other patrons.
Second, e-Patient activity I get -- I'll
explain the word e-Patient later. My doctor
prescribed aCoRE. On the day of the diagnosis, he
handed me this prescription slip and told me to go
join this patient community. I later found out that
this was the best source of reliable, up-to-the-
minute information about kidney cancer anywhere on
the internet.
Because information changes so rapidly and
all our systems and our physicians are overloaded and
everything, they have a thousand -- the ordinary
primary physician has a thousand conditions to deal
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with, and I had nothing better to do than to study
kidney cancer.
Now, in my case they told me immediately
that I was already at the best hospital in the
northeast. I didn't need to go anywhere, but I knew
that with certainty. They also told me to try to get
high-dosage interleukin if you can. Many patients
who show up in that patient community don't hear that
from their doctors because their doctors' information
is out of date.
The third thing I did was I shared my PHR,
my hospital's medical record password, with family
and friends so I could be engaged with them. They
could help me understand what was in there. Some
people think that patient empowerment is about
patients now know everything. Well, no, sorry, far
from it, right?
One of the things I wrote about on my
journal that I started was reading one radiology
report that said visualized portions of the bowel are
grossly unremarkable. We all thought that was
amusing. I also misconstrued some CAT scan data.
This is not about a patient rebellion. This is about
patients participating and being engaged. Long story
short, the treatment worked. Fifty weeks after the
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original scan, this was what was left of that tumor.
Miraculous treatment. I love good healthcare, no
question about it.
Now then, I discovered the e-Patient
working group, this blog, e-Patients.net. This
avuncular-looking figure top center there is actually
Tom Ferguson, the doctor who founded this group. He
died in 2006. He said e-Patients are equipped,
engaged, empowered, enabled.
John Sharp of the Cleveland Clinic, when he
discovered our group this past fall, said if you
haven't read the white paper that's on this site, you
don't understand the future of medicine. It contains
many, many anecdotes of how patients, given the
access to information that the internet gives them
and the ability to connect with each other through
the internet, are contributing value.
Again, it doesn't mean patients are right,
doctors are wrong. It means -- and this is
profound -- that it is a real error to think that all
useful knowledge comes from people in the industry.
There are enormous amounts of good that can be done
to improve care this way.
This is a slide put together by my primary
physician, Denny Sands, who is a part-time physician
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and part-time works for Cisco Systems. He talks
about knowledge symmetry, going from knowledge
asymmetry to knowledge symmetry, from paternalism to
participation to a consumer-provider partnership.
This is a blog post that I wrote about a
year ago. This is the essence of this new kind of
relationship. Physicians are coaches. Patients are
players. We talked in the discussion on this blog
post. A common complaint from physicians is, you
know, they'll recommend, like my doctor will say,
Dave, you know, you ought to eat different, you ought
to exercise more, and that's the end of it. The
patient goes out and doesn't do on the playing field
of life what the doctor recommended. And I
commented, in that white paper, one of the
conclusions is the best way to improve healthcare is
to make it more collaborative.
So the question becomes how can we do that?
And this is Denny Sands. One of his points is how
can patients participate if they can't see their
information? Right? Imagine if you were responsible
for driving a car but you didn't have the same
information about where you're at that your mechanic
has. So we formed the Society for Participatory
Medicine, as Mike said. Now, here's where we get
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into the device thing. All right.
So we published weight guidelines, and we
encourage people to use a scale. What if we
published speed guidelines but didn't give people
speedometers? Now as it happens, when I came up with
this metaphor, I was talking with Joe Fedar (ph.) of
Continua last Friday, preparing for this talk, and I
came up with this idea of these monitoring devices
being like speedometers, and I said, you know, I wish
I had a photo to illustrate this point. Well, this
was on the front page of a local paper yesterday.
Very convenient. Think about this. You're warning
people what the speed is. What if that guy had no
speedometer? How would they be able to achieve their
best?
Now, I'm going to switch over and put my
high-tech hat on. Given that, you know, I say I want
a lot of really useful devices. Like I find myself
thinking, how come every time I step on my bathroom
scale, it doesn't get recorded somewhere? I'll tell
you, I try to be responsible about this because I
went online looking for a Bluetooth bathroom scale so
I could have the scale talk to my cell phone, which
would upload to the internet. The first page I found
said so you're too lazy to use a paper and pencil.
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(Laughter.)
MR. deBRONKART: And you think your problem
is that you need more gadgets. Right? But I do want
more gadgets, all right, because, you know, I've seen
-- the first half of my career was in an industry
called typesetting machines. This is an industry
that has been disrupted out of existence by desktop
publishing.
By the way, talking about interoperability,
the fonts that we saw in the first half of this day
were not correct because the Adobe Premier webcast
system does not properly render fonts from monotype.
And so here we are actually displaying in PowerPoint.
This interoperability thing, that's the world I came
from because I want to see the kind of high-speed
innovation that put my career out of business.
So some lessons from the high-tech
industry. Excuse me. Object-oriented programming.
There are principles called encapsulation and unit
testing. Some of you will be aware of this. I just
want to point out briefly that in this kind of
approach, you test the interface to each device, not
the internals of it, and you don't try to test the
whole workflow. Now, you certainly need to be sure
the whole workflow works right. We don't want the
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kinds of disasters -- I said on Twitter during your
talk, Sickening stories I know exactly. You know,
these are like train wrecks, right? The switch is
set wrong and everything happens automatically and
people die. So thank you for sharing that.
But object-oriented programming. Now
here's the thing. This is a relatively new -- well,
compared to the early part of my career --
discipline. I found this graphic last night, a
T-shirt that says object-oriented programming is an
exceptionally bad idea, which could only have
originated in California. And it's from a legendary
software guru, Dijkstra. He was the father of
structured programming. He got rid of -- he
campaigned against the Goto statement. If you're a
programmer, you'll know what that means. He was a
Turing Award winner, one of the leading minds in
software, but that was in 1972. The world has
changed since then. Moore's law, right?
The impact of Moore's law, I knew
programmers who wrote machine code that were like
super-optimized in the old days, and they hated the
fact that faster computers made sloppy programmers
successful. There you have it. The penalty for
changing your mind dropped dramatically when
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computers got that much faster. So flexibility
became affordable and actually became more valuable
than efficiency, super-optimized efficiency. I saw
companies go out of business because they didn't
recognize that this had changed.
The next lesson from high tech. And I
could talk for hours about this, but I'm trying to
get us to lunch. The old approach to developing a
product was called waterfall. Waterfall was things
would flow downhill. You would decide what you want
the thing to do and plan it, and you would make up
your damn mind and have things go downhill, and when
it got to the end, it would do what you wanted it to
in the first place.
When I was involved in product planning for
typesetting machines, it was so long ago that we
could look at an industry and say, you know, the
newspaper people need a machine that does X, Y, Z, so
let's study it for six months and then we'll hire
some spec writers and blah, blah, blah, blah, blah.
And then we'll get some developers and then we'll
invent a machine, and by the time we have the machine
ready to come out of the factory, the world was the
same as it was when we had those meetings two years
earlier.
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No longer true. Today, what you have to be
able to do is agile, agile development. I know some
of you are aware of this. Recognize that you can't
figure out in advance anymore exactly what you're
going to need once you're done. Deal with it. This
may drive you crazy, that you can't spec the whole
thing out in advance, but that's the way it is.
Besides, things change out there so fast that the
target moves once you start developing.
So what you do is you get started with half
a plan and you adapt as you go along. And in order
to that, you've got to keep your options open.
You've got to design the thing so that it's easy, so
that you've got its functionality all bundled up
inside itself, and the only thing you really specify
that the outside world cares about is the interfaces
between the things.
The third thing from high tech -- and this
is why it's so important that we accelerate the rate
of release of new devices: a rich ecosystem. Like
this is the Drupal content management system. It's
used to be build many websites these days, this
incredible ecosystem. This is software products and
companies that can connect to Drupal.
What this is means is, is if you start a
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company or you write a program in your spare time
that plugs into Drupal, you can play with all these
people. You have this vast market. If instead the
population of your ecosystem is constrained for one
reason or another, your market potential is
constrained, and that limits innovation.
The way I put it in a blog post in
September is I want innovation at a rate that
resembles the rate of improvement in cell phones. In
2011 I want to think that this healthcare tool I'm
using today is like that, is so 2009. Right? And,
finally, the last thing. I've worked in software
tests -- what did I do? Show full screen. There we
go.
This issue of a combinatorial explosion.
It's a geeky term. Here's a scenario for you. It
has to do with testing individual devices versus
every combination. Imagine there are 2,000 models of
Dell PC and a thousand models of HP printer. If we
test every one in isolation, we'll have 3,000 tests
to do. If we want to be certain that every
combination works, that's two million tests to do.
And I'm not downplaying the importance of
testing and total workflow things. I think there's
an application for, like, limit checks so that even
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if some combination of circumstances of devices
causes something to go out of whack, you have
something like your landing gear aren't down, that
kind of a detector. Or, you know, there's oxygen in
the lungs, don't turn on the laser. That sort of
thing.
My point here, though, is given that so
much -- there's so much opportunity to do good with
participatory medicine. Consider this: two million
combinations versus 3,000 individual items, 667 times
more work. Consider the budgetary impact, the
probability that'll ever get done, the time delay,
and that has a drastic impact on innovator's payback.
It impedes innovation, and the consumer's benefit.
We will not get there in time doing it that way. By
the time you are desperate for better healthcare, it
won't be done. The good news is, from other
industries, as other speakers have talked about,
there are methods that have been developed that we
can just pick up and use in this industry.
I want modern mash-ups. For those of you
who aren't familiar with what a mash-up is, it's
where we -- well, similar to the iPhone and Zipcar
story. You have something that was developed without
knowledge of what other things are going to plug into
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it. There's a pizza shop in my town that has a map
that says get driving directions. The people who run
that pizza shop don't know how to do that. They just
plug into Google Maps. That's call a mash-up. And
mash-ups increase the value of every piece of the
ecosystem.
Old school. My doctor actually has a
plastic model of a heart on his desk. Okay? And
then there's the visible man, plastic statue, right?
Well, a few months ago I was roaming around on the
internet and what did I find, visiblebody.com.
Three-D. A free website. Just click on things on
the menu on the left, remove the skin, remove this,
that, and the other thing. One of my tumors was
attached to my soleus muscle. I had no idea really
where the soleus muscle was. So I went in and I
found it. It's that blue thing there. And I could
rotate that in 3-D.
And then I had this epiphany. I had this
epiphany. I thought, you know, that digital CAT scan
that I have, why I shouldn't I have Google Earth for
my body so that my physician, instead of picking up
the plastic heart and saying, well, this is what a
heart looks like and your this-that is wrong, right,
he could show me, over time, look what's happening
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because you're not doing this, that, or the other
thing.
Now, here's the thing. If this data were
out there where innovators could get at it -- no.
You know what it is? My coat is hitting the
keyboard. Some people are just over-exuberant. If
innovators could get at the data, we could have stuff
like this coming on. Visiblebody.com is free. You
know what that adds to the healthcare industry
budget? Zero, right? You know what it costs when
Google hooks up something else like this?
So I'm not saying it's trivial. I'm saying
there are methods we could use that will produce
results. Don't leave me this way, in a ditch. Give
us speedometers and tachometers and pressure gauges.
Help us heed the guidelines. I can do a lot better
if I know how I'm doing. Here's a runner -- I
grabbed this off the web last night -- with monitors
on his arm. That's it. Thank you very much for your
time and attention.
(Applause.)
MR. deBRONKART: Shall we go to lunch?
DR. WEININGER: You can take some
questions.
MR. deBRONKART: Okay, questions? I can't
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believe you people have been so good and attentive.
Thank you. Any questions or is it just lunchtime?
It looks like lunch.
DR. GOLDMAN: Thank you very much.
MR. deBRONKART: Sure.
DR. WEININGER: I have two quick
announcements or one quick announcement that has two
pieces. Folks participating in Session 1 and
Session 2, if you would please come up with your USB
sticks and reload your presentations. We think we
have a better way than they were loaded originally.
So thank you very much. And lunch is outside.
Do I have any other announcements I was
supposed to make?
DR. GOLDMAN: Yeah. We should tell people
when to come back for the webcast.
DR. WEININGER: Lunch will be done at one
o'clock, so come back then, please.
MR. MURRAY: One o'clock, one o'clock.
(Whereupon, a luncheon recess was taken.)
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A F T E R N O O N S E S S I O N
(1:00 p.m.)
MR. ROBKIN: Well, I hope you enjoyed your
lunch. Ladies and gentlemen, we're ready to start
back up again with our first moderated session. We
were fortunate to receive many, many, many fine
presentations for this workshop, and so the
presenters have graciously offered to shorten their
presentations down to 5 or 10 minutes, as the case
may be, so we can get as much content as possible in
the workshop.
So we've organized these presentations into
sessions where there'll be a moderator and two,
three, four, or five presenters. And, hopefully,
with everyone's cooperation, we'll be able to stay on
time and on track and we'll have time for questions
at the end of each presentation. So I'll thank you
in advance for your cooperation and for your help in
keeping our questions and our answers relevant and to
the point.
I'd like to introduce Session 1, which is
"Lessons Learned from Existing Regulatory Practices."
The moderator for Session 1 is Brad Thompson here on
my right. Brad is an attorney, and he's the leader
of the connected health practice at Epstein, Becker
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and Green, and he's just recently agreed to be
counsel to the Continua Health Alliance on FDA
matters. Continua is, of course, one of the sponsors
of this event. And what Brad probably won't tell you
is he's also -- he wrote the book. He's author of
the book that is used in law schools on the
regulation of medical devices. So, Brad, all yours.
(Applause.)
MR. THOMPSON: Thanks very much, Mike.
This is a different style, this afternoon is a
different style than this morning. This morning you
could pretty much sit back and listen and maybe ask a
couple questions at the end and that was okay. Our
expectations, though, have gone up for you now. You
have to work for your lunch. We do expect you to be
very involved in this discussion, and we're going to
deliberately keep the three presentations to five
minutes each to make sure that you have enough time
to get your questions asked.
And your questions may be of a policy
nature. They probably shouldn't be, you know, well,
I've got this product, when can I get it approved,
kind of thing. So if you keep them to a policy
level, I'd appreciate it. But the goal is to have a
robust discussion. We have folks from a regulatory
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agency here. What they say is not binding. They can
just speak freely.
ELECTRONIC VOICE: At this time, please try
again. Please enter your --
(Laughter.)
MR. THOMPSON: That was not me. I didn't
do it. All right. So we're going to get right into
it. I don't want to cheat anybody from their time.
ELECTRONIC VOICE: Welcome to ready
conference. For security verification, please enter
your pass code followed by the pound key.
MR. THOMPSON: Can I just turn it off? No,
I can't turn it off, huh? All right. Why don't we
start off. Our first panelist is going to be
Dr. Maureen Baker. She is the Clinical Director of
Patient Safety of the NHS Connecting for Health in
England.
DR. BAKER: Thank you very much. I'll do
my best to keep to time. What this suggests is
that -- I'll talk over this guy for a start.
ELECTRONIC VOICE: If you need further
assistance, please call customer service at
(719) 457-6904 --
DR. BAKER: Maybe not.
ELECTRONIC VOICE: -- or (888) 254-3533.
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DR. BAKER: Anyway, as there is so little
time for the presentation, if there's anything I flag
out or say that anybody would like more chance to
discuss, I'm around all the rest of the conference,
so please come and talk to me about it later.
A bit of context as well probably is
necessary. The NHS, the National Health Service, is
the gateway for all -- pretty much all healthcare in
the United Kingdom. It has 1.3 million employees.
There are about a million contacts with the NHS every
day, and it covers primary, acute, ambulances, mental
health, the lot. So if any of you were wondering
about the NHS, then it's a fairly huge organization.
Now health IT. NHS Connecting for Health
is the agency that is taking forward the national
program for IT in the NHS. And I'm a physician with
a patient safety background. I was formerly with the
National Patient Safety Agency in England, and when I
became interested in the patient safety agenda, it
struck me that as a physician using IT in my
practice, 100 percent of British GPs, general
practitioners, are computerized, electronic health
background, e-prescribing, internet access, on the
desktop, et cetera, et cetera.
And my interest was how do we use this for
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safer care? What is the safety benefit from the IT
agenda? And so we've been working in this area for
the last five years, and when we started -- and I am
fortunate to work with some safety engineers who have
a background in aviation, missile systems, and they
have taken a very useful approach, I think, to the
question of the safe systems, how can we rule out
systems that don't introduce new risks to patients
that weren't there before?
And the combination of five years work has
been that we now have two sets of safety standards
for health IT in the NHS. And these have been taken
through our information standards board, so they're
now PACA standards. And we've actually been using a
formal clinical safety management system in NHS
Connecting for Health for some time. The standards
are based on that. And as with all standards, I
mean, this must be -- I think engineers are
wonderful, but why don't they give standards names,
you know? Why is it all letters and numbers?
So two sets of letters and numbers. And
this first one, DSCN 14/2009, is a standard for
manufacturers, and basically the principle is making
a safety case. So it's up the supplier to see if
this piece of equipment is safe in the context in
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which it will be used, and here is my safety case.
I've done a hazard assessment. I've thought through
what can go wrong. I've put together the mitigations
for that. Here is the evidence in my safety report,
and that's my safety case.
DSCN 18/2009 is the onus on the healthcare
organization, which is largely around safe
implementation and maintenance of health IT. Now, we
have these standards now. They apply, as I was
saying, to electronic health record, the EPIS (ph.)
guiding that we do, and electronic transfer of
prescriptions, the PAC service, GP to GP, and the
electronic record is transferred not just between one
practice to another, but possibly between one system
supplier and another. So we have all of these
programs, and they're now covered by the standards,
but that's with health IT. What happens when we now
move on to and want to incorporate devices?
So, much of NHS care in the UK is provided
from family physician practices, general
practitioners. Around 90 percent of all contacts
with the NHS are provided through GPs. And as I was
saying, the GPs in the UK have their computerized
systems, and they've had them for years basically, so
they're very familiar with them. We're now moving
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on, and we've had a number of scenarios this morning
about the potential there is for many more devices to
interact with these systems in British general
practices. But indeed any EHR, whether it's in
office practices in the U.S. and hospital services,
there are a whole -- the scope is enormous.
So let's talk about, in this instance, the
blood glucose scenario, where the patient has a blood
glucose monitor in the home and the results are
transferred electronically to the physician practice.
These are some of the components that might be
involved in enabling this. And then we come into the
regulatory issues. In this context, what is a
medical device and what is health IT?
Certainly in the UK there's a completely
different regulatory framework applying here, and so
you have to think about this: Which software is
medical software? Which supplier classifies which
component? And basically, is this -- would this be
considered an end-to-end medical network? There's an
American standard, IEC80002. Well, I think it
probably would be, actually.
However, the cost components are dealt
with, if there are any, in the system, and pretty
importantly, what are the responsibilities of the
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healthcare organization, again, under the existing
NHS standard? So I've gone through that quite
quickly. I just wanted to flag up to you a cross-
section of some of the issues involved.
Now, we've also got to consider that any
regulation needs to be proportionate and effective.
It needs to be effective in keeping patients safe.
Basically, else what's the point in having it? If
it's not proportionate, it won't work. I'll tell you
what'll happen with glucose meters and British GPs.
They have to go through a whole set of hoops, such as
they can satisfy it's safe to link up these glucose
monitors, they just won't do it. If they just won't
do it, that means that patients don't get the benefit
of that particular technology.
And by the way, manufacturers won't be able
to sell them in that market. So that's something to
be borne in mind. Okay, I'll say again meet the
plain ownership of safety responsibilities, and one
standard we're thinking about is IEC80002. Thank you
very much.
(Applause.)
MR. THOMPSON: All right, our next speaker,
Linda -- we have a switch on the agenda. Linda will
not be joining us. Instead, we will have -- I hope
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I'm pronouncing his name right -- Yi Zhang.
MR. ZHANG: Yes, that's right.
MR. THOMPSON: Oh, I got it. Good. He's
with FDA/CDRH.
MR. ZHANG: Thank you, everyone. I'm
Yi Zhang. I'm a software engineer from the Office of
Science and Engineering Laboratories of the CDRH
center, FDA. The scenario I'm presenting today is
about diabetes management in home environment. I'm
hoping this scenario can inspire the discussion here
about what considerations need to be made on the
interoperability of home-use medical devices.
As you know, diabetes is one of the leading
causes to deaths for American people. Diabetes can
be categorized into Type 1 and Type 2, depending on
how the patient's pancreas is defective in insulin
creation. A patient with Type 1 diabetes cannot
produce insulin at all, so they need to use infusion,
the injection, to survive.
Currently, the -- of patients with Type 1
diabetes in the United States, about 10 percent of
them use insulin pumps for insulin DB rates.
Basically, the insulin pumps can provide two basic
patterns of the insulin DB rate, first, a specialty
rate, DB rate, which uses a low-rate, continuous
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insulin infusion to replace background insulin
secretion. The other type is corrective bolus
insulin DB rate, which administered a bolus of
insulin immediately and to bring a high blood glucose
level back to normal or to cover the carbohydrates in
a meal. So although it's very hopeful in managing
diabetes, the insulin pump can put patients into
risks. According to the FDA database, in 2008 there
were more than 5,000 adverse events reported, related
to insulin pumps.
So one of the primary reasons about the
insulin pumps is that patients operated their pumps
mostly in home environment, where they have no access
to the operation instruction, technical support from
their doctors and the physicians. So they are more
likely to make mistakes in configuring correct,
appropriate insulin profiles. Plus, current insulin
pumps require the patient to do a finger-stick test
to detect Vg levels.
As the technology advances, more and more
diabetes patients use glucose sensors for continuous
blood glucose monitoring and to save the trouble of
doing finger-stick tests. A glucose sensor can be
either subcutaneous or implantable.
No matter which format it is, a glucose
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sensor needs to produce digital readings every few
seconds. More of the glucose sensors can now talk
directly to the insulin pumps to save trouble -- save
the patient the trouble for manually inputting
readings to the pump. Then insulin pumps can
calculate the bolus dosage based on the digital
readings received from the sensor. However, the
current glucose sensors are pretty mature because
-- many because they are not accurate enough. For
example, a implantable glucose sensor can only
guarantee 85 percent accuracy.
So the diabetes society is locating --
bring multiple glucose sensors in to assist and to
detect Vg levels simultaneously, which clinical
studies -- many clinical studies have been done on
this direction, and it shows using medical glucose
sensors can significantly improve the accuracy of a
sensor.
Having this scenario defined, then, what
consideration we need to make on the safety of the
system? Or, especially, what interoperability issues
we need to consider behind this scenario? To my
opinion, we need to address at least the four or
three issues.
First, communication failures. We need to
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ensure the safe, secure, and the robust communication
between the insulin pumps and the sensors. Among
many communication issues, the most important one is
how the pump can decide appropriate Vg readings if it
fails to communicate to at least one or more glucose
sensors.
The second issue is the electrical
compatibility issues. Since being deployed mostly in
home-use environment, these pumps are open -- exposed
to various sources of radiation. So the performance
of a system as well as the interaction between the
pump and the sensor can be affected by the radiation.
Also the system can upset other medical devices that
a patient wears, wear the EMI issues.
So what standard should be -- the system
should comply with in order to ensure correct
performance and the correct interaction for the pump
and the sensor? And then the system is also open to
extreme environmental conditions like excessive
humidity, extreme temperature, vibration, dust, et
cetera. Those extreme environmental conditions can
also affect the performance and the interoperability
of the components.
So interoperable diabetes management
systems should not only include a pump, many sensors,
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but also introduce the physiological sensors and
remote connection with the doctor's remote
telemedicine. The reason to introduce physiological
sensors are twofold. It's twofold. First, it's more
dangerous and life-threatening that the insulin pump
continue to infuse insulin even if the patient is
closing the pump due to severe hypoglycemia. So the
system would be much safer if it incorporates
physiological sensors that can detect if a patient
falls into coma and instruct the pump to stop
infusion. And the second reason is the patient's
sensitivity to insulin, he worries when his physical
condition changes. So bringing more physiological
sensoring to the system can keep the pump better
input about what the patient's physical condition is
and how to adjust the DB rate accordingly.
One factor about the insulin pump is -- the
insulin pumps is that they manage your diabetes
passively, but the remote assistance from the doctors
can only instruct the insulin pump to approach
optimal DB rate profiles very quickly. So
telemedicine is also a key issue to develop safe
interoperable diabetes management. What safety
issues and the interoperability issues we need to
consider for this ideal situation, when the
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situation -- if the situation is compatible. So I
would like to leave this question to the workshop.
Thank you.
(Applause.)
MR. THOMPSON: Next we're going to have
Mary Brady, who's the Associate Office Director,
FDA/CDRH/OSB, responsible for home care initiatives.
MS. BRADY: Okay, I'll try to take my five
minutes here. So basically what we're going to go
through is a home-case scenario. I tried to keep it
as simple as possible, yet you'll find out it could
be very complicated as well.
So I looked at a heart rate monitor,
something that's going to usually look at transient
symptoms of people, such as palpitations or syncope.
Usually the person is also hooked up to a scale of
some sort, and they're also hooked up to some type of
blood pressure measuring system.
These all then go into a data aggregation
device, and it's a physiological signal transmitter,
and it receives information as well. It can record
any type of activity. In this particular scenario,
it's going to record the weight, the blood pressure,
and the heart rate monitor. All of this data is
recorded online, and it is transmitted to the
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physician, who receives this and can take action on
it. And if there's a problem with the wireless
transfer, some of these also can be hooked up
telephonically.
So what you have basically is a single-
component system that delivers continuous and
sometimes periodic computerized monitoring. This
happens typically 24 hours a day, seven days a week.
It automatically transfers that data, and it can be
in another state. It can be a far location. It's
not just right down the road. It's not just, you
know, down the street. It promotes patient
compliance through its ease of use, and this is
something that's very important in a home
environment, that it's very easy to use for the
patient. And remember, again, it's wireless data
transmission. So they're supposed to be allowed to
manually record this data and transmit it
telephonically.
And here's just a picture of the case
overview, where you're having the three different
systems going into the aggregate system and then that
transfers up to the physician's electronic health
record.
Okay. So here's the situation. This just
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happened last month, and this is a real-case
scenario. This patient was having transient episodes
of syncope. And so she went to her physician and her
physician said let's monitor you for a short period
of time. So she did. She received an expired device
from her physician. Walks out, turns around and
looks at it and says this is expired. And he said
that's okay, you can go ahead and still use it, it
works. So as soon as she gets home and it's all
hooked up, it starts alarming, and this is due to it
being expired. So she has to switch this out now.
Okay, now she receives different information. She
has called the 800 number that's really nicely
located on this device. She calls them and she gets
different information each time she calls down there.
And as she's waiting for her new device, she's
sitting there quite anxious and her physician can't
help her at this time because he doesn't have any
more devices with him.
So she started receiving phone calls, and
after the device started working, she got her new
device. It started working, okay, and it started
alarming and she would call them -- that's not on
this particular thing, but she would call them and
say something's wrong here. And they said, well,
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we're not receiving any data that says you have a
problem. And she said, well, it's alarming.
Well, then she turned around and received
phone calls from the data receiving site, wondering
if she had disconnected the device because they
weren't getting any readings. And she turned around
and said, well, no, it's all connected. I don't
understand what's going on. First I call you and I
have an alarm and you don't catch that, and then you
call me and say you're not getting any signal. So
there was a mix-up two different ways there.
She lives in the first floor apartment at
the base of a hill. Some days she can't use her cell
phone, and she was thinking, hmm, is there something
that's kind of associated here? So she would move
over to the window with her heart rate monitor, and
sure enough, it would start working again. So she
was concerned that what was going on with that
aggregator that was taking all of that data had the
same issue as the cell phone and was hoping that she
could get that data transmitted manually just in
case, but she did not receive a manual monitor with
this.
So she's really unsure how much data was
really transmitted through that device, and when she
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called her physician, he said, oh, I think I have
enough data. Let's go ahead and work with it. And
she didn't want to wear anymore anyway. So you're
looking usability, usefulness, things like that.
So the potential problem here is that this
is a signal-detection risk and it's possibly poor
quality of service with a medical device. It brings
you to ask, you know, who is responsible for the
different areas? If it's being used in the home, who
is responsible for the good transmission of the data?
And is there national reliance upon data? If we take
this out and broaden it to the entire United States,
who's responsible to make sure that that data is
being received here and being sent properly? And are
there going to be integrity problems that increase as
home use increases with this type of device? And how
does this design influence the ease of use?
In the error messaging area, you just have
to think about what kind of alarm should be there
when the device is disconnected or transmitting data.
Should it warn about interference and to what extent
do we provide warnings for this and how many warnings
should you be providing?
And in the area of troubleshooting, how
should troubleshooting occur when you're not sure
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what really is happening? So how do you go through
that? As a patient yourself sitting in your home,
how do you try to figure out what's going on with
your device?
And for data identification areas, when you
move devices from one person to another -- remember,
this was bring transferred from one patient to
another to another -- how does it know it has changed
to the next person? And we kind of talked about that
earlier this morning. And how long can you keep the
data from each person inside that device? So these
are just issues that are up for discussion today, and
hopefully we can get some good talk on them. Thank
you.
(Applause.)
MR. THOMPSON: All right, what I'd like to
do -- and by the way, for the panelists, we've got
these microphones. You can stay where you are for
this part, but you're going to have push the button
that sits right in front it, down at the base there,
in order to be able to talk, I believe. All right.
I'm going to open it up for questions in
just a second, but I have a question that I want to
go down the row and ask the panelists to comment on,
and then we're going to turn it over to the audience
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to get your questions as well.
All of you come from regulators of various
sort. That may not be a good description of the
English counterpart, but you're all involved in
health policy. I want to ask you a question, not so
much from a legal point of view, because that's too
much minutiae, but I want to ask you one from a
policy and a clinical standpoint.
Each of you presented an array of
technologies that began with a device that touched
the patient in some way, measured something, in some
cases even an insulin pump that delivered therapy.
And then it connects through a series of steps,
components, to either a computer or a cell phone, and
it's ultimately, maybe, transmitted to a physician's
office, and there's software involved at each step of
the way. From a risk standpoint, just a risk
standpoint, which components do you think ought to be
regulated? Okay?
So do you want to go through your scenario
in your mind and figure out which components you feel
engender enough risk to merit regulation by the
appropriate body, from your own cultural perspective?
I realize we have different jurisdictions involved
here. Do you want to begin? It's essentially the
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questions you posed rhetorically, Maureen, at the end
of your -- the second to your last slide, you had
which are the devices and which software gets
regulated? I'm asking you to sort of answer your own
rhetorical question.
DR. BAKER: Yeah, yeah. I think there does
need to be a regulation framework that encompasses
the whole system. Now, that's not to say that
manufacturers of cell phones need to comply, you
know, so that -- I mean, they don't care whether
their cell phone can be used for this application or
not. But the body that introduces this as a system
would need to provide -- in my opinion, there needs
to be some assurance that if you're going to put a
cell phone in this, you can do it safely. And so I
feel that there does need to be a regulatory
oversight of that, but where it should be, I think
we're just really in the process of teasing out
because at the moment, and certainly in the UK and in
your context, it isn't clear and the questions are
really just starting to be asked, as far as I can
see.
MR. THOMPSON: Can I press that just a
little bit further to get a little bit more specific?
If I have a cell phone, call it a pear cell phone,
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but just a hypothetical cell phone, and the medical
device manufacturer says you can connect my device to
a pear cell phone -- pear as in the fruit and not the
pairing -- is the medical device manufacturer then
responsible for showing that they can work together?
Is that the point you're trying to make?
DR. BAKER: Yeah, I think it's like a -- so
you know, if you buy a computer game -- I think we
still do -- so you can use this on machines that have
got this capability, and it'll be a list of what the
capability is that's required for that game to
function properly. So I would foresee that as part
of the case the supplier needs. And yes, it can link
up to the cell phone, but the cell phones need to
have the requirements, and then presumably it's then
up to our -- or possibly the health organization of
group to see, yeah, this cell phone, the one I got
here, is appropriate for this device to connect to.
MR. THOMPSON: I want to ask the same
question. You described an interconnected blood
glucose sensor and pump, but you also described then
a remote connection that might be ultimately tethered
to a physician's office. So could you describe which
of those components, just from a risk standpoint, not
a legal standpoint, but from a risk standpoint, which
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of those components ought to be regulated?
MR. ZHANG: Well, first I'll make it clear,
the role of our Office of Science and Engineering
Laboratories is to provide engineering support for
the regulators in FDA. So this might not -- I might
not be the best one to answer this question. But
from the engineering point of view, of course, for
insulin pumps and glucose sensors, right now they're
independent. They are considered as separate medical
devices and they're regulated by FDA.
About the connection between the pump and
the glucose sensors, I don't see any -- I did not see
any submissions in this scenario. But the data
transmission from the insulin pump to the remote --
to the doctor's PC or the physician's, I would like
to let Mary answer this question. And it has to be
regulated by someone, but I don't think the FDA.
MS. BRADY: Yeah, I think I can speak more
from a clinical perspective, and I welcome our folks
in the labs to come up if they want to offer up
something. But I believe there needs to be
regulatory oversight for an entire system when it's
being used outside of a controlled clinical
environment. Once you're going into the home and
outside of a clinical environment, it's virtually
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uncontrolled.
So there needs to be some sense of that
what you are doing, there's reassurance that if
you're trying to diagnose and provide treatment to a
patient, that there's assurance that something is
actually happening and it's accurate, accurate to an
extent that we want it to be in that kind of
scenario.
I believe, when you have a system that
starts off with a patient and they are feeling that
they are safely being monitored from a remote site
and they have no way of understanding how to
troubleshoot something or know that their information
is being transferred, that there needs to be some
sort of mechanism that way.
To the area of cell phone technology and
all of that, where you have an intermediary piece,
all the different pieces that go in between the
patient and the physician, I think there needs to be
some sort of oversight there as well. I'm not saying
that FDA needs to call them all a device. We don't
know that. We're still in the process of working
through that. But what you need to have is an
understanding that when I have this device, I'm
probably going to have this for a period of time, and
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the way that technology upgrades itself so
frequently, I'm not sure that if you kept everything
separate, that every piece of that technology would
be keeping up with each other.
So if you're upgrading your cell phone, is
that also going to handle that application or not?
Just, you know, questions we need to be asking
ourselves right now.
So I think there needs to be some type of
oversight overall to make sure that when these things
say they're operating as a system, they continually
and consistently operate as a system.
MR. THOMPSON: At this juncture, I
forewarned you that I wanted a lot of audience
involvement. Are there questions and comments from
the audience? If so, you'll need to go to
microphone, please. Yes.
MR. deBRONKART: First of all, the story of
the idiot company with the data collection device, I
went through exactly that with Wells Fargo, trying to
get an erroneous payment returned to me a week ago.
Every person I talked to, seven phone calls over
eight days, said the previous person had it wrong.
And the amazing thing is that they are really
competent at their processes for receiving money.
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(Laughter.)
MR. deBRONKART: And not for dispensing it.
And it wasn't that they were crookedly trying to hold
on to it. They just obviously had the idiots working
in that department. Or, actually, it's more likely
that they just hadn't defined their reliable process.
So it's easy to be a smart aleck and rant about this
stuff, but there really is a question: How do we go
about engineering the processes that will make the
right things happen?
The best thing I know from my business
experience is to get -- is to put into the process
the people who suffer if it's done wrong. Okay?
Now, diabetics happen to be a great community for
this. They're like the prototypical e-Patient, very
engaged. They're happy to stand there and say no,
wait a minute, you didn't do this, you didn't do
this, we need this, and things like that.
So I'll just float out the suggestion that
involving what we call the invisible stakeholder,
right, the patient, in the certification process is a
good approach. The other thing -- and this is a
question. I don't know how we go about it, but I'm
kind of surprised, given how things go in the high-
tech industry, that there are these issues of how
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devices communicate reliably, right? Like a device
is sending out a signal, but there's no closed loop
verification that the data has got there, right?
The basic way that the internet is designed
is something gets sent out, and you get word back
that it arrived. And if it didn't happen, then it
tries again and it tries again, and eventually you'll
get an error message saying you couldn't connect.
So I don't know what to do. What I'm
really curious about is how could it be -- and I mean
this not as a wisecrack. How it could be that so
many smart people would not be aware of existing
solutions for things like getting data from one
device to another?
MR. THOMPSON: Any of the panel have a
reaction?
MS. BRADY: I think they're afraid of
regulation.
(Laughter.)
MS. BRADY: No, I'm just kidding, I'm just
kidding. I'm not sure. I think that's why people in
this room are together now to say this is something
really that could potentially get out of hand and
that we need to start putting some sort of wrapping
around it at this point. That's my understanding of
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this. I can't agree with you more. Yeah, thank you.
MR. THOMPSON: Why don't we go over here?
DR. MUN: I'm Dr. Mun from HCA. We have
been doing exactly the patient monitoring at home in
the last six months, and we have done wireless and we
have done 802.11. We have done -- the experience we
have had up to this point is that insulation issues
are very difficult because when you walk in a home,
initially we thought the easiest thing to do is use
wireless G.
So then you can just put the device in and
just walk out. You don't have to touch anything.
Because we are afraid if you go in there and touch,
let's say, phone lines or even their video lines, if
something does go wrong, then how can you manage
that? So that's what we decided to do initially.
And then a problem became that some houses
have good reception and some of them don't. And the
next thing we realized is that the cell phone company
changed the protocol it's sending information between
cell towers. So all the things we have done first
three months went down the toilet because we're
convinced that they changed it, because initially
they denied that they changed anything. And so this
was -- to put it very nicely, it was a circus on our
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side and we looked very stupid. Meanwhile the nurse
who's getting this information -- in our case the
nurse gets the information and then gives it to the
physicians because they filter it, and a physician
comes out, looks at all this information, and there's
the basis.
So when the communication does not happen,
the nurses now feel that they have a liability
because they have this information but they cannot
give it to the physician, or they cannot collect
information on time. So I know on the physician side
they are saying why do I have to look at this thing
every day? Am I getting paid for this? And they're
not.
So in terms of regulatory issues and all of
that, I think before we go there, we need to have a
reliable system, and we need to have a clear
definition of what the service is expected to be
provided as well as expected to receive because
without that, I don't think any regulatory issue
would make any sense. Thank you.
MR. THOMPSON: Anyone on the panel have a
thought or reaction?
DR. BAKER: Yeah, cleaning up. This is why
we need to really start working to think how you do
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it properly. And it is something about thinking of
the device, the piece of cake, in the system in which
it works. You cannot think of a piece of cake in
isolation.
MR. THOMPSON: I think you stood up next.
MR. GRYZWA: Okay.
MR. THOMPSON: So we'll do you and then you
over there.
MR. GRYZWA: There's something I'd like you
to consider as you develop these systems that we
talked about, like the aggregator, clearly a piece of
medical equipment. What we struggle with -- I'm Mark
Gryzwa. I'm from Boston Scientific today for the
management. We have a Class III implant in a
patient. How do we classify the device that will
then talk to it? And if it is a commercially
available cell phone, what do we with that software
on that, and how do we partition that from the other
software that may be on that phone?
Then you get to the internet quality or the
3G network, AT&T, the very service providers out
there in the world. Do we put some kind of
restriction on them as well? We talked about like if
you were on AT&T, is that enough to make it work?
And then, now we get to the back end system, as I
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like to call it. How do we classify that, which is
really just store and present data? And then if we
manipulate that data in any way, have we increased
our risk?
So these are all questions that we wrestle
with daily on these systems, and the more clarity you
can provide us as to how that classification can work
throughout the system -- we acknowledge that it is a
system front to back and that system can include your
IT professionals. It can include people that answer
the phone. But we really need some clarity as to how
that works all the way through. It can't be Class
III medical all the way down to the server, but what
is it is what we've been wrestling with.
MS. BRADY: My question for you, I guess,
is have you worked through this at Boston Scientific?
Have you come up with some ideas as to how you think
this would be best taken care of, each piece of the
system, as you're talking about?
MR. GRYZWA: Sure, we have tons of ideas.
(Laughter.)
MR. GRYZWA: We never lack those. It's how
do we get that dialogue like this, with folks like
you, on a regular basis, to say, here's what we're
thinking? Where do you want to take this? Because I
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think you're struggling with it as much as we are, if
not more, in rating more and more of these systems
heaped on you. They're clearly not unregulated.
What, you know, we look at is a lot of EHRs. A lot
of EMRs today kind of got into existence without a
whole lot of oversight, and now they're becoming
slipped in. We're trying to figure out where we fit
in that, kind of that broad spectrum of things.
MR. THOMPSON: By the way, I've been given
the two-minute warning, and I apologize to those of
you standing up, but maybe we can have discussion
over the break or something with our panelists, but I
think we only have time for one more question. In
the blue stripe.
MR. WITTERS: My name is Don Witters. I'm
with the Center for Devices and Radiological Health.
I lead the electromagnetic compatibility and wireless
group. Many of the issues that were discussed here
have wireless components in it. But I wanted to get
back to your question, which is really working in a
shared-risk environment with not only wired but
wireless components. How do we manage that? How do
we get a handle around it? How do we get that
framework, as one of the speakers talked about it.
Mary's example is a good example, I think,
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of quality-of-service issues because there wasn't a
good quality of service. One of the other speakers
spoke to that, too. But there are also other aspects
that deal with this. To get a handle around it, we
need to develop a better process by which we can
recognize, by which we can develop the tools, the
information, that are independent of any particular
point of view but are right to the focus of this.
We developed a guidance, a draft guidance
for wireless medical devices. We are also involved
in a series of workshops since last year, where we
were discussing these issues and how we can come
together. Some of that started to deal with some of
the aspects of the questions that you had.
So I think not only do we need standards,
we need standards that not only involve safety but
effectiveness, and there are really no standards that
deal with effectiveness. We need processes that
really deal with these fundamental issues of the
shared risk. Whose risk is it? Whose responsibility
is it?
There is one aspect that's being developed
now, the ISO 8000-1, which does speak to network IT
and risk management, that is coming to fruition.
That's only one piece, but more tools need to be
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developed. So I'd just encourage a more vibrant
discussion with as many of the stakeholders as
possible in this area.
MR. THOMPSON: Thank you very much. I've
been told that we're out of time, unfortunately.
I've also been reminded that we're going to have
sessions later on in the program where we're going to
break out into working groups, and a lot of these
topics will be great for discussion fodder among
those groups. So I want to thank our panelists very
much for their contributions.
(Applause.)
MR. ROBKIN: Thank you, Brad, for
moderating that session. The last question, I think,
is a good segue. This is the session on Enterprise
Issues. I'm Mike Robkin, and I'll be your moderator
for the next few minutes. First up will be a
presentation by a team from Kaiser Permanente. Doug
Grey, who's a physician and chair of the Kaiser
Permanente National Product Council -- sorry, the co-
chair. Vice chair?
UNIDENTIFIED SPEAKER: Vice chair.
UNIDENTIFIED SPEAKER: He's the vice.
MR. ROBKIN: Vice. So if you're not
familiar, Kaiser is, of course, a very large
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provider, and the National Product Council oversees
the acquisition of Kaiser's medical devices. So here
is the voice of the customer. He'll be followed by
Tom Judd, who's National Project Director, and then
Tom McGrane, a principal solution consultant. After
that we'll have a presentation by Tim Gee, who is a
medical device connectologist. He runs a blog.
What's the blog?
UNIDENTIFIED SPEAKER: Medical
Connectivity.
MR. ROBKIN: Medicalconnectivity.com. And
he's the founder of the first conference on medical
device connectivity. So Doug.
DR. GREY: Thanks. The first time I met
Michael was when you made the decision about our
digital operating room, and for those that are
unfamiliar with that term, that's really how surgeons
manage images in surgery. In other words, if you're
doing laparoscopic surgery and you want to see the
gallbladder, that's what it is.
And so about two days ago Michael said
we've got some urgent news. We've got to truncate
your presentation down to five minutes. And so I
said I could do you one better; I could do it to five
words: can't see, call biomed.
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(Laughter.)
DR. GREY: And you've all probably heard
that before. We're going to divide our presentation
into three components. My first is from a
physician's perspective, a provider perspective, and
also a procurement perspective. There are some
clarifications that have to be done around the loaded
word of integration, where integration has become
ubiquitous in our system, and I'll clarify that. Tom
Judd is going to talk about the unique challenges of
a digital operating room, and lastly Tom McGrane will
talk about some IT challenges and potentially
opportunities.
Integration. The elephant in the room for
us is when we opened our first hospital for -- with a
digital operating room, and I got a page when I was
in Washington about 10 minutes later with a guy
saying I can't see the gallbladder.
This used to be an environment where you
plug a monitor in, you plug a camera in, you'd
connect the two, and everyone was happy. And I think
what has happened now is there are a raft of devices
that have to integrate.
And so the image, instead of going directly
to a monitor, goes through all sorts of circuitry so
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that you can recall images from the medical record,
you can store them, you can capture them, you can
compare them. All of those things have to be done.
And so the elephant in the room for us is now we've
gone from a world of a nurse turning on/off switch to
something where you need an IT consultant to fine-
tune your operating room.
But integration for Kaiser means even more
than that because I can guarantee you that there's
not a surgeon that I work with that really cares
about the back end, front end, or anything else. All
they want to do is see a picture. And so there's all
sorts of IT integration that has to take place if you
are going to meaningfully capture those images.
We have been trying to be creative because
when you craft a new contract and you've got a
billion dollars of installed base of equipment and
you make a procurement of $10 million of equipment,
you have to integrate that into your system. How do
you go about, as a chess game, managing all those
unique devices so that you can move them between
hospitals, around in rooms, et cetera, to make them
more effective?
The integration, to the nurses, they raise
their hand and say pardon me. I don't have a
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bachelor's in integration. This is going to affect
my workflow. I'm here for the patient. How I am
going to manage this with all the efficiency and
quality measures that you're likewise inflicting on
me? So integrating into the workforce is one of our
great initiatives. We've got a whole center
around -- just near the Oakland Airport to really
focus on how this equipment gets integrated into the
workflow. That's something that is another issue.
We build two to three hospitals every year
and open them, and yet the hospital's a hybrid of
equipment. They aren't just new equipment. We
cannibalize all sorts of different things to make --
in the name of efficiency.
But then Tom Judd gets called, and he has
to integrate different cameras, monitors, routers,
the cabling is new, the interface with a different
supplier because the interface last year was with one
supplier and now we have supplier B that needs a new
interface. So all of those challenges are something
that aren't in the name of integration of seeing a
picture in an operating room, but those are equally
important.
And then, lastly, we have a whole
contracting arm, but how do you go about quantifying,
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when you acquire new devices, what the actual cost
is? Because we're in a mode now, in this new
environment of the obligation of plugging something
in and having it connect, that you may save 10
percent on a contract but then spend 30 percent
trying to solve the problems of integration into the
system that you couldn't solve because you couldn't
anticipate it.
So these are all integration issues. Yes,
we can talk about the interface and the direct
connection, but those are equally important and
likewise will have tremendous impact on the quality,
the safety, and the value and efficiency of what
we're trying to accomplish. So I will hand the baton
to Tom.
MR. JUDD: Thanks, Doug. We've done some
simulation along the lines of this particular case
study, and a lot of this capability is, of course, in
use. And I'm going to make it simple and fast here
because I was asked to. But from an image management
-- I mean, obviously there's Julian's, wherever you
are, anesthesia and vital signs measurement and
monitoring going on. This is the image management.
What's new about image management? Of
course, the radiographic image is being pulled in,
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whether they're real-time or, you know, archived
images. But the whole visible light -- I heard the
Director this morning talking about using those jpeg
images in many creative ways.
So management of visible light in the
context of visual operating image management, where
we're talking about a cockpit computer in the corner
that does a lot of functions. We're talking about
the tower with the camera control unit and the
endoscopes in the operative field and so on.
So here's some of the things we've seen,
particularly for those surgical specialties that use
a lot of images. What we're really talking about is
changing workflows, optimizing workflows, higher
quality care with better efficiency. So there's a
preop component to it. This, by the way, is able to
be automated for different surgical specialties,
different procedures.
But what do you look at before you go in
the room? What combination of digital visible light,
digital pictures, radiographic, and so on? How do
you set up the room so that, you know, between cases
all you got to do is say what the procedure is and go
in and do it? Intraoperatively, what do you display
where?
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You know, we got urologists, for example,
that need to look at high-res fluoroscopy on one
screen right next to high-definition endoscopy to put
the catheter at the right place at the right time.
And there's the whole -- how do you manage the
process of capture, annotation, storage, and so on,
the image management postoperatively? Other things
that come into play in this, what is that aggregator,
that first link that was talked about in the HPSP
documents, to manage this process? What about
bringing in wireless devices like ultrasound? How do
you wrestle with that? Doug talked about image
management role definitions. How does this change
what the nurse does when in the procedure and what
the doctor does before and during and after the
procedure? And then bring in the component, not just
of surgery, but setting up the surgery with the
virtual visits and pushing images around before.
So this is just a quick flowchart. We kick
off this digital operating room process with the
patient demographics that allow the middleware, the
DICOM wrapping of the images appropriately, and then
the HL7 messaging that tease this back up to the
doctors and the electronic health record and then a
visual of that. Tom.
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MR. McGRANE: So it's doctor, biomed, IT,
and that's the pecking order within Kaiser
Permanente.
(Laughter.)
MR. McGRANE: Lined up just right. Okay.
So speaking a little more generally beyond just the
DOR effort, initially, one of the things we're
focusing on is we have a very large enterprise
network. We have eight different regions, 32
hospitals, and Kaiser's pretty big, as I'm sure you
all know, and within that there's a lot of networks
and a lot of systems that have grown up.
So we're right now trying to integrate all
of our systems onto a common enterprise because as we
move to an EHR, which we have primarily done, and we
have all of the information, we have the ability to
put all the information onto a common platform, a
common EHR, but we don't have all of the systems that
collect data yet onto the network so we can get to
the EHR. So that's the process we're in.
And, you know, as we do that, we have a lot
of challenges, and this goes to, I think, a lot of
the questions we heard from the previous panel about
the standards and where you impose standards and
regulations and perhaps where can you go -- if it's
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too regulated, it's very difficult. You can't get
the -- I like the term mash-up, if we're over-
regulated.
So from an IT perspective, we have this
huge responsibility to make sure that all of this
traffic going across this enterprise network isn't
infected with viruses, isn't corrupted, you know,
people aren't, you know, stealing data. And that's a
tough thing because it's always morphing and people
are getting more creative, so we have to stay on top
of it. So as we have our, you know, switch and
router vendors, like Cisco, constantly developing new
technologies, you know, WEP protocols for better
crunching, we want to be able to, just as quickly as
they develop it, overlay it into our network. The
challenges we often come across as we start bringing
in different systems on the biomedical systems is,
okay, we want -- you can come on to the network.
There are these rules or these guidelines,
and oftentimes it's like, well, we can't do that, we
can't have that version of malware run on this
device. Why not? And often we hear, you know, FDA
regulations. I think sometimes that's overused by
our biomed buddies. You know, I'm not so sure, but
we do hear that a lot.
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And to the extent that the devices that we
do incorporate from an IT perspective are over-
regulated, there's a balance here, you know, we all
understand, but it really inhibits the ability to
bring them on board and to get the patient data to
the record, electronic record, so that it then can be
shared across with other medical centers.
Like Kaiser -- had started interoperating
and sharing their data. But if we can't mash-up, if
we can't work nimbly, it's going to be very
challenging. Under the specific recommendations,
this is kind of back to the DOR example I wanted to
add in this. So I remember when we were going
through our initial forays with visual ORs and we had
the vendors set up and we were working with it, the
vendor, as good vendors do, they kept increasing and
enhancing the technology, and as we -- sometimes at
our request, because we're so big we can do that.
And as we get this technology advancement
we say okay, you know, you've betaed it, it's
working, we want to turn it on, and often we were
told, well, you know, it's not FDA approved yet.
Well, when is that going to happen? And, you know,
it takes awhile, and while we're waiting FDA
approval, we're not getting the benefit of already
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developed technology.
In fact, I can remember the example with
digital alarm, that the vendor told us we have it but
we're not submitting it yet to the FDA because the
process takes awhile and, you know, there's a certain
amount of effort. So we have to get -- we wait until
we have a certain amount of enhancements all stacked
up before we even submit them. And this, you know,
of course keeps us and the physicians from having the
technology that was developed for them to benefit
them and we're kind of in line. So I guess that
would be my one message while I'm here in the lion's
den talking about the speed of which things that are
submitted get through the process. And a very short
summary. We need minimum requirements defined
between the suppliers and FDA. And after that, we'll
take care of the rest.
(Laughter.)
MR. GEE: Well, I'm going to sort of
leverage off the presentation that was just given,
although I have a somewhat different point of view.
As opposed to being over-regulated, I think maybe
we're a little under-regulated.
So this is how medical device systems are
created. It's how the requirements are gathered.
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It's how they're specified and designed. It's how
they're approved or cleared by the FDA. And this is
how they're used in the real world. A big
difference. A huge difference.
Now, I would imagine that the majority of
those systems that when they do get installed are
installed to specification of the system that was
cleared by the FDA and you know, everything's kosher
in that respect. But certainly over time, I would
bet every one of those systems gets way off the
reservation.
So there's four issues, problems, that
could be addressed. One is particularly -- and I'm
speaking mainly on the networking side of things as
opposed to up at the application layer. Networking
standards, we've got a lot of great networking
standards. We don't need more networking standards.
We just need to better use the ones we have. And
right now there's so much flexibility, you could have
a range of variation in standards, configurations,
and profiles that are adopted and insisted on by
hospitals around the world that is huge.
There's really no reason why we can't take
that variability and narrow it down substantially so
that medical device manufacturers, who are not
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networking rocket scientists -- I mean, let's sort of
admit that -- can have a much reduced scope of things
that they need to do so that they can make a medical
device that's a reasonable network appliance, because
that's what they are becoming, in a way that is
consistent and presents fewer variables for
everybody.
The other thing that networks need is some
kind of framework within which to do coexistence on
the network. If you go out and you buy medical
device systems from CareFusion and Hospira and GE,
Philips, Welch Allyn, and you try to put them all on
the same network, it won't work. How are they
supposed to solve that problem, though? I mean,
they're all -- many of them are direct competitors.
They can't sort of meet in the back room without
raising FDA -- not FDA, but antitrust issues. There
used to be a framework so that that can occur in a
way that they don't have to worry about disclosing
proprietary information and don't have to worry about
antitrust issues. They also need a framework for
test and certification to be able to support
networking infrastructure beyond the vendor that they
had installed in the lab when they developed their
product.
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Let me know. How many people are aware of
a vendor that does more than -- supports more than
one wireless infrastructure vendor with their system?
Anybody? Okay, there is one company. It's
represented here today. Draeger supports four --
five?
MR. FUCHS: Four.
MR. GEE: Four wireless infrastructure
vendors. They're the only ones in the industry. And
so, you know, you go into a hospital, and they base a
decision on clinical requirements for a system that
requires one network infrastructure vendor. Hospital
IT says no, no, we use another vendor's
infrastructure, and all of a sudden you've got a
problem.
So what we need is some kind of test and
certification mechanism so that when I release a new
wireless patient monitor, it not only supports the
manufacturer that I had in my lab, but it supports,
you know, three, four, five others as well. And one
of the wrinkles here is that that test and
certification needs to be more than just a weekend
plug-fest in a hotel ballroom. It needs to be
something that conforms to the FDA's quality system
regulation because they're medical devices. And if
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you don't do that, then you just force the
manufacturer to redo all that testing themselves
anyways, and the plug-fest ends up being a waste of
time.
And everybody in the industry needs a
framework to ensure the safe and effective creation,
maintenance, and evolution of these systems in the
real world. There's a huge sustaining engineering
burden here, not just as network infrastructure
manufacturers upgrade their firmware or replace a
router with a new router or change to the next
generation of wi-fi infrastructure. It's also the
servers and the operating systems as well as the
medical device systems, although they tend to change
a lot more slowly.
So to propose some solutions here, just to
spark a little conversation, from a provider
perspective, the IEC80001 is a great start. But, you
know, hospitals need to do a lot more than risk
management. They need to have a whole framework of
policies and procedures to manage change, to be able
to first capture all the requirements and
specifications for all the different medical device
systems that they're supporting, and then be able to
keep all of that straight and make sure that
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everything they do is in conformance. And then, when
the product that they need for conformance is no
longer available from a manufacturer, they can go
through an appropriate process of risk analysis and
testing to find a replacement component that still
results in a safe and effective medical device
system.
Common network designs and configuration
profiles, I mentioned that earlier. If the industry
could sort of get together and say instead of we're
going to support this much variability, let's support
this much variability, it'll be easier for everybody.
Wouldn't it be great if we could test and certify
provider networks so that the hospital would always
know that, you know, we're in conformance with this
profile? A manufacturer that wants to come in and
sell a system knows they're in conformance with that
profile, and it makes the whole process of getting
the technology, implementing it quickly, and being
able to benefit from it that much easier.
On the manufacturer side, we need a
framework for doing test and certification for the
network medical devices, both coexistence as well as
supporting, you know, multiple infrastructure
manufacturers' products. And then we need this
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framework to be extendable so that we can provide
ongoing support for, you know, the constant changes
that occur in all of these off-the-shelf technologies
that we use.
You know, there's a certain amount of
sustaining engineering that has to be done depending
on what a risk analysis shows has changed, and it can
be substantial or it can be lightweight, but you have
to go through that process to figure out what it is
and then do it. And to expect every hospital to do
that on their own, and every manufacturer to do that
on their own, it's crazy, it's inefficient. We've
got better things to spend our money on, like cool
clinical features that will save lives.
So how do you come up with these
frameworks? How do you make all of these decisions?
Well, here's a graph showing the usual suspects.
Okay, we've got the FDA, we've got the IHE, ISOs or
SDOs, like HL7, DICOM, 11073, Continua trade groups
and then some other thing. And these are the
criteria for our market, which, I should say I'm
speaking sort of hypothetically from the acute care
market. The ambulatory market already has a group
called Continua Health Alliance that pretty much does
much of this, although in a different way. But
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you've got to have acute care expertise, be able to
develop and support network profiles, do the vendor
test and certification, provider test and
certification.
IEC80001 is more of an implementation
thing. You get a great standard, but you know, it's
a great process. But some hospitals, without
guidance, will create really great risk analysis and
others will create really poor risk analysis. So
there needs to be some guidance. And then QSR
compliance, familiarity and ability to deliver on
that.
And as you can see, there's really not any
group that we can sort of take this to and dump it on
their lap and say, here, fix this. Probably the
trade groups can do a lot of it. Certainly the nice
thing about a trade group or a consortium or an
industry -- I'm sorry -- a trade group like HIMSS or
AMI (ph.) or the ACCE is that they can work directly
with their members to create network profiles and
things like that, help educate them on IEC80001,
participate in the development and expansion of 80001
beyond risk management. So some food for thought.
MR. ROBKIN: Thank you, Tim.
(Applause.)
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MR. ROBKIN: So I'd like to start off with
some questions from the audience.
UNIDENTIFIED SPEAKER: Yeah, I'd like to
address the comments of our last speaker. It occurs
to me that you described Boeing, the systems
integrator. I don't know whether you're putting
forward that as a business model, but it occurs to me
that, now using the aviation example, we've just
plopped down and said, okay, airlines and components
manufacturers, avionics manufacturers, you've all got
to do it this way. And I don't think the FDA is in a
position to be a Boeing.
UNIDENTIFIED SPEAKER: Why is it us? Why
don't we let Boeing do it?
MR. GEE: Yeah, actually, I've had a
similar discussion with -- was it you, Sandy? I
think it was -- about, you know, it's the FAA that,
you know, certifies airframes, and it's the FDA that
is more about process. And what I think we need as
an industry is not so much somebody to tell us how to
do things but an organizational structure for us to
figure out what to do.
UNIDENTIFIED SPEAKER: And, Tim, this gets
back to the discussion of the last panel actually,
and I'll refer back to the analogy that was used
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relative to the defense industry, that gentleman over
here, relative to the quality of service, and
requirements are often quality of service. In
defense systems, like these large-scale defense
systems, one solution with a quality-of-service
problem is simple: supply it. In other words, as
opposed to living off of AT&T or Verizon, pick your
poison, essentially you have your own certified
network that you certify.
In the situation that was described in the
last panel -- and I think that is really reflected in
where things are moving with 80001 -- the challenge
is related to, well, where do you certify? You know,
you can't -- unless you control the network, unless
you control the entire environment, how do you
certify the entire environment?
You might specify quality-of-service
minimum requirements in order to achieve -- you can't
participate unless you achieve certain minimum
requirements. Then I'll wait for the torches and the
tar and feathering out in the hall after I make that
statement. But the point is, is that unless you
control the end-to-end, how do you assure that you
achieve the high quality you need?
And the fact is we don't control it. We
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control one aspect of it. We control either the
devices or we control communication to the devices
immediately. But in terms of some of the scenarios
that were described previously which -- well, you
didn't have connection unless you walk near the
window, as an example, or didn't have a connection
unless you turned around and patted your head three
times.
These types of challenges are going to
proliferate throughout the entire interoperability
environment, unless something is done relative to the
end-to-end problem. And it's more than -- obviously,
when you exit the enterprise, that's where one area
you run into a problem.
Several years ago intra-enterprise
communication was a problem, and I think that -- you
can think of it even that it's sort of kind of going
the way of the dodo. But even so, in order to
achieve effective home health now, one might take the
model from the AT&Ts of the world or the Brinks, so I
guess the quality-of-use securities are the 911
security dispatchers.
But even there you're not guaranteeing the
service. The services, if given that direction to
supply the connection to get through, you will get a
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response. The challenge seems to be and continues to
be guaranteeing the service required to ensure that
you can rely on these systems for intervention, which
I think is really key from the safety perspective.
MR. ROBKIN: Let me redirect that question
or comment back to Kaiser. Do you guys want to talk
about what it would take to certify the enterprise
network and maybe how you would feel about giving up
network functionality for medical device
interoperability?
MR. McGRANE: You know, I would say -- you
know, I guess the word standardize or certify. But
when I hear certify, what comes to mind to me is, you
know, recertify and recertify, and it really does
take away from the ability to be nimble and the mash-
up factor goes away. If the guy using the iZipcar
had to, you know, wait for AT&T or somebody to
recertify something for that occasion, he wouldn't
have been able to do it.
So I think there needs to be, in areas
where the -- and there is areas, of course, where
certification is key is, you know, patient safety
here. But in areas of network protocol and things
like that, like I focus on, I think standards-based
common interfaces, that's all good. But to the
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degree that we need certification, you know, there's
just too many moving parts. We'd be stuck. We'd be
frozen.
MR. GEE: In looking at this issue outside
of the hospital, where you don't control the network
and you don't control a lot of these things, I think
a lot of it comes down to how you do your risk
management and how you design your solution and how
you mitigate those risks that you've identified.
Obviously if you can't mitigate those risks that
you've identified in a way that created a product
that's safe and effective, then it should never have
been cleared by the FDA until the technology's
available to do that.
MR. ROBKIN: Question?
MR. MADDALI: Mahesh Maddali, Boston
Scientific. Just an off-the-cuff comment here.
We've talked about the ownership of assuring safety
of medical devices on the hospital institution
infrastructure. Again, you know, the diagram, Tim,
that you showed up there, where it's completely
broken apart, what's the regulation on that?
I mean, sometimes I think if you sort of
start asking yourself how does that end certified --
I'll use the word tested or whatever. Maybe that'll
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start forcing a discussion like the Boeing, the
aggregate, where the FAA is talking to Boeing as to
this is how we want this done. And that's forcing
common standardized processes on all the sub-
suppliers and sub-vendors. Maybe if it comes through
the hospital side, on the back-end infrastructure or
anything like that, maybe that'll also foster some
kind of commonized standards.
UNIDENTIFIED SPEAKER: Well, the FDA
doesn't regulate that. It's the practice of
medicine.
MR. MADDALI: I realize. I know the FDA --
that's just a quick off-the-cuff.
MR. ROBKIN: There wasn't anything as close
to what you're talking about. The proposed MDDS rule
came out from the FDA, which touches on some of those
topics.
Rick, you had a question?
MR. SCHRENKER: Yeah. Tim, the first
thing, I thought that you hit a lot of nails right on
the head from a provider standpoint and from an
engineering perspective. I found the statement going
beyond 80001 sort of interesting, and do you -- are
you willing to -- do you have any ideas on expansion
beyond risk management that you'd be willing to
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mention?
MR. GEE: Yeah. I just finished a project
for a hospital, creating a framework of standard
operating procedures and control documents that -- to
provide the framework for dealing with multiple
medical device systems on their shared network
infrastructure and EMR integration and all of that.
And when I was done and looked back it, it's almost a
mini QSR for hospitals.
You know, you come up with your goals or
your intended use, and you do a risk analysis like in
80001, as it's currently drafted, and you go ahead
and implement and test that, which isn't an 80001 but
could be in, you know, 80001-2012. And then you have
the sustaining engineering piece, where you track
those things as they change over time and manage
that.
UNIDENTIFIED SPEAKER: It's called
corrective and preventive action.
MR. ROBKIN: Okay.
UNIDENTIFIED SPEAKER: I have a question
from the telephone.
MR. ROBKIN: Go ahead.
UNIDENTIFIED SPEAKER: This is directed
toward Tim Gee. Brian Shoemaker wants to know what
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the possibility, at least for hospital network type
of situations, of establishing one or more physical
centers with actual network setups and various
devices for honest-to-gosh testing, certification of
devices in a hospital-type environment.
MR. GEE: One of the SOPs that I developed
dealt with creating a lab because you have to have a
test lab just like manufacturers do. If you're a
hospital and you have these systems on your network,
you have to have the facility to be able to test
those changes before you roll them out into
production. And actually that's one of the big
challenges because if you're an organization like
Kaiser, how do you take a little office somewhere and
create a lab that actually is a reasonable
representation of their huge enterprise network? But
it's clearly a requirement. You probably could speak
to that.
MR. McGRANE: Yeah. So we've done that.
Dr. Grey mentioned our Garfield Center, which is a
large building that we mocked up to look like a
regular clinic or a hospital floor, and there's
patient beds, there's telephones that they would
have, the whole room environment, the nurse call
stations. So we emulate that because we have -- you
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know, we definitely do not want to be taking these
new systems in the hospitals and, you know, road
testing them live and with real patients in real
settings.
So we've emulated it, and it actually comes
down to you can only go so far. At the end of the
day, you know, you can simulate as best you want, but
until you actually take it out and go into the real
hospital and do it, I mean, you're still going to
learn some lessons.
But we found that with this mockup
hospital, we're able to catch a lot of the stuff we
otherwise would've missed. You know, from a wireless
network, we can emulate not only a clinical setting
but the network they would be participating in. And
as the EKG things roll around, we can kind of learn
stuff about some of the challenges we come across.
MR. ROBKIN: Okay, I think we have time for
one or hopefully two more questions.
MR. ARMANDEL: Hello, I'm Dave Armandel
(ph.). One of the options that we have here, I
think, in the standards is, certainly on a network
like that, you can actually have some automated
tests. It's always looking at the network and always
looking at protocols, and so you can always make sure
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the device is working properly.
And so we can have it whether it be self-
tests, whether it be where it's running all the time,
the automated, in an automatic fashion. And clearly
that's not going to catch all escapes, but certainly
you can catch quite a few of the escapes in doing
that, as opposed to a system that once you deploy it,
you don't test it but every now and then. Okay, once
a year or once every six months. Just like we're
looking at. The tape is monitoring for individuals.
With healthcare, certainly in the hospital, you could
implement something similar.
MR. ROBKIN: Yeah, the challenge there
would be to have some sort of test or certification
that covers a significant portion of the risks
because what most enterprises do is they have some
little offices, a few tests for solving the last
problem, but nothing comprehensive.
MR. ARMANDEL: Well, I think that's what's
interesting here to me because I think we have an
opportunity to be starting to look at what needs to
be placed in devices, et cetera, to be on the
network -- easily, but certainly I don't know if the
scheme of that would actually help ensure that you
could do the testing. In other words, if you don't
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design the test then, okay, then -- test it. Then
you're clearly not going to have folks to make sure
it's --
MR. ROBKIN: One last question.
DR. BAKER: Yeah, listening to this
discussion, I thought I'd reflect that as part of the
empire of NHS Connecting for Health, we have a
network called the National Integration Center, which
definitely tests systems that wish to connect up to
the spine, the NHS spine, and that's what it's been
doing so far.
It's branched out into -- we now have
something that's called -- and that's more like for
the design and feeding back things, and it's looking
at them and is kicking it back. Then, like you
said -- however, it strikes me that there may well be
a development function there for that structure and
to do at least some of the communication processes
that have been discussed. And it would, however, be
leading into a whole new area, and I'm thinking we
can probably do this in a national way, but is it
possible to do it in the many scales below that?
MR. ROBKIN: Thank you. A good point.
We're going to take a break now. Come back in 10
minutes to the hour. If you're missing -- if you'd
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like a summary sheet with some issues to write down
or a summary of the upcoming presentations, they're
on the table here. So 20 minutes. Thank you.
(Off the record.)
(On the record.)
DR. GOLDMAN: Ladies and gentlemen, first
we have a warm hello to all of you out in web land.
I don't know what to say to web land. I don't know.
I don't know if there is a web land, but kind of
there's a TV land.
There is a sign-up sheet that was outside
and will be circulated for the ride share to return.
So you'll see it. It's pretty clear. You indicate
whether you have extra seats in your vehicle and/or
you indicate if you'd like to ride with someone, if
they have it, so -- and we'll see how that works out.
Again, there is a shuttle bus at five o'clock, but
we're not sure how long it will take for the
roundtrips for the shuttle bus, given the traffic,
and we thought we'd, you know, maximize the ride
sharing.
This next session is our Session Number 3,
Systems-of-Systems. As Brian says, you can say that
again.
UNIDENTIFIED SPEAKER: Say it again.
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DR. GOLDMAN: Systems-of-Systems.
UNIDENTIFIED SPEAKER: Loudly, so the
people outside can hear.
DR. GOLDMAN: No, I can't be that loud.
And in this session, we have three people on the
panel. We have Dr. Frank Block, who's going to talk
about systems-of-systems issues and will present a
scenario that will be the starting-off point for the
rest of the work. Then Dick Moberg will talk about
using standard communications protocols to implement
medical device plug-and-play. And George Samaras
will talk about wrangling the human element of
interoperability, defending against Reason's latent
flaws and Dekker's drift.
DR. SAMARAS: Thank you, Julian.
DR. GOLDMAN: And with that title we're
expecting a lot. I'm going to just take a moment,
and then I'm going to sit down and the panel's going
to run on its own for a while.
Dr. Block is from VCU. Dr. Block is an
anesthesiologist and also a world-renown technology
expert in monitoring and clinical technologies and
things of that sort. And Dick Moberg has been
working on medical devices for a long, long, long
time. We know each other a long time. Dick has been
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working on an implementation, a standards-based
implementation of IEEE 11073 classic, in his company
and on some research work under STTR, and it's been
really very helpful to have his perspective of
implementation.
And then George Samaras, I guess, this is
his old home. He used to work at the FDA and now
works to facilitate other companies' research and
activities in regulatory and other engineering areas.
I don't really understand a whole lot more about what
he does. It's all very mysterious to me. But with
that, let me hand it over to Frank to start with the
scenario.
DR. BLOCK: Thank you, Julian. My voice is
still trying to give out, so bear with me.
Everything's on the slides. So if you can't hear me,
it's actually okay. I think Julian actually covered
everything pretty well. I'm going to give you a
clinical vignette that has several issues tucked away
in it.
We have a burn patient in ICU Room 1. The
patient is connected to a multi-parameter monitor, or
MPM, that monitors blood pressure, EKG, pulse
oximetry, and so on. The patient is admitted to the
multi-parameter monitor with a name and medical
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record number, and the MPM is both connected to a
central monitoring station and also to several
bedside devices. Pretty typical ICU setup. The
bedside devices for this patient are a standalone
cardiac output monitor, an electronic bed scale, an
electronic urine output monitor, and an infusion pump
with a closed loop controller.
Everything is fine. The data from the MPM
and the beside devices are recorded and trended on
the MPM and also at the central station. In fact,
this system has been working very well for several
months. They've had a recent software upgrade, and
today the system worked fine for several hours and
then the caregiver noticed that the MPM has stopped
communicating with the bedside devices.
The infusion pump is continuing to infuse
at the most recent rate. The other bedside devices
are working, but they're just not talking to the MPM.
The old trend data are still available both at the
MPM and the central station.
So the caregiver tries to do a little
troubleshooting, and they turn the bedside devices
off and back on and they unplug and re-plug each
bedside device, and then they unplug all of the
bedside devices at the same time and plug them back
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in one at a time and it's still not working.
There's only one other MPM available in
this particular ICU that isn't connected to a
patient, and that's next door in ICU Room 2, and it
happens to be made by a different company. So the
caregiver moves the MPM from Room 2 to Room 1 and
connects it to the patient while the first MPM is
still connected. That's the way you do it so you
don't lose any monitoring.
And so they unplug all of the bedside
devices from the old MPM and connect it to the new
MPM, and now they're all working again. And now the
old MPM, just in time, has stopped working entirely;
it is completely dead. So the trends that were
available on the MPM are no longer there. They're
not on the new MPM. The old trend data from the
bedside devices is not reloaded onto the MPM.
So the caregiver tries to admit the patient
on the new MPM and gets an error message that says
that the patient is already admitted because, of
course, the patient was already admitted on the old
MPM and the normal procedure would be that you would
discharge the patient from the old MPM first, which
is a great idea except the old MPM is now completely
dead and there's no way to do that.
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Meanwhile, at the central station, the
central station still thinks that the new MPM is
located in ICU Room 2 and the patient data are being
displayed in the wrong location at the central. The
central station also thinks that all of the bedside
devices have been moved from ICU Room 1 to ICU Room 2
because they're now connected to the monitor that it
thinks is in Room 2. And of course that means that
they're no longer connected to the patient in Room 1.
So the nurse manager goes to the MPM to try
to configure its new location, and of course the
clever designers have determined that it won't take a
new location while a patient is connected to it. So
that doesn't work either. So the caregiver has an
idea. They use the admit function to enter a patient
with the same name and a different medical record
number, and now the system is happy, and now the data
are being trended, but the central station, of
course, thinks that there are two patients. And the
old trend data on the central station cannot be
downloaded to the new MPM, and the hospital medical
records office will soon be screaming as soon as they
figure out what they have done.
So here is a rather chaotic scenario that
has dozens of issues that are contained in it. I
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wish I could tell you that this wasn't a pretty true
scenario, but unfortunately it is all too true. And
the next presentations will focus on just a couple of
these issues, and I hope we'll have some time in some
of the later discussion periods to talk about some
more of the issues. Thank you very much.
(Applause.)
MR. MOBERG: So my job was to look through
Frank's scenario, and when we first talked, I was
supposed to go over the engineering issues and tell
everybody in eight minutes how we're going to solve
them, and obviously I didn't get very far. So let's
go back through a couple of these things. So here we
are, if you remember the scenario. So we've gotten
one. There's another one in a different room, made
by another company, right? And then we unplug all of
the devices. We connect them all to the new MPM made
by another manufacturer, and they're now all working
again. Well, that's as far as I got because, wow,
how did that happen? You know, it's like we've been
working for 10 years to make this happen.
(Laughter.)
MR. MOBERG: And it wasn't even a problem
for Frank.
(Laughter.)
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MR. MOBERG: So actually what we're doing
is really trying to make this work, and so I wanted
to focus a little on that and, you know, tell you of
the laundry list of problems that we found just
making this happen. I didn't get anywhere else in
your scenario.
So what we're trying to do then is, you
know, let's say on the right is this multi-parameter
monitor and we have -- and I work in the neuro area,
so these devices are going to be more neuro oriented.
So on the left we have two devices that we want to
plug in here, and the idea is that we want to take
those same devices and plug them into another multi-
parameter monitor made by another manufacturer.
Well, right now we have to do that with proprietary
drivers, and there a lot of companies in here
working, including ourselves, making drivers for all
of these different devices so they'll all plug into
our specific sort of data collection and multi-
parameter monitors, as Frank said. So obviously, you
know, that's sort of tedious, and this is just the
procedure we go through at our company for a new
device to be added.
And we're an FDA-regulated company, so we
started doing a device definition document. We
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negotiate with the manufacturer to get their
protocol. You know, you can see all the steps down
there. We write a driver. We then try to beg,
borrow, or steal a device to test it and all this
stuff.
These are the particular areas in red here
that are very specific to our device. So every
device we interface, we're doing some stuff that's
sort of standards oriented, some stuff that by
definition has to be specific to our data collection
system, the way we display it and all that.
Well, what we would like to do is get away
from all of this, and this is sort of what's going to
open up this -- and I'm preaching to the choir here
to some extent, but what we need then is a standard
protocol of the device and sort of standard receiver
on the receiving end, and then the plug-and-play
works, right? But as we all know, these are legacy
devices, so we need adapters in there that translate
the legacy protocol into the standard protocol and
then this will work.
So what I want to do is show you -- here's
what we've been doing. So we make a product, the one
thing on the right, and basically you could think of
it as, you know, most vital signs monitors now do
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hemodynamics, and they work from the neck down.
Well, we're just basically using the same concept but
from the neck up, and that feels about 30 years
behind hemodynamic monitoring because everything is
in little discrete boxes all over the ICU. None of
them talk to each other. They all need to be sucked
into a central sort of display, and that's sort of
what we do. So this device just came out.
But what we're trying to do now is, you
know, we hooked up with Julian after many years of
knowing him, but then got involved with ICE about
three or four years ago and got some funding from
TATRC and a little bit from the NIH. So we're taking
our propriety device, and we're migrating it into --
we're taking the components out and migrating it into
an ICE-based system, and we're learning a lot in the
process, and that's what I wanted to share a little
bit with you.
So we're building adapters to hook the
devices in. We're building sort of a data aggregator
for the network controller and adding functions like
decision support and stuff on the supervisors. So
here are the adapters. We're looking at -- I took
the 11073, and we're coming up with some designs for
these. We prototyped them, and you can see what's
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sort of attached up at the top there.
This is a demonstration we did at TATRC
last summer, where on the left you can see our -- we
actually took three devices, and we hooked them
together and made little adapters and they were
all -- so that's a little adapter right there, and
then they all go over here, and all the data from
these devices are all, you know, talking 11073 and
display over here on one device, right? And I don't
know who that guy on the right would be.
I just want to go through a few issues. I
just have three issues. One is that we found out is
that -- is we concluded that compliance to the
standard does not guarantee consistency of
implementation. So in 11073, there's a lot of room
for wiggle in there. There's scanner objects.
There's these object IDs and private object IDs and
all this stuff. And unless company one and company
two deal with those the same way, you know, they're
doing this, you have some -- you could have some
potential problems there with sending the data over.
So compliance to sort of the standard of how we all
implement that is one of the issues.
The other one that's come up in our field
is time synchronization. So we have to get all of
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this data together time-synchronized. Now 11073
handles that actually quite nicely. But in neuro,
there are a couple of examples where you really need
to synchronize things very tightly, and one of the
issues is looking at bringing out a regulation, and
there's a lot of research work going on by just
looking at things like mean or total pressure and ICP
and closely synchronizing those, but they have to be
synchronized tightly, and what we need is a way to
send that, the accuracy of this synchronization,
over. So how granular is your data is another thing.
And then another thing is if we are -- one
of the things that actually, I think, Julian turned
me on with part of the ICE thing is instead -- we
also, in addition to getting data over, we would also
like to be able to manage devices, right? So if
we're going to get all of this data in one place, why
not, you know, give something to the biomeds to be
able to go back and find out what version of software
was used to collect that data from that patient for
quality issues and things like that, and where is
that device?
So we would like to be able to put sort of
metadata from the devices on these -- you know, on
these adapters, tie that adapter to a specific
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device, and then send that over along -- you know,
along with our sort of, you know, data collection
thing. That assumes that this adapter is always
going to be associated with this device, right?
And so the whole device association thing
comes up with our adapter. So how do we build
something into the adapter that allows us to
associate it with a particular device and a
particular software version? That's a tough problem.
We haven't really figured it out yet. We're waiting
for the FDA's unique device identifier to come out,
and I might be dead before that, but I'm not sure.
I'm trying to hold on.
(Laughter.)
MR. MOBERG: So that's another thing that
we've -- and it actually goes back to some of Frank's
scenario of being able to associate devices with
rooms and all of that. So it's a very similar
problem.
So just to keep this short, I just have
some suggestions. One is, in the exercises we've
done, it seems to me that we probably are going to --
we're going to need a lot more than a standard and
probably we've come to have something like an ICE
best practices. So if you're going to implement
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this, it might be good to have some guidance from
that and also guidance from maybe professional
organizations, FDA and so forth.
And then the second part of that is we
probably want to have some way to do third-party
testing of either adapters or the communications and
all of that. And it's been nice at this meeting.
I've met some of the people from NIST, and I think
they're doing a great job of developing some testing
tools and everything and then probably have those
third-party agencies that manufacturers go to to test
their devices. So I think something like that might
work. And that's all I have to say. Thank you.
(Applause.)
DR. SAMARAS: I'm going to try to follow on
with Frank's vignette. I'm going to take a small
piece of it. The scenario is fictitious, but what
actually happened is not a fiction; it's just been
masked. If any of you in the room actually recognize
what I'm talking about, please don't blurt it out.
But basically the cascade of events actually
occurred, and this is just to illustrate the problem.
The clinical scenario is that we have a patient being
infused for volume management. He's a burn patient.
We have some programmable intelligence. We have some
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sensors, some Ringer saline going in. And this
system of systems actually worked fine, and then it
didn't, and it was not readily obvious why it didn't.
Here's kind of a diagram of the case
scenario. We have both the regulator, the healthcare
facility, and the two manufacturers. Manufacturer
Number 1, or N, actually built the infusing device
and one of the inputs -- this is not actually what
happened, but I'm trying to translate into what --
into a similar set of circumstances. One of the
inputs was not guarded. However, the manufacturer of
the programmed intelligence had guarded both their
inputs and outputs and therefore there was no obvious
problem. The latent flaw that was caused -- that
existed in this system didn't show up.
UNIDENTIFIED SPEAKER: George, use the
mouse to move around because the folks on this side
can't see your pointer.
DR. SAMARAS: Oh, I'm sorry, I'm sorry.
Okay. So the folks at the FDA reviewed both of these
systems, and they cleared them, as you would expect
they would, and the initial user at the healthcare
facility tried out the system. You had to put all
the pieces together and it worked fine.
And what we don't show in here, though --
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Frank tipped our hand here -- is that between this
point in here, a remote software upgrade was sent to
one of the two units, actually to the programmed
intelligence unit. And in that instance this new
employee at Manufacturer N missed guarding one of his
outputs because it wasn't in the requirements. It
wasn't spelled out as part of a requirement.
And so a new clinician comes along -- I've
lost my mouse -- and this last user sets it up and
sets up a set of parameters in such a way that it
hadn't been used that way before and the system
failed. And as Frank kind of implied, they turned it
off, they turned it back on again, they played games
with it, and it wasn't obvious what had happened.
And by the way, during the same time,
the -- I'm sorry. Let me back up here. The
inspectors at the district office had also inspected
both of these manufacturers, and they both found --
they were found that they were compliant and no real
problems.
So before I tell you more details about
what actually occurred and why it occurred, who do we
blame? If we blame the reviewers, you can watch
administrative clearances grind to a halt. The
inspectors are not trained or resourced to detect
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what it is that we're going to ultimately understand.
The initial user, they put it together and it worked
just fine. The last user, as far as we understand,
they used it per the various manufacturers'
instructions. Manufacturer N, maybe, maybe not.
Manufacturer M, the first engineer did everything
right. The second engineer did what he thought was
correct, did his job the way he understood it.
The point that I want to make is that this
is and will always be a systemic failure. The
component failures, the particular incidents that
happened or what device actually failed, they're
merely symptoms, and until you deal with the
underlying disease, you will not be able to get the
rid of the symptoms.
Okay, let's talk about a couple of human
factors issues that will lead us to why I believe it
happened. First of all, there are two types of
errors that humans make. There are user errors,
where the locus of control is the actually healthcare
provider, the user, the engineer, whatever, and those
have to do with expertise, memory, workload, and
behavior.
But then there's another category of errors
that are called use errors, and there the locus of
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control is not the individual using the device on a
system but in fact is the way the system was
configured and developed. And this kind of looks
like the quality system regulation because it is.
Management controls, risk management, design
controls, document record and change controls impact
how the device is actually physically realized and
how it then interacts with the user. The user not
only interacts with the device but the device
interacts with the user.
There are two classes of errors that
developers or manufacturers can make. There are
propagated errors, and those are, you know, you make
a mistake in a needs analysis. You then have a hole
in your design requirements. You then have a hole in
your specification, your design specifications. You
realize the device. Physically you make it, in other
words. And you've got a problem, but you can detect
that problem with engineering validation. Compounded
errors are a different problem, and they actually
show the limitations of engineering validation, which
doesn't get talked about much.
The first kind are after James Reason --
he's a professor at Manchester University, I guess is
where it is. He wrote a book in 1990 called Human
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Error. And basically what happens is he pointed out
that you can make a mistake in your needs analysis,
miss a design input, a requirement, and not notice it
because you always do your specifications a certain
way and so it masks it.
As a result, this green arrow down here is
what we call a latent flaw and will not appear until
there is a change in the specifications for some
unknown reason. You know, you buy a part from
another supplier, you have an engineer that makes a
change because he knows this is a better way to do
it, and all of a sudden this latent flaw unexpectedly
and suddenly becomes an unanticipated failure.
The second type is after Sidney Dekker and
he wrote an interesting book -- and I have the
references on my last slide -- called Ten Questions
About Human Error. And in this case it's like the
latent flaw but it propagates through to the
specifications, and then because of the way we build
stuff, we routinely manufacture stuff, it gets masked
and then it doesn't show up for quite a long time.
And he is in the aerospace and aeronautics
business of human error, so he was talking about how
variations in maintenance of an aircraft led to
basically it crashing and killing a whole bunch of
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people. But the concept is generalizable to any kind
of engineering system.
Now, I would argue that the reason that the
two manufacturers ran into this problem, which was
then recognized or landed on the healthcare provider,
is that they had two disjoint development lifecycles,
which are iterative. This is basically an example of
classic systems engineering done in the '20s, '30s,
one of the first agile methods. Actually, it's not
generally recognized that way. But what happens is,
rather than following a waterfall procedure, the most
effective way is to keep cycling through these.
And you saw at the beginning of that little
use case study that in fact both manufacturers kept
doing stuff, but they weren't interconnected. As a
result, because there were missed design inputs,
because there were defective or missing design
inputs, they propagated through to create a problem
when the device was released.
Now, I'd like to offer an opinion as to why
I think design controls, which are central to the
quality system regulation, not only didn't work but
cannot work. What happens is verifications occur.
You know, we get our marketing folks and human
factors folks to go out and identify who the
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stakeholders are and what their needs, wants, and
desires are, and from those we select a subset that
are economically and technically feasible, and that's
what we put into our box. And so those are the
requirements for the box.
And then the engineers take the
requirements, and their work product are the
specifications, the design outputs. And then the
manufacturing folks build those or prototype them,
and then they get -- at each step of the way we're
verifying that the specs match up to the
requirements, the requirements seem to match up to
the stakeholder needs, and then we finally do a
validation.
But we are validating against the design
inputs, against the requirements. If your
requirements are defective, if you did not properly
translate -- identify your stakeholders and properly
translate their needs, wants, and desires, there's no
way that you can get the correct set of requirements
and there's no method -- this is actually a diagram
of the quality system regulation and design control
regulation, 21 C.F.R. 820.30. There is no way that
you can figure out that you are missing a stakeholder
through validation or through verification.
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So the argument that I would make to you is
that the armamentarium that we have now works in
certain cases, but as we start to put together
multiple systems into larger integrated systems, we
are going to run into a new set of problems that are
going to need a new approach to dealing with it, both
within the company that's doing the development as
well as within the regulatory bodies.
So from my perspective, here is the
challenge. The failure loci -- was that one or two?
Or am I dumb? Two. Good. The failure loci were
people doing their jobs as they understood them. The
failure cause, as I read it, or defective design
inputs resulting in latent failures and drift, the
root causes were that lifecycle management, in other
words, from lust to dust, all the way until the user
facility throws the device into the can, that's the
full lifecycle. And if we back up here -- no, I
don't have it on that, actually. Forgive me. And
the regulatory emphasis was on marketing and
manufacturing, which from a precedent perspective,
that's fine. That's what the FDA has always done.
So the conundrum is everybody did their
job, but risk management, risk assessment, and
verification and validation weren't up to the job for
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catching it because both manufacturers did their jobs
correctly, did those procedures. The regulatory
challenge is that when you increase system
complexity, which will happen when you start having
interoperable devices because what is complexity but
merely more components, more pieces to interact with
each other and therefore to give you unanticipated or
unexpected behaviors, you're going to get an
increasing number of failures and a lot of bad PR.
My suggestion is that the regulator
consider shifting their emphasis from marketing and
manufacturing to lifecycle management. The reason I
say that is, for the most part, I mean, we do have
outliers in the industry, and we do have newbies
coming in, new firms, startups, but for the most
part, industry is mature. They know how to do all
the basic stuff, and they do it well.
For the regulators, it's a little more
difficult because regulating marketing and
manufacturing is easy. They've been doing it for the
past what, 20 years or whatever it's been since the
Bureau of Medical Devices was created. But lifecycle
management is a much more difficult problem.
The second possible solution -- and I think
these kind of need to be considered in concert -- is
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greater vigilance by medical device manufacturers
that are building interoperable devices, to worry
about what are latent flaws, what are drift, who are
our stakeholders? Now, our stakeholders are not only
the people that we're selling to, the people that
maintain the equipment, but also all those people
that we're going to have interface to.
And finally we need to improve the
understanding of the users, both physicians,
managers, engineers, and regulators, of complex
system failures, that is, not just one-point
failures, and also that there is a human factors
component that is of critical concern for each and
every one of the stakeholders. And here are those
recommending readings, James Reason, Sidney Dekker,
and Dismukes et al., which is an issue on limits of
expertise. Thank you.
(Applause.)
DR. GOLDMAN: Well, that was wonderful.
Let's open up the mike to questions. I've saved a
few for emergency reasons only. We'll see what comes
in from the audience. And who will tell us if
there's any web questions coming in? I'll guess
we'll find out.
MR. MURRAY: I spent about four years
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riding around in a submarine, and everything we did
and every system we owned had at least four levels of
backup. You started out with remote operation. If
that didn't work, you ran to the local switch. If
that didn't work, you ran right to the valve itself.
You needed to do it with hydraulic oil or compressed
air. And if all else failed, you took out your
wrench and operated the valve that way.
So my question is, I mean, is there
anything in this discussion about what kind of backup
systems do we put in place when we convert everything
to a computer-based society and it fails? Is that
involved with the risk management in this process?
In other words, do we put a backup system in place?
How do we address that? Because it seems to me, when
these systems go down, there's going to be no patient
treatment hand-delivered.
DR. SAMARAS: For the scenario that I gave
you, I think the problem was that your spanner didn't
open wide enough to turn the valve manually. And
that's where you got stuck.
MR. MURRAY: I mean, why don't they just go
in there and write the readings down manually instead
of relying on the remote?
DR. SAMARAS: At 60 beats per minute, do
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you mean?
DR. GOLDMAN: Frank, do you have --
DR. BLOCK: Well, I think we missed already
with the electronic medical records. We've beaten
our medical staff and many of them use these -- and
now when they go down, and they do go down, nobody
knows what to do. And so to think that people are
having trouble doing the normal procedures and
miraculously they're going to be able to perform some
sort of emergency backup procedures, I actually don't
have much hope for that, I'm sorry.
DR. SAMARAS: If they were under water and
were about to drown, they'd figure something out, but
they're not.
DR. GOLDMAN: So Tim? Tim Gee?
MR. GEE: Yeah, I'd like to ask the panel
of the kinds of issues that we run into every day,
what percentage of those are a result of just poor or
inadequate design and which -- and how much of it is
a result of just an insufficient regulatory
framework, as you suggested.
DR. GOLDMAN: Are those mutually exclusive?
MR. GEE: No.
DR. GOLDMAN: Okay.
DR. SAMARAS: In my experience, I've not
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run into poor or inadequate design or inadequate
regulation. If anything, I think we regulate too
much in areas that we don't need to regulate, and not
enough. My perspective is, is that you have
engineers who have a specific duty and a specific set
of training solving the wrong problems. And if you
can't give them -- pose for them the correct problem,
then why would you expect them to come up with the
correct solution?
DR. GOLDMAN: Frank?
DR. BLOCK: Well, I think there are some
significant design problems, the main one of which is
failure to understand the environment it will be used
in and the way the people will use it. And it may or
may not be what you had in mind. There's no
substitute for spending an unbelievable amount of
time in the clinical environment and seeing how
people are really using your equipment.
DR. GOLDMAN: So let me go through my
experience two weekends ago on call in the hospital.
I was working in some ORs and I heard -- I was too
busy, but I heard that on the same day in another OR,
they were unable to get the electronic medical record
to work. So they were using paper, a paper record,
which was amusing because it's been about six years
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since we've used paper in our institution and people
don't know how to use paper. We need a manual to use
paper. So there's a record missing all sorts of
data.
But I went into that room at 5:00 or
6:00 p.m. and, you know, I had a chance to hear more
about it and they told me that the touch screen input
wouldn't work, so they couldn't manually enter the
data that isn't acquired automatically, the non-
physiologic data couldn't be entered.
So I just took a quick look behind the
anesthesia machine, and I saw a coil of wire, a cable
that was underneath a wheel, and I saw that it was --
you know, because it was pulling on something, I
noticed that there was a connector that was partially
out, a USB connector halfway out on the back of the
anesthesia -- on the PC that's on the side of the
anesthesia machine, the PC that's used to host the
EMR.
And, of course, as you would expect, that
was the equivalent of the mouse input, which is what
the front of a touch screen uses. A touch screen has
a video input, and it has a mouse equivalent for the
touch screen, and that was partially out. And, you
know, people were too busy, busy with that patient's
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care and also weren't comfortable with the system to
look and see. So they had an entire day of a record
that's really missing a lot of data.
If this happened 10 years ago, it would've
been a more complete record, but now we've become
dependent upon -- on the electronic system, so people
are no longer adept at maintaining a paper record in
real time because it's actually -- it's a unique
skill. And so I looked at that and, anyway, it
was -- you know, once someone had the time to look at
it, it was a fairly trivial fix.
And I wonder, based upon the discussion we
just had, is the problem regulation? Is the problem
incorrect use of technology, connectors that, you
know, don't stay? There's no way to fasten that USB
connector in place. Is it the use of the incorrect
technology in the wrong environment? Or is it just
something that we have to live with? In any event,
it's a real problem.
At another time in another operating room,
I noticed the surgeon lost the video image in the
middle a laparoscopic procedure, and that was quite a
problem because everything goes dark. They have
sharp instruments in the patient's abdomen, and if
the patient starts to bleed, they can't see that the
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bleeding has started, and they can't stop it rapidly.
So when they get an image again, it may be too late
to stop the bleeding because they can't see -- they
can no longer see. So they would have to convert
from laparoscopic to an open procedure.
And what happened, in fact, was the same
thing, an analogous thing, a USB connector slipped
off the back of a PC that was inside a mobile case,
and it took someone who knew the system very well to
quickly run into the OR, and he knew exactly where to
look and he addressed it.
So I'd like to toss that out, those
scenarios, out to the panel and say, well, what's the
category? What should we do about it?
MR. ZAKIAN: I have an answer for that.
DR. GOLDMAN: An answer comes from -- yes.
MR. ZAKIAN: It's very interesting that, in
the healthcare environment, we're always monitoring
patients but we never monitor our systems to that
degree. And that's where the failures are. The
failures are in not having systems that are being
monitored and self-healing systems and the quality of
that system.
For instance, you know, a USB cable, a USB
connector coming off a PC, if you had a proper
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monitor looking at that PC and what that PC was
doing, it would tell you on the screen that your USB
port -- your USB connector is disconnected.
Or, in the same token, it should be able to
tell you whether the data that's going out to the EMR
is going out or not. And that's what really lacks
here. It's a monitoring of the systems that are
monitoring the patient.
DR. GOLDMAN: So part of it is system
health or system diagnostics.
MR. ZAKIAN: Absolutely.
DR. GOLDMAN: But part of it is should we
be using connectors like that for systems like this?
Are they appropriate?
DR. SAMARAS: If that was on John's
submarine, it would have a lock on it so that it
couldn't fall off. The problem is nobody asked for
the lock the way the military does. On the other
hand, the cost of everything -- if you've done
anything for the military, as I have, the cost
skyrockets.
DR. GOLDMAN: It doesn't have to be
titanium for a USB connector.
MR. MOBERG: So part of this -- so I think
Vaughan's point is correct, and I think John's point
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is a correct one as well. Twenty years ago, before I
had my life change and went into the medicine, I was
in the defense arena and we were doing design
relative to anything, you name it, military. We
involved captains, corpsmen, et cetera, in the
process of design. So they were involved in
essentially designing the use cases and actually in
designing the designs. So they actually were
involved in the actually detailed drawings and
designs of the systems.
It seems to me, what you're all speaking to
a degree is involvement in the clinical trials,
involvement of clinicians of all sorts, respiratory
therapy, nursing, et cetera, both in the use cases
and in the actually design of the technology and how
it's actually used as well. I don't think it
would've picked up Julian's specific case, but I
think Vaughan's point would have.
And I see sort of a dichotomy, a difference
here between the way we treat the design of --
although we do engage in clinical trials, in the
process of actually doing the designs themselves and
involving the clinicians at the point of care and the
process of actually looking under the hood at the
architectural drawings in doing a systems-of-systems
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architecture.
DR. SAMARAS: I have run into so many of my
clients who have -- my clients' engineers who have
said I'm constrained from changing what I built. I
have to build to the requirements that I'm given.
And if I don't build to those requirements, I'm going
to get in trouble. And if it's not in there, I don't
do it. Even if I think it's a smart idea, I may
suggest it, but by the time it goes all the way up
the chain and all the way back down, it's too late.
So I think the problem we have is we're so
used to dealing at the manufacturing and marketing
end of the stick that -- which is the blunt part.
Unfortunately there's another sharp end of the stick.
It's not when it goes to the doc, it's also when it's
poking the engineers who are trying to figure out
what they're supposed to do.
DR. GOLDMAN: Frank. And we have one more
question, then we have to stop.
DR. BLOCK: Yeah, I just wanted to mention
Charles Perrow's book Normal Accidents. I expect a
lot of you are familiar with that. He looks at
shipping disasters, Three Mile Island, the space
shuttle, and so on, and his basic thesis is that if
you have a system that is, number one, complex and,
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number two, tightly coupled, that accidents should
not really be considered accidents; they're basically
normal.
Just for a perspective, the human body and
the physiology of the human body and everyone sitting
in this room, just resting in your chair, not
connected to any medical devices, is incredibly
complex and incredibly tightly coupled. And even in
a very simple world of medicine, as soon as we start
doing things to that, it gets even more complex and
more tightly coupled, and as we get more and more
advanced technology and systems and interfaces and so
on, it's not getting simpler, it's not getting less
tightly coupled, it's going the other way.
UNIDENTIFIED SPEAKER: I just have a quick
question. The one thing that we've started to
concerns ourselves with, I guess, is addressing the
black box and making sure that the device you're
talking to or the system you're talking to is the one
you expect to be getting data from. We've been
focusing a lot on the data itself, but as things from
outside the hospital, outside the firewall, you can
start considering yourself really with the widget
itself that's actually taking the data. So in other
words, either the data comes over -- well, is the box
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you're actually talking to the one you expect? Do
you expect that to be an issue going forward?
DR. BLOCK: Well, I mean, there's no
substitute for an adequate front end, but I will
emphasize, for instance, when I talked about
automatic recordkeeping, the ability to hook these
devices up to your EMR, I always emphasize that all
of these devices that are recording the data, they do
not record patient data. That is a myth. They do
not record patient data. They record monitor data
and device data. Those data may be right, those data
may be wrong.
In that sense, it's just like a video
camera pointing at the box, and it records the
numbers that you saw. And so you need to have that
healthy skepticism as to whether the numbers coming
out of the box are right or wrong, and if they are
wrong, how do you get into mischief when they are
wrong?
DR. GOLDMAN: Thank you. I think that was
the last question, but we have one from the ether.
UNIDENTIFIED SPEAKER: Yes, from
Brian Shoemaker. How often do system/equipment
designers actually have their engineers, not just the
marketing mavens, spend time directly at a hospital
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or clinic watching doctors and nurses use their
systems?
DR. BLOCK: Well, about 25 years ago, an
anesthesia machine company, which is no longer in
business, told us that none of their engineers had
ever been in an operating room when a case was going
on. And these were people who were designing our
anesthesia machines. So it gets better today, and
the FDA says it has to be better today, but I think
there's always an opportunity to do more.
DR. GOLDMAN: Yeah, I think the short
answer is not often enough. They're welcome. We're
eager to have them experience the joys of patient
care so that we can remind them of how -- well, how
what's easy to diagnose in terms of a USB connector
being part way out of the back of the computer is
trivial in your office, in fact, goes undiagnosed all
day long when people are under pressure to care for a
critically ill patient, which was indeed that case.
And they're not necessarily comfortable with the
electronics that they might face.
And that's the reality. Simple things like
that are actually too complex to be dealt with by
people under that kind of pressure, who then are
afraid they'll get in trouble for breaking something
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if they touch it. The same getting in trouble
concept they talk about in engineering.
So thank you very much to the panel and to
the audience.
(Applause.)
MR. THOMPSON: While we're loading the
presentation -- it should be done in just a second
here -- this session deals with mass
interoperability. I'm not really sure what the hell
that means, but we're going to be talking about
things like mobile health and wireless health. And
we've got some interesting use cases lined up. Our
first presentation will be by Praduman Jain,
sometimes also referred to as P.J., who's the CEO of
Vignet, Inc. He's going to talk about mobile health.
MR. JAIN: Good afternoon. My name is
P.J., and I'm the founder and CEO of a company called
Vignet, Inc., and we are in the business of providing
a mobile platform for connected health. We've been
looking at this space for a while and have some
thoughts to share.
So industry has been focused a lot on
looking at connected health, and in various studies
there's a lot of discussion of connected health
reducing costs and improving the quality of care and
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that the traditional methods of healthcare have been
augmented by a lot of newer technologies, remote
patient monitoring, telehealth. A lot of wireless
and mobile solutions are also coming into this. So
clearly these are all new grounds, new areas, and you
know, from the perspective of patient care, obviously
ensuring safety is paramount in the delivery of care.
I want to go back a little bit and look at
the history. So we are talking about mobile phone.
As you look on the left here, this -- he was pretty
happy with his mobile phone. He was able to make a
phone call. The first wave of that was voice only,
right? We would just be able to talk remotely. The
next wave in these types of phones, we all know about
the stub antenna and the black-and-white phones, but
we were very pleased because now we could do voice
and data, voice and SMS. We could send messages,
right? The third wave came around and probably in
the audience all of us carry a third-wave device
today, where we do voice, messaging, and data
applications.
So if you look at the continuum of time
here, we've been embracing mobile and more and more
functionality today. You know, go around the list of
new applications. We do mobile banking, mobile
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wallet. We do a lot of location-based services. So
mobile has been doing a lot, and we've embraced it.
The question is what's next, right?
People are going to do what they're going
to do, and people are going to use them for a variety
of healthcare applications, call them medical, call
them fitness, call them any of these applications.
So we came up with a couple of use cases just working
within the industry, and these are the things that
industry's talking about.
This is a use case where the mobile device
is used as a conduit. So you have a medical device,
a pulse oximeter, a weight scale, what have you, and
mobile is just a conduit. It receives the data,
sends it into an electronic medical record, personal
health record. That's the role of the mobile. The
question is what should happen from a regulatory
perspective for a situation like this pure conduit?
The next use case is the mobile is a
conduit, still just like the use case before. The
internet, the web, the server in the cloud, whatever
terminology we want to use, that internet is now
processing the data. So looking at all of the data,
and are there any alarms, alerts? And it's sending
the data back to the mobile for primarily display
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purposes. So mobile's role is only again a conduit
and a display mechanism.
In a third use case, where there is no role
of the web or the internet, mobile is doing all the
work here. It reads data from the medical device.
It stores it on the mobile. It checks for out of
range, and it provides alarms, alerts. All of the
processing is done by the mobile. So what's the role
of mobile, then?
And in this use case, the fourth use case,
mobile is doing all the work. In addition, it's also
receiving a lot of software updates from the
internet, from the web, and those updates are now
being downloaded to the medical device. So mobile is
again acting as a conduit for the software that's
being transmitted from the web to the medical device,
and mobile is a conduit. So these were all the
different use cases and scenarios that seemed
plausible.
We believe that the mobile phone can be an
attractive platform for the delivery of care. There
are four primary functions involved in delivery of
care. There's some sort of collection of data, there
is display of data, there is the processing of data,
and there are some software updates. There are
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things that a manufacturer would do to update a lot
of the systems.
So the mobile phones can be used for a
variety of applications, from education, just purely
health education purposes, to monitoring, to
diagnostic, to treatment, and it would be very
beneficial to have very collaborative, nimble, and
flexible pathways to ensure safe and effective
guidelines around mobile and the role of mobile and
how that should fit in in the delivery of care.
Thank you.
(Applause.)
MR. THOMPSON: Next up, we're going to have
Dr. Brigitte Piniewski, CMO of PeaceHealth Labs.
DR. PINIEWSKI: A slow start here. Hello,
Brigitte Piniewski with PeaceHealth Laboratories, and
I'm here to answer Brad's question, what is mass
interoperability about and how does that change our
responsibility as an FDA organization, as vendors, as
manufacturers, and as healthcare delivery systems?
And I just want to encourage the head-
nodders in the crowd, because I do better when
there's agreement with things I have to say, so
please feel free to head nod.
So the main point of this presentation is
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to really remind us -- one of the speakers this
morning said that we used to have the luxury of
having an idea, spending some time organizing it, and
by the time we were ready to deploy, everything was
still in place so that the relevance was still there
and what we had worked on was received effectively.
And with today's talk, I'd really like to focus on
how much the world has changed and how the
opportunity for looking at things differently is
really upon us now.
And just to set the context for this, the
value proposition for the FDA here is to support the
2010 national -- the nation's first health security
strategy. This strategy, put out by the HHS,
suggests that we would really like to share
responsibility between government, individuals,
communities, the responsibility for future health
expression. And so we'd like to learn how we can use
connectivity, mass connectivity, to provide
communities with a proactive community voice and
really use the power of the end of many to build
proactive resilience for communities. And we're
going to do that through maximizing this resolution
of pre-endpoint experience, and I'll give you an
example using a flu pandemic, such as H1N1. So from
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those of us on the ground, here's the view. We'd
like to frame this up so that we can discuss this as
we move forward.
Here is an ideal scenario where we have
wellness on the Y axis with peak wellness at the top,
deteriorating down to illness and death at the
bottom. And then the X axis shows us the ideal
scenario throughout the decades of our lives.
If, in fact, we could just have all of our
communities exist with something close to our peak
health potential throughout and then drop off rapidly
to death, then this would be optimized. However,
what we see as clinicians on the ground, our mission
at PeaceHealth is to be responsible stewards of
community and individual health, but we can't do it.
Every day we're reminded by our patients that this is
the sort of thing we're seeing: an earlier and
earlier encroachment of chronic disease expression in
the population.
In this room we probably have many of the
very last of the accidentally well. The traditional
medical system was the green line. We should all be
well until we are ill, and then medicine should be
introduced when we become unwell and return us back
to perfect health. But we're now in this age of
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chronic care management, which, when we get down to
the bottom -- oh, here, I should be using the arrow,
right -- when we get down to the bottom here, we're
no longer able to really return individuals back to
peak health. Eighty percent of what we do is chronic
care management.
And so what I'm suggesting is that in this
episode up here, in wellness, pre-illness, and
illness, we have this deteriorating ability to return
people back to health. And so the reversibility or
the fluid phase is decreasing as we move down. And
what we're really seeing with our children is this
rapid progression, in early age, into decreased
health expression.
So 60 to 80 percent across multiple
studies, across multiple locations on the globe, is
being suggested as preventable health. So our
population is not well until they are ill, and if we
invest all of our energy in understanding how to turn
the care paradigm, this bottom part of the page, into
a perfect experience, if we could make doctors,
patients, and devices perfect at all times, we would
still be sort of down here in this space and likely
just return the individual to perfect care but not be
able to return them to optimal health.
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And so one of the real challenges with
where we are today and the opportunity, as we'll
describe later, is that this system down here in
illness is all predicated on the requirement of
sufficient levels of pathology. We need sufficient
levels of pathology to be able to measure and
quantify whether we've effectively altered something.
And that has put us into the place of defined
clinical trials. But when we wait for sufficient
pathology, we lose the ability to return people to
health.
And so the whole point of mass
interconnectivity is, in this space above here where
there's insufficient pathology but where we can
connect in very, very, very many, we can start to
deliver practical truths, practical scientific truths
that will be of sufficient correctness to adjust the
choice architecture for our community and make them
safer at the end of the day. Then if we make this
area safe, flawless, and perfect, we will not have
protected our communities to experience the peak
health potential that they could have.
And I just remind all of us that a few
short decades ago, each of us were in a community
that had no ability to have Type 2 diabetes until you
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were in your fifth or sixth decade of life. That's a
health advantage that we neither deserved nor earned.
It was just there. And that environment does not
exist today for our children. In many communities
Type 2 diabetes is 50 percent of the pediatric
diabetes burden.
And so understanding how to use this mass
connectivity to let the community teach us what
really works effectively is an opportunity that
interconnectivity, such as Vignet, brings to us
today. And because it's available, we have a
responsibility to understand how to use it
effectively.
So not that everything is truncated with
mass boundaries, but I just wanted to highlight.
This is current regulatory environment. This is
where we've built the Cadillac of understanding very
high-risk environments, very important to get to the
right drug for the right person at the right time.
But above there, there's a learning
opportunity -- sorry. Above there, there's a
learning opportunity to build a model that the
community can teach us in a relatively low-risk
environment many of the things we're struggling with,
because the bottom part of the page here, this
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current regulatory environment, as we've heard over
and over again today, is infinitely complex. There's
so many moving pieces. There's IP involved. There's
this, there's that, there's the next thing. And so
understanding how to get it all right down here may
be a relatively insurmountable task. But up here,
where we have a relatively low-risk environment, we
can have the user environment start to teach us some
of the simple things in terms of how should they work
together and how do they bring us value.
So let's go to the example where we take a
pulse ox, because many of us are familiar with pulse
ox and the narrow intended use of pulse ox, you get
to use it in the ICU, in the OR suite, not so much in
the ambulatory setting, and it has a high competence
in this very narrow intended use. But let's build an
environment that we talked about for the upper use.
What is the use of pulse ox outside of this intended
use, and what would be the regulatory environment
that would allow the pulse ox to learn how to be used
in a community that is not part of this narrow
intended use?
So the plan is to identify not just the
wild west, where we just instrument everybody at all
times and hope something valuable comes out of it,
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but really a much more structured approach where we
identify the health outcome that we wish to target.
We check the medical literature and clinical
experience for avoidable contributors. Then we build
this mass interconnectivity and we accumulate data.
In the beginning we don't have any
predictive capacity. But as the data builds, we lift
to a place of sufficient correctness, and in just the
choice architecture, to respond to what we've learned
from the sufficient correctness. And then we repeat
the cycle.
So in an H1N1 world, where -- forget this
picture but remember the earlier picture -- we had
people coming along at peak health, dropping all the
way down to not just illness but also to death. We
had 14-year-olds last season that were perfectly well
but succumbed. The parents were unable to detect
when it was time to get this child into healthcare,
and stopping that deterioration of pulmonary function
wasn't possible in some cases.
And so the question becomes can we use
technology to sufficiently divide those who are going
to have complicated pulmonary course with the flu and
those who are not going to have a complicated course
with the flu? This is not a fixed intended use.
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It's a flexible intended use. We want to know, can
we find this out? So technology gets together in a
nimble and agile and quick environment, and in the
space of a weekend, almost -- I have high aspirations
for our technologists here -- they can build a patch
that will put together temperature, O2, and heart
rate. And let's deploy that across our flu season to
an end of many and start to watch the patterns to see
whether in fact we can pull from that very large
dataset an ability, a proactive ability to understand
who in our population may or may not be more likely
to experience a complicated flu versus a non-
complicated flu.
And so this gives us a way in which
communities can start to understand how to use
technology to proactively have some idea of what is
the anticipated ICU burden of this next flu epidemic.
And so rather than have a flu experience be
disseminated across a community and no information
taken, that experience gets delivered to a vacuum.
But in this environment, we understand that
this may be very clinically relevant information.
Let's make it low cost. Let's patch it. And then,
in the space of a flu season or two, we start to have
very important, sufficiently correct information
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about how do you separate those individuals, and we
can start to proactively understand what is the
suggested ICU burden of this next flu that we're
going to have by monitoring these sorts of markers in
the next season. And then we get better. Perhaps
the heart rate's not so good. Maybe we need heart
rate variability, and we should put that in instead.
So of course many benefits, many
challenges, but I think one of the deep and powerful
implications of mass interoperability is we have
access now to information that we didn't have before,
access to making sure that tomorrow's resilience,
community resilience, is not the same as yesterday's
resilience.
Use the community health experience to
teach us all that it can teach us about moving
towards greater and greater and greater resilience.
Don't allow community health experience to be
delivered to a vacuum. Provide it with a structure
in which that experience -- and I always say no
experience is too small -- can be organized and
analyzed to provide resilience the next go-around.
And this is Edna St. Vincent Millay. She
says it much better than I do because she's a poet.
So I'll just read it for you. In a nutshell, "Upon
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this gifted age, in its dark hour, rains from the sky
a meteoric shower of facts; they lie unquestioned,
uncombined. Wisdom enough to leech us of our ill is
daily spun; but there exists no loom to weave it into
fabric." And so I'm hopeful that the FDA and this
organization together can build that loom. Thank
you.
(Applause.)
MR. THOMPSON: Okay, next up, we have
Mike -- is it pronounced Paradis?
MR. PARADIS: Paradis.
MR. THOMPSON: Paradis. Wireless Sales
Manager, Dynastream Innovations.
MR. PARADIS: Yes. I think I'm the only
sales guy in the whole room, so I apologize in
advance.
UNIDENTIFIED SPEAKER: Sell us something.
UNIDENTIFIED SPEAKER: Make no mistake,
everybody's selling something.
MR. PARADIS: No, I understand. I don't
want to make this a sales pitch by any means. I
think, in the 30 years or so that I've been out
flogging semiconductor products, I've had to set a
lot people straight when they went down the wrong
path. So I'm going to try to do what I can to maybe
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start that path a little earlier for you.
Dynastream Innovations was the inventor and
creator of a protocol called ANT. It's the de facto
standard in the fitness world, so from accelerometer-
based technology, heart rate straps, things like
that. The ANT Plus Alliance, as you can see all on
my bling, I'm a proud Continua member. Thank you
very much for the opportunity. And I'm also a very
proud ANT Alliance member. We have an alliance of
200 and -- approximately 210 members.
So, anyways, what we're going to do this
time is talk about the simple do's and don'ts when
you're specifying a network. This is not the
technical specifications, but when you're making an
idea of what kind of data, how often you'll want to
have it, and what it should it look like, if you want
to live in an ultra low power environment, consumer
products, very low battery usage.
Okay. So the system do's, the thumbs up.
Those are the important things. The most important
part in this room, I think, and I've heard from
numerous people today and other times, is a shared
communication link. You don't want to have a problem
with giving your information to somebody that doesn't
want it or that you don't want to have it go to.
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So that's always from a wire. If you take
a wire away, you have the ability for other people to
get that data. So my suggestion and our suggestion
is to make that association scalable, not something
that's mandatory at the top level, but something
that's very, very simple. I know we heard about --
that preventing -- the 60 percent in there that's
preventable. That's the business that we're in.
We're in the business of keeping people fit and
exercising and taking away the potential of perhaps
having Type 2 diabetes, or at least helping that.
But that's a simple process. That's a
consumer product. It uses simple broadcast
methodology. Nothing really tight, no strong pairing
mechanisms. But you do need some very secure
communication authentication for treatments. Even
weight scale information has been deemed to be very
secure requirements. So make sure when you plan for
your products, or when you're making a specification
as part of the SIG group, that you allow for both.
Make a simple user interface. I picked
that picture because to me it epitomizes the angst
that people without technological interfaces in their
life all the time feel when they try to use something
that's been thrust upon them. So let's try to make
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it automatic. So try to think of those things when
you make this system integration decision.
Always look for extended battery life
wherever you possibly can because that's going to
make it easier. There's no charging mechanism that
you have to worry about and a complex user interface.
And then try to find multiple use cases that you can
put into one simple transport mechanism or some
methodology.
Consumer price points. Believe me, in the
30 years that I've been doing this, that's the target
every one of my customers has had. So it's not
really possible out there, but the closest to zero
wins typically. And we're going to try to deploy
these pieces of technology in a mode that the
consumer will want to use them. They're going to
want to get it awful close to that zero, rather than
trying, you know, to make it a very expensive
opportunity for them. So we need to keep the bill of
materials that these devices have as simple as
possible.
And our test and certification targets have
to be really kept at minimum. Every time you have to
test something or certify it and go through rounds
and rounds of that, it adds bottom-line dollars. A
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$10,000 addition to a process adds a dollar to each
10,000 piece device. So that dollar multiples into
10, perhaps, when it gets through a bunch of hands
before it gets to the consumer. So think about those
decisions when you're making that thing at the start.
And then it's hard to pick one technology
out of that. I have one, and I'm not throwing my
technology out as the winner by any means, but allow
for multiple technologies. There's technologies
today that are very, very strong and good, and
there's technologies that'll be coming tomorrow
that'll be 10 times better. So don't shoehorn us
into having only one specific technology required.
So PAN, again, this personal area network.
So that's that body-worn network that you see where,
you know, the fitness world has. Basically the
bottom cost goes down as you start to integrate the
devices. The innovators start at the bottom left-
hand corner, and as you get farther down the price
curve, you start to get adoption curves starting to
go up.
And if you think of Bluetooth as a great
example, when it hit the cell phone, it became a
dollar. Before that it was $8. So the fact that it
had lots of adoption, companies like CSR and Broadcom
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could take the features of a chipset or over a whole
board and put it into one device and then change that
device every cell phone year and, you know, making
hundreds and hundreds of millions of devices.
So there are some current technologies out
there in the PAN space, and you can see ours is on
there. This is not a sales pitch. It's as close to
reality as I can think because a lot of them are the
reality in other markets, but they're not the reality
in the personal space, where we've got about seven
million units now out in deployment, so we're kind of
up that adoption curve a little farther. So there's
lots of good technologies out there. Consider them.
They're all great.
Low battery consumption. I've heard from
the blood glucose market that a glucometer can't
operate on anything but a coin cell battery. It's
important to have that target in mind. That's what
the use case is. It's not that it can't operate on a
double AA battery or a chargeable lithium pack, but
the use case is it should operate on an inexpensive
consumer-replaceable device. It should.
So always try to keep that in your mind
every time you make a decision step, adding extra
amounts of data, adding extra authentication
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communication back and forth. That consumes power
and that doesn't allow you to live on a small battery
such as a coin cell.
And interoperability. Everybody's talked
about it today. That's a little indication of what
our ecosystem looks like. It's extremely
interoperable. We have 11 device profiles, Bluetooth
and Bluetooth Low Energy, ZigBee. A bunch of the
other standards have a got group of profiles also.
They demand interoperability. And we always say 100
percent interoperability is the minimum you should
count on. Never give into, yeah, it's almost
interoperable; if you do this it's interoperable.
So try to keep your interfaces as simple as
possible, and then target hardware implementation as
often as you can. The closer you get to the hardware
with an implementation of a protocol or a network,
the more reliable that interoperability is going to
be. So I hope I'm not losing anybody on the non-
technical side. I'm trying to keep it as slim as
possible.
So here are the don'ts. Again, the angry
smiley face. So wired systems historically have a
lot of data traveling across them. They can.
They're a wire. There's no limitation. There's no
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power consumption issues. So taking that historical
usage and trying to duplicate it in an ultra low
power wireless system is going to be virtually
impossible. If you want to live up to the do's that
we heard about, a coin cell battery, low bill
materials cost, the user interfaces, they've got to
be very simple.
And a sensor communication. Now, this may
not read extremely well, but if you think of a sensor
measuring some data to send a time of each time that
measurement was taken, and software revs and battery
life and all of that information across every
message, it's going to consume a hundred times more
power than you could in a very simple consumer-driven
kind of a product. So try to take that information
and put it in somewhere else in the system.
So this is a wireless watch. It takes the
day, date, and time that it's got, and it puts it
together with the heart rate information and it
stores it, and then when it gets close to a PC, it
uploads it to the PC. It's not sending that
information across from the heart strap every time.
And allowing manufacturer-specific file
structures, that's a challenge. You're not going to
get interoperability. Hardware-wise, you can, but if
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you have two files that don't look alike, they're not
going to interoperate. The health records are going
to be a problem. So don't allow that.
Over-complexity. You can see there,
there's a little bit too many locks on that bike.
That's over-security. I had one picture that I tried
to get that had a thousand locks on one bike because
you can over-secure a bunch of things. And it really
doesn't do much more than the two locks that would be
sufficient. But really try to take the assurances of
the connection. Take the security costs and the
money that it costs to do that and the battery power
into consideration. Don't overdo the security
requirements as best you can.
Encryption is very expensive, by the way.
You can get free encryption engines, but the time
back and forth is a very large amount of battery
consumption, and it also is a level of complexity at
the host processor that's going to cause you a larger
bill of materials cost. So sometimes people say, oh,
it has to be encrypted, and it doesn't really have
to.
And broadcast for fitness is the way to go,
in our minds. So authentication for blood glucose
and blood pressure and periodic communication for
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activity and heart rate and SpO2 and some of those.
Stay out of the tunnel vision. Remember
that you're not just making one device. You're
trying to make an ecosystem. So try not to define it
as the device that you're friendly with. And having
data correlation, having multiple points of data
makes sense of that data. It makes it look better.
And hear no evil, see no evil. Blind
interoperability assurances. You'll hear that all
day long from people that say, yes, it's going to
work. Listen to somebody who says, here, it does
work. That's the end of my presentation. Thank you.
(Applause.)
MR. THOMPSON: We're running just a tad
behind, so we're not going to be able to take many
questions, but we could take a couple of them. Maybe
while you guys -- if anybody wants to ask a question,
if you could come to a microphone, and I'll ask one
in the meantime. And P.J., I'd like to ask it of
you.
In your presentation, I thought you did a
nice job of laying out some of those use cases. I
wonder what you think about the regulatory solutions,
what you want to see happen in order to enable some
of those use cases. Remember to press the button
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there before you respond.
MR. JAIN: As I was pointing out early on
before the use cases, that from a consumer
perspective, from a patient perspective, people are
so used to using their mobile phone, they're going to
want to use it regardless. So obviously, you know,
we've got the FDA here, and they're going to be
looking at it from -- perspective.
But from a user perspective, I just want to
be able to use my device, and I expect it to be safe
and effective to be able to provide me with the value
that I've gotten so used to. So I think it's really
working collaboratively with the FDA to come up with
that answer of what that should be.
MR. THOMPSON: Okay. Do we have any
questions from the audience? If not, I guess we'll
move on to the next presentation, but I'd like to
thank these panelists first. Thank you very much.
(Applause.)
MR. ROBKIN: So before we begin the last
session for today, there are only a few people who
had room in their vehicles, so if you could be nice
enough to wait at the door at the end of the
sessions. There will be two shuttle buses that can
carry 15 people.
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UNIDENTIFIED SPEAKER: Each, each.
MR. ROBKIN: They will be ready. Each. A
total of 30 people. Fifteen times two is 30. And
they will be downstairs at five o'clock if you want
to take a shuttle bus back to the hotel. If we run a
little long and you don't want to take the shuttle
bus, there are lots of cabs, of course, and they will
have a phone number for the taxi service downstairs
by the security. No, once. Two buses going once.
If you know you want the cab, please tell Lindsay or
Molly out front, and they'll call a cab for you ahead
of time. All yours, Brian.
MR. FITZGERALD: Well, welcome to the last
session for the day. We're going to be talking about
system risk management here, and it's a nice lead-on
from the systems-of-systems talk we had earlier.
MR. MURRAY: Who are you?
MR. FITZGERALD: My name is Brian
Fitzgerald -- thank you, John -- in case you didn't
know me. I'm here with the Food and Drug
Administration, the Center for Devices, and I got
conned into moderating this session here. I've got
four excellent presenters. Let me introduce them
before we call them up.
We're going to be starting with John
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Zaleski, and I want you to just understand that John
literally wrote the book, and possibly the first
book, on integrating device data into the electronic
medical record. John's with Philips Research in
biomedical informatics aspects.
Then we're going to be asking Dale Wiggins
to come up and talk to us. He is the CTO of patient
management and health informatics at Philips
Healthcare. Then we're going to have Tracy, Tracy
Rausch, who is the founder and the CTO of DocBox,
point-of-care healthcare informatics. And lastly
we're going to have Peter Kelley, who's the Director
of QA and RA, with 20 years history of development at
Capsule.
And with that, what I want to do is, just
before we have these presentations, there are two
questions that I would like to put on the table,
questions that if our presenters don't get the
opportunity to answer, that you will have the
opportunity to answer us at question time. So I'll
put these questions out now so that you have time to
think about it.
The first one, when we're talking about
systems of systems, what risk management paradigm is
being used when these systems are created and
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aggregated and maintained? What risk management
paradigm is being used? The second is who is doing
the risk management of these systems? Perhaps the
corollary to that is who can do it? So let's just
keep those two questions in our mind, and I'll bring
them back up again, and let's see if we can discover
something new about these risk management paradigms.
The question is from one of our online
viewers, is do I know about OHME? OMHE. And the
answer is no. What I'm going to do is I'm going to
ask our questionnaire to enlighten us during the
course of this presentation so that we can share the
answer. John.
DR. ZALESKI: So I'm going to touch on
actually a vignette that Dr. Goldman brought up early
in his presentation, and after Dr. Friedman gave his
talk, we were talking offline, and I'm actually going
to touch on, I think, an aspect of Element 3 that he
was talking about. So what I opted to talk about
here was time and frequency alignment of multi-
parameter data and primarily from the perspective of
clinical decision making.
So this is kind of an eye chart, but really
what I'm focusing on here is real-time clinical
decision support systems require accurate high
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frequency data, that is, data that arrive in real
time, that are used in real time for clinical
decision making within what I call one meter of the
bed or one meter of the patient. Many devices employ
gateways. Some are direct connects, and those on
gateways typically possess common timing and
synchronization services.
And Dr. Goldman referred to NTP earlier,
the specific concerns over integrating data for
multiple devices that are not calibrated to common
timeframes and do not provide common time windows and
therefore asynchronously need to have data pulled in
order to make clinical decisions. And I'm going to
identify this -- I'm sorry. I'm going to demonstrate
this from the perspective of one scenario, one I have
lived, and just to illustrate the types of challenges
involved.
So we've all seen pictures today or various
pictures of high acuity environments. This is
another one. I'm showing essentially different types
of devices that are in use at the bedside in a high
acuity environment, typically an intensive care unit,
but potentially OR as well. And in these
environments, clinical decisions need to be made, and
what I'm showing here is somewhat of a rubric for
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clinical decision making.
I'm identifying the fact that there are lab
information systems, radiological information
systems, X-ray, CT, et cetera, that are used -- long
X-rays as an example -- departmental information
systems, devices, enterprise health records, all
information that are associated with a patient, that
are essentially pulled together in the process of
creating or establishing an action to assist the
clinician in the bedside point-of-care assessment of
a patient. So clinical decision support systems that
involve real-time decision making have to pull
information from all systems together to be able to
make effective decisions.
And one specific example that I like to
show is one of spontaneous breathing trials or
managing patients postoperatively. An example of
such patients are coronary bypass patients. The so-
called CABG patients are those who typically are
managed postoperatively. That is what? They're
essentially on the mechanical ventilation. I'm
showing a subset of parameters here, a very small
subset of parameters, just to illustrate the process
against a temporal axis, the time axis. So as an
example, spontaneous breathing versus mandatory
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breathing, what the ventilator is doing and how the
ventilator is reduced over time as a direct response
to physician orders and what the patient is doing in
terms of spontaneous breathing, title volume, cardiac
output.
And then what I'm showing typically are
synchronous data that is collected. The X's indicate
data that are normally collected synchronously, that
is, they're offered up, they're sent by the devices
typically without being requested, and then data that
are essentially queried at asynchronous intervals,
including infusions. And I'm showing nitroprusside
here as a simple example of that, a vasopressor and a
vasodilator.
And the point being that the time intervals
associated with the collection of these data are not
necessarily aligned at any one center of time. And
I'm showing that here by the vertical bar, which
illustrates that data availability and staleness,
potentially, in relationship to a request for
clinical decision support. So you can see here these
ovals that identify the request for information,
which actually exists between two specific active
known times or known pieces of data when they're
actually available versus when they are available
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synchronously. And one potentially motivating
requirement or need for this is the writing of an
order for reduction in respiratory support, reducing
a patient from intermittent mandatory ventilation
level 12 to level 8 or to CPAP, continuous positive
airway pressure.
These decisions are made on the basis of
the patient's overall data, including laboratory
information system, O2 saturation, et cetera. And
sometimes the data are available and sometimes they
are not. The point being that if data are stale, are
old, then a clinician will be making a decision on
relatively stale data. But compounding this problem
is the fact that some of the data may be arriving
from devices that are not necessarily aligned in
time, in terms of the overall network time.
So I think Dr. Goldman showed a simple
example of one clock showing one time, another clock
showing another time. Frequently, as an example,
mechanical ventilators are an example of these --
typically are not on gateways, whereas multi-
parameter monitors can be, through their gateway
architectures, and infusion pumps can be as well.
The point is that the data that arrive from the
multi-parameter monitors versus single or standalone
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devices can be offset, and it may not be known how
far they were offset. So what is complicating or
potentially compounding the problem is the situation
in which absolute time is unknown, and especially
with regard to clinical decision making.
So, what are the potential hazards
associated with this? Well, misaligning vitals data
when integrated or fused together could impact the
clinical decision making from the perspective of
misaligning orders, misunderstanding when the actual
data were valid, and when an order actually was
accomplished, when it was actually carried out by a
staff member, and accurately recording the
information, the clinical documentation.
Orders based on time differences can result
in misalignment of when, as an example, a change is
performed on a mechanical ventilator or an infusion
pump, data not collected on one system because the
time threshold is not met on the system, as an
example. The list goes on and on. Some of these are
more acute than others, but the point is, is that
they can occur and in large part because there is no
common timeframe for them.
Now one possibility or one -- in terms of
clinical impacts, I decided I'm not going to go into
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detail in this chart. But the potential impacts are,
as an example, cardiac output changes can occur as a
result of infusion results or infusion changes, and
they can occur very, very quickly. So we're not
talking about changes here that have a long center in
terms of time interval. They can occur very, very
rapidly when changes in infusion drips actually
occur, et cetera. So we're talking about situations
in which high accuracy is necessary.
In addition to that, if we could provide
the capability to do gap filling, that is, be able to
pull data in when it's required for clinical decision
making, so that when there is a time gap between
available data asynchronously, we could go back to
the device either automatically or flag or identify
in a fashion similar, I think, to what Dr. Goldman
was talking about, simply identify the fact that data
are missing and go and request it or query it from
the device, when necessary, or notify that there are
data missing or a decision is being made on the basis
of data that are stale, as opposed to simply just
saying, well, this is the latest information that
happens to be in the record, in the documentation
system.
One possible approach to doing this is --
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and we've all seen various -- or some of us have seen
various representations of devices talking through
gateways to interfaces engines, to departmental or
EHRs. Being able to automatically go and re-query
for information that is stale would be very useful to
do. And that's basically it.
MR. FITZGERALD: Thank you, John.
(Applause.)
MR. FITZGERALD: Now we'll have Dale
Wiggins.
MR. WIGGINS: I'm amazed. I never saw a
research organization finish on time before. Sorry.
I get punchy at the end of the day. It's great to be
given the presentation at the end because I know that
we're the last group before drinks and so the
questions will be short. There we go.
Okay. So I'm going to talk about a
clinical problem that when I first heard about it, I
thought it was pretty straightforward. There's
publications out on the internet available, talking
about this clinical problem and when you read it, it
seems like it would be a great case for device
interfacing. The benefits are quite clear. The
problem with realizing those benefits is that if you
do it with today's clinical practice, it requires
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clinician time that quite frankly they don't have.
They basically have to sit in front of the devices
all day long and manually adjust all these settings
continuously. So I'm going to try to talk a little
bit about this problem, some of the issues that I
uncovered looking at them.
So the basic problem is relatively simple,
at least I'll simplify it to something that I can
understand, and I'm sure some of the clinicians can
add a lot of complexity here. But the basic problem
is either too much or too little oxygen for
ventilated neonatal, preterm infants, in other words,
in the neonatal ICU. So what they're trying to do is
adjust a setting on the ventilator, which is the
inspired oxygen fraction, to maintain a pulse
oxygenation rate with the patient.
So what I tried to represent here is,
graphically, whether some of the workflow -- what's
the major workflow, what's the control points that
are realized in terms of solving this clinical
problem? So it all starts up top and obviously it
starts with an order. And what that is passed down
to is someone that ultimately needs to execute that
order, and that relates to making specific settings
on a ventilator, which ultimately impact the patient,
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and hopefully we get the required results out of
those settings to ultimately achieve the therapy
goal.
I think the complexity -- the first
complexity that you uncover is that we often ignore
patients, especially neonates, are not a predictable
machine. You know, we like to think about, you know,
in my technical world that, you know, everything's
logical, everything's predictable. And I think Frank
said it earlier best. You know, patients are not
entirely logical and predictable.
So we do have feedback mechanisms built in
along the way. Unfortunately, I think in current
practice, a lot of these feedback mechanisms relate
in a lot of clinician overload. And I think, as
Julian pointed out, a lot of times it's patient
overload as well. He showed a nice example of one of
our applications that ultimately kept him up all
night.
And ultimately, I think, it does make the
case for how we can improve a lot of that workflow, a
lot of that patient outcome, and as we've studied,
you know, the ability to impact the way that that
patient receives that care can ultimately have big
impacts on their improvement and their ultimate
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outcome as well.
So what we've also represented here is some
of the clinical decision support opportunities that
we see in this clinical scenario, if we did have some
of the automated feedback loops built in, you know.
And I think there's -- we often look for the perfect
solution, but what we've tried to identify here are
there are actually multiple different ways with
varying levels of complexity that you can look for
partial solutions.
So in this next slide what we've tried to
do was just, you know, at a high level, identify some
of the major settings that, you know, I talked about.
You know, if you look at it from a top level, it's
relatively a simple use case. You've got one setting
you got to adjust and one measurement you need to
observe.
Well, in reality, when you think about it
from the order, the therapy order that is given and
how you translate that into all these settings, all
the various interactions with the system that the
user has, whether it be setting the various modes and
settings based on the order, device connectivity and
device failures, actually adjusting some of the
settings along the way, and then also how we
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ultimately feed back, it does become a rather complex
endeavor.
What I next tried to do is identify some
specific issues in each of those categories. And I
think you've heard probably most of them in different
scenarios today. In order not to throw too many
stones in a glass house, if you will, I'm going to
talk about the one that's most relevant to the
patient monitoring business, since we're involved
with it. And again, I'll use Frank's example.
He said that it's careful to note that
those observed measurement values, they aren't
patient measurements; they're device measurements.
They're what we interpret the signals to mean, and as
such, you know, we like to think that they're
100 percent accurate. I'm sure that everybody would
like to think they're 100 percent accurate, but they
aren't. They're subject to the transducers that are
applied to the patient. They're subject to motion
artifact. They're subject to environmental
conditions.
And all those factors come into play in
terms of the accuracy of that measurement. And
unfortunately we look at study after study that says
that, well, if you're just looking at that HL7 vital
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sign, for instance, well, you're probably going to
get about a third of those in error, and that might
even be in a really good case.
So I think it's really important -- and I'm
going to move in interest of time -- to make sure
that we're keeping track of what is the specific use
case, and as we're drilling down on those interfaces,
to think about how are we expecting to use that
interface and making sure that we really do have the
right specifications and the right requirements
associated with those interfaces, such that we really
can get the results that we achieve. And I think a
multiple of speakers today have talked about that in
great detail, but I think to me that's one of the
overriding things that I have heard that's really
consistent throughout this carrier.
I did want to be -- this is my last slide,
and I thought I'd be remiss if I didn't mention that
there is a lot of great work that's going on in the
standardization area. And ultimately, I think, from
a vendor standpoint, standards need to be part of the
solution because ultimately when we talk about
getting vendors to participate and ante up to this,
we need the standards so that the business case is
broad enough that ultimately you can make profit at
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the end.
I think that, you know, the -- I'll use the
old joke. You know, the good thing about standards
is that there's so many to choose from. I think some
of the real things that I like about what I see
happening today is that we're starting to move more
from just the base standards, more into true
interoperable profiles, and I think, as those become
demanded by customers, that then we really will be
able to achieve some of the breakthroughs.
But this list up here, as well as the other
ones, isn't sufficient. There's a lot of holes in
terms of as we put these systems together, they still
need to be addressed. There's a lot of fundamental
research and technology investment that needs to be
made to, for instance, get those pulse ox values to
be much more accurate, make the requirements and
specifications much more clear so that we really can
put these systems together in a reliable fashion.
Okay.
(Applause.)
MR. FITZGERALD: Let's welcome Tracy Rausch
to the podium.
MS. RAUSCH: So about five years ago we
were sitting in a conference room with a few people
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in this room with Dr. Goldman, and he says we have
all of these clinical scenarios and stories, and what
do we with them? And myself and a couple other
clinical engineers kind of looked at him and said
that's probably a pretty good question. And that's
where this work actually started was, you know, in
that conference room. What do you do when a doctor
tells you a story? How does that actually translate
into something or requirements that an engineer, as
we've heard before, who's never been on the OR, who's
never been in ICU, can actually understand what that
doctor's actually saying? This work went on for
about four years. Fits and starts.
And what's starting to come out of this
work is that there are basically some building blocks
that are common amongst almost all clinical workflow.
So we're talking this from a perspective of -- you
know, we've heard the technical approach to this.
How do you integrate? But really the system is a
clinical system, and right now this is the picture of
the clinical system. And basically the text is what
you're going to hear, if you hear two nurses talking
to each in a room across from two patients. Some of
it's a little frightening, but we'll get past that.
So basically the reality is, is healthcare
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is a combination of many systems. These systems
include the people, the information systems, the
medical devices, and the patient. We've heard a
bunch of talks today. Most of them are leaving out
the people part of this aspect. So how does actually
clinical workflow impact what you need to do for
interoperability and device integration? You can't
design a system without understanding how the parts
work with each other. You get unintended
consequences, and there's a safety issue. So I did a
little math last night, so my numbers might not be
great. We can negotiate those back and forth. I
figured I don't even need to read it. It's big
enough.
(Laughter.)
MS. RAUSCH: This is in a critical care
unit. This is the number of combinations. I don't
even know how to say this number, so we're just going
to leave it of what it is. One of the things we can
do, in a system-to-system, medical device types can't
be the primary component of the system. We need to
go down one more level lower. What is that
functionality of that device? This allows us to
advance innovation. If there's a new management
parameter, we shouldn't have to go back and redo
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everything. We should be able to classify that
parameter as a certain component.
Using functionality of the devices, it's
going to allow for that advancement. But early work
has shown there's basically a common set of building
blocks. Through the work of the ICE-PAC and the
plug-and-play program and my company, DocBox, and
some others, we've actually done a pretty intensive
analysis of ventilator processes and workflow of
critical care. What are the different situations?
What are the different scenarios? And also with
infusion therapies. When we put these two down
beside each other, it's a really big conference
table, I can tell you that right now.
I believe right now we have probably about
70 letter-sized pages of workflow that's printed out
of basically what happens if you take one infusion
pump and one ventilator and put them together at the
site of care, of what a clinician is responsible for
doing. But all of a sudden you start looking at it
and things start popping out. There's commonality
among all of these clinical workflows, commonality of
decisions.
So if we could actually capture what those
common device components are, we could actually start
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to look at systems in a safe way, because if we can
make each of those individual components safe and the
interactions to them safe, our combination number is
still pretty big, but it goes down a little bit.
Some of the examples of these blocks -- and
you know, we're naming them generically, this is
ongoing work -- will be, how do you collect data?
How do you send data? How do you compare data? And
this is coming from the clinician's perspective.
This isn't coming from one device talking to another.
What is the functionality and what does that
clinician need at the time of, you know, these
interactions that occurring?
So I've still got this big number, and I'm
not really sure what to do with it. So my first
thought, I'm not -- you know, I don't know
everything. Let's go borrow some of the technology.
So now I'm not saying that we need to go adopt
certification processes from other industries. I'm
not saying we need to go do other things. But let's
learn how they get through that process, and can that
technology be designed for the healthcare system?
Aviation's been using simulation since
1934. We're a little behind on the ball here. Right
now there's not a single airplane that's designed
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that the entire system is simulated, a system-to-
system, before a single piece of device is made.
The Defense Department can simulate an
entire battlefield environment and understand what
the logistics are, where things happen, where things
are supposed to go, and what are the risks if
something doesn't occur. Computing power in these
simulations, it used to take them about 300 hours to
do this analysis. They're now telling us it takes
about 30 hours. And the technology can be done on
basically a workstation, and that's pretty amazing.
So I have pictures, thanks to some
colleagues. They're simulating nuclear power plants.
They're simulating new facilities. They're
simulating the battlefield environment. And it's not
just the pretty pictures and, you know, the avatars.
You can move the environment and see where things
are, but it's actually the analysis that's behind it
that's the important part of this. You can look at
relationships, you can look at risk points, you look
at where things fail, and you can do this in a way
that you can use technology to actually help us
understand how these requirements work and interact
with one another.
So some of the conclusions. If you use
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functional building blocks instead of the device
types to understand how systems interact with one
another, you probably have a little better
understanding of what's going on and actually how to
make and design heterogeneous safe systems. And the
other thing is let's utilize some existing analysis
methodologies to move towards, you know, either
certification methods or another method that works
for healthcare, to understand these systems to
systems.
So I wanted to thank the plug-and-play
team, the ICE-PAC team has contributed to this work,
and Lockheed Martin Simulation and Training Systems
Virtual Labs Division.
(Applause.)
MR. FITZGERALD: Thank, Tracy. Please
welcome Peter Kelley to the podium.
MR. KELLEY: If you can all bear with me
for a few moments.
(Pause.)
MR. KELLEY: All right. Sorry for the
interruption. First, I'd like to thank the FDA and
CIMIT and the Continua Health Alliance for making
this opportunity possible. I believe this is a
really important subject that we all are talking
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about today, and this is really an outstanding
opportunity to be able to just get together and to
discuss it.
What I want to talk about today is to just
explore applying some of the concepts that are
embodied in the IHE framework and applying those
concepts to risk management for the purposes of
controlling risks in systems of systems. We've had
many scenarios painted today about really potentially
disastrous occurrences that could happen, and I've
got my own that I'll show you very briefly just for
illustrative purposes. Before I do, I need to point
out that I'm not proposing that IHE take on this
charter. What I'm trying to do is to reuse some of
the mechanisms that they have implemented quite
successfully and applying those to management of risk
so that -- for the purposes of stimulating a
discussion around this topic. We've heard a lot of,
as I said, scenarios and possible mitigations. What
I'd like to present is a way of bringing those
together in a standardized way that could really help
to facilitate the implementation of risk management
via both ISO 14971, which is risk management for
medical devices, and the new IEC80001.
Before I do, I just thought I would go
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through a real brief walk-through on risk management.
Risk management is a structured way of assessing the
potential harm that could occur during normal use and
non-normal use of medical devices, or in this case
systems of systems.
We start with a risk analysis. We identify
hazards that could occur. We identify hazardous
situations that could trigger those hazards and then
we assess that. Part of the assessment is the
identification of the harm that could occur and the
likelihood that that harm would happen. The harm is
then evaluated to determine the severity of that harm
and the probability that the harm would in fact also
occur in the presence of the hazardous situation. In
the event that the risk assessment reveals an
unacceptable level of risk in either the system or
the device, you move on to risk control, where you
identify mitigations that you put in place and to --
and after you have done that, you do a residual risk
analysis to make sure that you have not added more
risk to the system than you have removed from it.
The risk case scenario that I want to talk
about today is a closed loop system -- we've heard,
again, several of those today -- with a bedside
computer-assisted medication administration
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application which is controlling the infusion of a
patient on cardiac medications. The BCMA receives
the patient's vital signs through an MDDS, a medical
device data system, and all of these systems are
residing on a hospital network, along with EMR and
ADT applications.
This is an example of a risk profile that
is called patient association. Each profile can
contain any number of risk case scenarios. For
brevity, I'm presenting only one here. A hazard is
associated with each scenario. In this one there's
an incorrect association between a monitor and a
patient. In this situation the two patients are in
the cardiac care unit, one is on a vasopressor, the
other's on a vasodilator. Both are controlled by a
BCMA. Through some happenstance in between the EMR
and the ADT system, or perhaps any other number of
scenarios we could describe, the association of the
monitors, the vital monitors for patient A gets
associated with patient B or vice versa. The BCMA
then instructs the infusion pump to titrate the
vasodilator too rapidly. The harm that results is
that the patient goes into deadly dysrhythmia and
ultimately dies.
Using the risk management process, the
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obvious severity of that is catastrophic. And for
this example, rather than going through the
evaluation and determining whether or not this
mitigation would be required, I'm assuming, for the
purposes of illustration, that we would want a
mitigation for this issue.
And this brings us to a risk case control
example. The idea here is that we would have -- each
hazardous situation would be accompanied by a
standardized risk case mitigation. In this very
simple scenario that I presented, it could be that a
requirement be put in place that all transactions
must include a patient identifier. Perhaps there's a
subset of transactions that we could identify that
would need that. But if a patient identifier had
been included with that transaction between the BCMA
and the infusion pump, the infusion pump would've
recognized that it was the wrong patient that it was
being told to change the titration form. The
verification of this could be a standard test
protocol similar to what IHE does now.
Finally, vendors would be able to publish
statements, declarations of conformity, if you will,
to identify the risk case control statements. So
they are effectively declaring that they have
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implemented the specific mitigations. These would
then be used as a deliverable for complying with
IEC80001.
One of the benefits that I could see for
doing this is it takes a lot of the ideas that I've
heard about today, a lot of the difficulties we
encounter, a lot of the potentials that could be put
into place to correct those, puts them into a
framework where we can all talk about these things at
the same level, where we can identify standard -- not
standards but standardized mitigations which can be
used to correct them. And then it gives the vendors
a convenient means of being able to declare that yes,
they have implemented that.
The hospitals who are then trying to apply
80001 to their healthcare network can then say, well,
we've got vendors A, B, and C, who have done these --
who have met these risk profiles, who have
implemented these risk mitigations. That fits with
the mitigations that we are requiring. And that is
my presentation. Thank you.
(Applause.)
MR. FITZGERALD: Thank you very much,
Peter. We have a few minutes left. We can throw the
floor open to some questions and maybe some answers.
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We have two questions on the table. What risk
management paradigm is being used, and who is doing
the risk management of these systems? Peter managed
to touch briefly on those two issues. Does anybody
else have any comment or any question about these two
things?
MR. MURRAY: I have a question for
Dr. Zaleski, but not your question.
MR. FITZGERALD: Go ahead. Let's field
some questions.
MR. MURRAY: I was interested in the time
synchronization -- the product, and in listening to
both you and the other folks, we all view medical
devices as pushing devices, data push, not data pull
primarily because historically that's the way it
works. The box sits on the wall or on the table and
you look at it or you wait for it to spew out its
data. If you were to turn it around and make it a
pull approach, would you then eliminate your -- or at
least eliminate part of. I can see where you
wouldn't eliminate all of the time delay and the
synchronization of it.
DR. ZALESKI: You wouldn't eliminate the --
that's one of the part of the process. You have to
provide the capability. But what you need to do is
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provide the intelligence to be able to request the
information.
So if you go back to Julian's scenario,
whereby the ventilator assumes a pause during the X-
ray and then resumes after that, that could be a --
that is an example or one example potentially of a
situation where the device could push data
asynchronously or the data could be requested
asynchronously, on the event, transmit this
information verification, as an example. I'd say
it's one aspect of it. It's not the complete.
MR. WIGGINS: Can I add something to that?
Just to add one more thing, from the standpoint of
the way we implement our system today, we actually do
pull in the time from the enterprise systems in our
central station environment and then we -- so we
synchronize to that level, and then we have a much
finer grade synchronization between the central
station and the bedside monitors themselves. So I
think, you know, that's part of the challenge, that
we need to make sure that we understand when we're
looking at specific use cases. You know, for
instance, IHE ITI has a consistent time protocol that
works great, you know, at the central station level.
But if we get down to the finer grain or the point-
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of-care device integration, we're going to need a
different level to get some of those finer grain use
cases.
MR. FITZGERALD: So we have a couple of
questions. Let's take the question over here first.
UNIDENTIFIED SPEAKER: It was more an
answer to your question, who is responsible? I think
that has to reside with the systems integrator. If
you look at the existing way that medical devices --
if you take a medical device, a bedside medical
device, and you look at the label on that device,
that's the persons or organization responsible.
If you then look inside that -- devices
from other manufacturers. So you already have the
framework where different devices from different
manufacturers are combined into a single system, and
I think what we're doing now is we're not looking at
the same box. I do, though, think there are issues
and complexities beyond the scope and responsibility
of the person or the organization that is doing
that -- taking that responsibility. So I think while
they take responsibility, the regulatory bodies have
also to protect them by -- you know, we talked today
about shared responsibility, and I think we're now
entering into an area where there are different
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parties out there that accept responsibility, and
that includes the user. So the patient can't just
turn around to everybody because they tripped over a
wire. You have to look at the involvement of the
different parties within that.
MR. FITZGERALD: Well, thank you. That
introduces a neat concept of shared risk space.
Let's take a question.
MR. ZAKIAN: So I'm going to readdress the
time synchronization issues and especially in medical
devices that are not going through monitoring
stations where NTP is normal, but more going through
serial-connected devices that go through MDDSs. Most
of the time the device stamp and the timing on that
is inaccurate because it's a device time that -- so
my suggestion is that you really need to have two
times that. You need to have the time stamp of the
device solely for audit trails and log -- you know,
log file reading on the device in case there is an
anomaly in the device. Yet, again, you can inject
the real time from an NTP, giving it the accuracy of
the asynchronous data collector.
MR. FITZGERALD: Excellent point, the
concept of trusted time and untrusted time.
MR. ZAKIAN: Exactly. And that's very
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doable.
MR. FITZGERALD: It is. You're right. It
is very doable. Let's take the lady. You can wait,
Rick.
UNIDENTIFIED SPEAKER: I'd like to ask the
panel to just talk a little bit about where the human
factors for testing comes and the whole risk
assessment process that is kind of looking at the
user actually using the device in the environment
intended.
MR. FITZGERALD: Well, volunteers to -- who
wants to address that?
MR. KELLEY: I think it's really addressed
at two different levels. The first is by the device
manufacturer during the development of a device.
Very early on, when they're establishing their user
inputs, their user needs, their design inputs, a key
component of that is risk analysis and also user
needs analysis as it relates to risk.
Second is going to be at the system level
or the system-of-systems level, as we've talked about
it, and I'm not sure how that gets to be done in the
context of a clinical environment where you have, you
know, ongoing clinical operations and needs in trying
to implement a new system and do, if you will, an
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ergonomic study of that. There's some real
challenges there.
MR. FITZGERALD: And perhaps we could say
80001 could assist with that. Rick.
MR. SCHRENKER: I want to get back to the
question about the risk management paradigm for a
second. Peter, in your one slide, there were medical
devices connected directly to the network, and that's
a very high-level picture with it. Have you or
anyone else on the panel thought about the
differences between, for instance, local control
versus -- I mean, some problems can, and from basic
control theory, should be addressed locally.
So maybe you don't have to go to the
network for every transaction and what the impact
that might have on risk management, or maybe the
network can inform the local environment for some
period of time and things like that. So is that
covered in the suggestion for a profile? Are those
the kinds of things that should come up? For
instance, local versus -- more local versus more
remote phones?
MR. KELLEY: I would see that as coming out
of the risk case scenarios that are developed and
then the communications that are associated with
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those as well. So you would create a scenario
perhaps with the medical devices connected to the
network. You may come up with a mitigation or
control mechanism where you would lock that local
control over it, over that particular hazardous
situation to prevent it from occurring.
MR. WIGGINS: So just to add a little bit
more on that, I think it's an excellent point, and I
think, to me, it gets back to really understanding in
detail the requirements of your specific use case.
And, you know, I know for a fact we had gone down
some designs and actually got to an end state where
we're basically in what we hope to be pretty close to
final validation and basically discovered that we
couldn't sufficiently mitigate our risk and basically
had to scrape the entire effort.
So I think it's -- your question is
directly to my point of we have to do a much better
job up front at understanding those detailed
requirements and latencies, a very key point to that,
before we can really make a lot of progress here.
MR. FITZGERALD: Thank you. Julian.
DR. GOLDMAN: I have a question regarding
the selection of use cases to generate the
appropriate requirements to bound the space in a way
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that would allow a system to be built that would be
at least modestly future-proofed. So I don't know
what that means, what kind of a word.
So let's say that you come up with a use
case and the data relationship, in terms of the data
granularity and some examples that you gave, John,
you can look at the data. The granularity will allow
a certain level of causality to determine what came
first, what came second. And that might be
appropriate for that use case.
And then perhaps you design a system around
it or you implement parts thereof. And then a year
later you have a more sophisticated use case, and it
has tighter timing requirements or greater
granularity or some other facet. But, you know, that
presents a challenge.
But on the other hand, instead of looking
at that one use case, you could step back and say,
well, what's the highest bandwidth I would reasonably
expect in this part of the system? You know, what's
the tightest timing requirements as far as causality
are concerned? If you look at an EKG, for example,
it inherently is an electrical signal that'll have
different properties than a blood pressure waveform
or a respiratory.
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So how do you balance, you know, what you
can max out on a single signal basis for what you --
based on what you know about the properties of that
versus mapping things to use cases, which always have
certain -- you know, a lot of variability in terms of
their requirements?
DR. ZALESKI: This is one question when the
business ones research the answer it. All right. So
a general answer. Well, I think that you need to
design based upon the acuity of the environment
you're delivering to. And I'll refer as an example
back to Dr. Piniewski's comments in the last panel.
One thing I picked up on, but I didn't want
to be obnoxious and get up at the microphone, was the
idea of heart rate variability and being able to pick
up on heart rate variability as a potential heralding
of the onset of septic shock owing to the
compensations, as an example. But to pick that up
requires sufficient frequencies and sufficient data
to be able to do a full assessment of the signal.
So in that case, and in situations that
involve essentially making high or high acuity -- I'm
sorry -- a high acuity environment involving real-
time decisions, I would say that second or sub-
second, potentially millisecond requirements might be
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necessary.
So you're asking a general question. The
general answer is, in terms of high acuity space, in
terms of the types of comorbidities and types of
challenges that you face in that type of a clinical
setting, I think high frequency is the answer. And
then the question is, well, what about this case,
what about that case? And we can discuss this over a
Glenlivet in about 60 minutes or so. But I think
that -- I think high frequency potentially might be
the situation.
DR. GOLDMAN: But I'm sorry, the open bar
is not including --
DR. ZALESKI: I'm buying.
(Laughter.)
DR. GOLDMAN: Thank you.
MR. MURRAY: You're buying for how many of
us?
DR. GOLDMAN: That's what I want to know.
MR. FITZGERALD: So how many other
questions do we have? Going once. Going twice.
UNIDENTIFIED SPEAKER: I want to make a
comment.
MR. FITZGERALD: A quick comment over here.
UNIDENTIFIED SPEAKER: Okay. So if I
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understood correctly, Julian's question was like what
kind of timings and parameters, how we choose them --
right? Is that the question?
DR. GOLDMAN: Yes.
UNIDENTIFIED SPEAKER: Okay. So I think
what we have to do is to build the model, and when
you have your model done, then you're going to
predict your output of your model and you're going to
compare with data. When that difference is basically
acceptable based on the accuracy you want to achieve,
then that would propagate back on your system
parameter selections.
DR. GOLDMAN: A somewhat different
approach, I think.
DR. ZALESKI: Yeah, I was looking at the
conclusion as opposed to the process.
DR. GOLDMAN: Uh-huh.
DR. ZALESKI: So yeah.
DR. GOLDMAN: Yeah.
MR. FITZGERALD: Okay, let's try that one
more time. Going once. Going twice.
UNIDENTIFIED SPEAKER: You have to answer
your own question.
MR. FITZGERALD: One in the back. Well,
he's challenged me now to answer my own question. So
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this has to stay here between just us, okay?
(Laughter.)
MR. FITZGERALD: All right? What risk
management paradigm is being used? Too frequently
it's the wrong one. It doesn't include the 14971
assumptions of a recumbent, perhaps unconscious,
unresponsive, and unconsenting patient. It tends to
be the risk management paradigm of the IT community,
which assumes consent, which assumes only loss due to
malfunction and bad reputation. That's my answer to
that question.
MR. MURRAY: And it only assumes multi-
point failures.
MR. FITZGERALD: Single-point failures.
MR. MURRAY: Single-point failures.
Forgive me. Not multi-point failures.
MR. FITZGERALD: So the other question.
Who is doing the risk management of these systems?
Well, basically it's Rick, Rich Schrenker, one of the
very few people that I've come across who is willing
and able to confront the 14971 implementation on a
system-of-systems basis. And I said one of the very
few people that I've come across because in my own
humble estimation, there is not enough risk
estimation and risk management being done in these
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systems of systems. And I think many of the
questions that we see are symptomatic of an
inadequate hazard analysis, an inadequate
requirements basis. That has to change for this
whole thing to move forward. My humble effort at
those two questions. And enjoy the drinks.
(Applause.)
DR. GOLDMAN: Wait, we have announcements,
don't go.
MR. MURRAY: We have an announcement, you
say?
MR. MERKLE: Quick announcements, quick
announcements. First of all, thank you very much.
It was a very, very informative and fantastic first
day. So I'll make it short.
The Continua Health Alliance would like to
invite you all, all the attendees, to a reception at
the Sheraton Washington North at 4095 Powder Mill
Road at six o'clock, 6:00 p.m., where we can all
enjoy a drink and deepen our discussions and maybe
have some camaraderie networking. So you're all
invited. I hope to see you all there. Thank you.
Goodbye. See you tomorrow.
(Whereupon, at 5:30 p.m., the meeting was
adjourned.)
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Free State Reporting, Inc. 1378 Cape Saint Claire Road
Annapolis, MD 21409
C E R T I F I C A T E
This is to certify that the attached proceedings
in the matter of:
WORKSHOP ON MEDICAL DEVICE INTEROPERABILITY: ACHIEVING SAFETY AND EFFECTIVENESS
January 25, 2010
Silver Spring, Maryland
were held as herein appears, and that this is the
original transcription thereof for the files of the
Food and Drug Administration, Center for Devices and
Radiological Health, Medical Devices Advisory
Committee.
____________________________
RONALDO OTERO,
Official Reporter
(410) 974-0947