hl7-uk 2003 conference healthcare interoperability past efforts-present benefits-future prospects
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HL7-UK 2003 Conference Healthcare Interoperability Past Efforts-Present Benefits-Future Prospects. Clement J. McDonald, M.D. December 11, 2003. Work of many Regenstrief faculty. Mike Barnes, M.D. Paul Dexter, M.D. Burke Mamlin, M.D. Mick Murray, PharmD. Marc Overhage, M.D., Ph.D. - PowerPoint PPT PresentationTRANSCRIPT
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HL7-UK 2003 Conference
Healthcare Interoperability Past Efforts-Present
Benefits-Future ProspectsClement J. McDonald, M.D.
December 11, 2003
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Work of many Regenstrief faculty• Mike Barnes, M.D.• Paul Dexter, M.D.• Burke Mamlin, M.D.• Mick Murray, PharmD.• Marc Overhage, M.D., Ph.D.• Susan Perkins, Ph.D.• Gunther Schadow, M.D.• Bill Tierney, M.D.
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Where we were in early 80’s
• Building our own systems to collect data– Lab– Pharmacy– Scheduling system
• Horrible batch and cobbled interfaces to collect data from other institutions systems
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What to do?
• Impossible except for nutty people• We needed an easier way• Standards…
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Plea for standards help• 1981 1st rejection of grocer’s paper• 1983 (Jan.) Grocer paper published 1
• 1983 (Nov.) Plea for standards at fall SCAMC meeting 2
• 1984 (Nov.) A discussion of the draft proposal for data exchange standards for clinical laboratory results. 3
(1) McDonald CJ, Park BH, Blevins L. Grocers, physicians, and electronic data processing. AMA Cont Med Ed Newsletter 1983; 12:5‑8.
(2) McDonald CJ. Standards for the transmission of diagnostic results from laboratory computers to office practice computers ‑‑ an initiative. Proc Annu Symp Comput Appl Med Care 1983; 123‑24.
(3) McDonald CJ, Wiederhold G, Simborg DW. A discussion of the draft proposal for data exchange standards for clinical laboratory results. Proc Annu Symp Comput Appl Med Care 1984; 406‑13.
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1984 SCAMC Fall Symposium
• Panel Members:– Clement McDonald, M.D.– Gio Wiederhold, Ph.D.– Donald W. Simborg, M.D.– Ed Hammond, Ph.D.– Fredrick R. Jelovsek, M.D.– Ken Schneider, M.D.
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1984 Proposal- Familiar?FIGURE 1
Patient 1 (general information about patient)Battery 1 (information about first battery reported/requested)Result 1 (information about the first result of battery 1)Result 2 (information about the second result of battery 1) Result n (information about the last result of battery 1)Battery 2 (information about battery 2)Result 1 (information about the first result of battery 2)Result 2 (information about the second result of battery 2) Result n (information about the last result of battery 2) Battery n (information about the last battery for the first patient)Result 1 (information about the first result of the last battery)
Patient 2 (all of the structure repeats)
Patient N
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Pleas answered
• 1988 ASTM 1238-88 4
• 1989 HL7 published version 2.0 5
• 1990 SCAMC – Progress, Promises and the Conductors Wand 6
(4) Standard Specification for Transferring Clinical Laboratory Data Messages Between Independent Computer Systems. Annual Book of ASTM Standards; Philadelphia, PA, 1988.
(5) Health Level Seven, Version 2.0. An application protocol for electronic data exchange in healthcare environments. Ann Arbor, Michigan: Health Level Seven, 1989.
(6) McDonald CJ. Standards for the electronic transfer of clinical data: progress, promises, and the conductor's wand. Proc Ann Symp Comput Appl Med Care. 1990;14:9-14.
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Music & words 1990
• MIDI to orchestra what HL7 is to EMR
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1995-2003
• Messages fairly good• Could get HL7 result messages working in
1-3 weeks• Vendors knew the standard• Most “BAD” messages due to conscious
placement of right info in “wrong” field
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Example bad messages
• Value, units, normal ranges, flags, and performance site put ALL in OBX-5
• Value and units both jammed into OBX-5• OBX-5 says “see comment” - everything
jammed into following NTE • Whole report (many test results) jammed
into single OBX-5
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Life good but not perfect
• Codes for the same question (observation) different every where
• Need most-Standard question (observation) codes – If answer is text- all’s well– If answer is numeric - all’s well– If answer is a code (but come with text
representation) – not perfect, OK
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LOINC standard for codes• First meeting – 1994
– Select group of interested parties• Mayo medical laboratories• CORNING MetPath (since merged with SHF to
become Quest)• University of Washington• Indiana University/Regenstrief Institute• University of Utah (Intermountain Healthcare)• Veterans Administration• University of Ghent Belgium
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LOINC Actual• Identifies the observation (OBX3 and OBR4)• The question not the answer• First file distributed April 1995 (6000 terms)• Now 34,000 terms
– Battery structures– Hierarchy– Synonym– Free Mapping and browsing program
• Free for all uses – url: http://www.loinc.org/
McDonald CJ, Huff SM, Suico JG, Hill G, Leavelle D, Aller R, et al. LOINC, A Universal Standard For Identifying Laboratory Observations: A 5-Year Update. Clin Chem 49:4; 624-633
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Medical Records Without Standards
[G]
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The present medical records with standards
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Wishard the oldest and the broadest coverage
• Data beginning in 1972• Since early 80’s
– All laboratory data– All pharmacy (in patient and out) – All dictation– All diagnostic studies ( radiology, cardiac, etc)– Al encounters ( with DX's and procedures etc)– Coded clinical information from largest clinics ( OB and Medicine
and med subspecialty• Since late 80’s
– All- physician entered orders• Recently – Inpatient vitals, MD note entry, etc.
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Standards that support EMRs
Display: courtesy of HTML and IP
standards
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VISIT INFORMATION From registration system
Courtesy of HL7
VITAL SIGNS DATA FROM AUTOMATIC BP- PULSE –
TEMPERATUREcourtesy of HL7
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Chest x-ray 12 bit, 400 x 400 resolution
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Chest x-ray 12 bit, 1024 x 1247 resolution
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Chest x-ray 12 bit, 2048 x 2494 (full) resolution
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Radiology & images courtesy
DICOM, JPEG, and JPEG2000
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Trade offs between JPEG and JPEG2000
• JPEG decodes much faster (5X)• JPEG Compresses “small” images (e.g. CT
and MRI as well as JPEG200• JPEG2000 compresses large films (chest
x-rays) (2000 x 2700) 12 bit depth by 5 x better
• Use JPEG for “small” CT and MRI images and JPEG 2000 for large plain films.
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Echo reports courtesy of HL7
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•Echo images Courtesy of Motion JPEG
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Scanned images
•Courtesy of TIFF
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Telemedicine Courtesy of:
•H232•IPSEC•MPEG 1
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IT is ALL in the Standards
HL7 (most)•DICOM (to capture uncompressed images from PACS•NCDP (Prescriptions from outpatient pharmacy •JPEG , JPEG 2000 for storing clinical images in Clinical
Repository•IP (Everywhere)•JPEG, MPEG 1•Code Standards Currently Used:
– CPT– ICD– LOINC– CDO-3
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Guard Rails• Improve preventive care from 30% to 400%
over control state (1)• Improve drug dosing and reduce errors in
drug prescribing• Increase required corollary orders 5%-64%
(e.g. test Vancomycin levels when giving Vancomycin)
1. McDonald CJ, Hui SL, Smith DM, Tierney WM, Cohen SJ, Weinberger M. Reminders to physicians from an introspective computer medical record. Annals of Internal Medicine 1984; 100:130‑138. 2. Overhage JM, Tierney WM, Zhou XH, McDonald CJ. A Randomized Trial of “Corollary Orders” to Prevent Errors of Omission. JAMIA 1997;4:364-375.
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Preventive Reminders
0102030405060708090
Occult BloodCervical PapHematocritChest XrayPneumovaxTB Skin TestSerum K
Mammography
Flu ShotDiet
ReticulocytesFE/TIBCDigitalis
Liver Enzymes
AntacidsControlStudy
McDonald, et al. Reminders to Physicians from an Introspective Computer Medical Record.
Annals of Internal Medicine, 1984;100:130-138.
Perc
ent R
espo
nse
[RG]
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Physician Order entry- (POE)
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Computer based POEGopher order entry
• Were first to succeed with order entry– 20 million orders at Wishard since 1986
• POE provides better options for delivering influencing patient care
• Even non fixed (not patient specific) content can have an effect
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Gopher physician Users
CHF example
Cost Savings
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Preventive POE inpatient POE reminders 2001
(Dexter et al.)
36%
0.80%
51%
1%
32%
19%
36%
27%
0%
10%
20%
30%
40%
50%
60%
pnevx flu shot SQ Hep ASA
reminderscontrol
Dexter PR, Perkins S, Overhage JM et al. A Computerized Reminder System to Increase the Use of Preventive Care for Hospitalized Patients. N Engl J Med 2001;345:965-970.
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City Wide RMRS Functions• CARE deliver clinical information when needed
for emergency care (NLM supported study)• Public health seek out reportable conditions
from laboratory data evidence, equivalence duplicate cases, organize and deliver to public health
• Research molecular biologic epidemiology through Pathology samples ( National Cancer institute
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Whole city• About 1.3 million people • Five hospital systems and their clinical facilities • Fourteen separate hospital facilities• All four homeless care clinics• 450 K emergency room visits per year• State and county public health• Three uses of community data repository
– Direct patient care– Public health– Research
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State Board of Health
County Health Department
Quest
LabCorp
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INPC all 5 city institutions
# HL7 message streams 149
# NCPDP streams#DICOM streams
12 (Agfa PACs, GE PACs)
# rows/observations stored 436 million
# text reports stored 11, million
# CPOE orders stored 22 million (est)
# radiology images stored Studies= 1 million images=50 million (est)
# EKG tracings stored 480 thousand
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Clinical use
• At Wishard and Clarian total of 2.5 million accesses per monthby more than 4000 different clinical users
• Emergency Department physicians can look at records from all institution as one merged record when patients present at the Emergency department
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Monthly volumes
# HL7 messages per month 5,491,882 # OBX results per month 5,803,541 + ___
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Uses in public health (all based on HL7 messages)
• Automatically scan HL7 lab messages for reportable disease– Look at test code– Look at normal flag *– Look at result– Send those that =>reportable condition
• Faster by 8 days, more complete by 2 fold• Immunization reporting• Tumor registry
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Reportable disease example
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Outcomes• Reliable
– Real time delivery– 100%received (for participants)
• Reporting completeness (capture/recapture)– Found nearly twice as many cases from the index
hospitals as found by the usual methods• Reporting timeliness (versus result date)
– 8.4±15.4 days faster than HD – case finding– 1.4±2.0 days faster than hospital case finding
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INPC Use in research
• Help in writing and planning grant applications– How many patients of a given kind are
available in the database– What are their characteristics
• Help in recruiting patients to clinical trials (see next slide)
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Use in research – grist for epidemiologic studies
• Mahon BE, Rosenman MB, Kleiman MB. • Maternal and infant use of erythromycin
and other macrolide antibiotics as risk Factors for infantile hypertrophic pyloric stenosis.J Pediatr. 2001 Sep;139(3):380-4.
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Research – Shared Pathology Informatics Network (SPIN)
• Pathology departments store tissue as paraffin blocks for 10-15 years
• Protein, DNA and even MRNA can be identified in these specimens
• Clinical repository can identify cancer patients with specific characteristics– E.g. short and long survivors of small cell lung cancer
• Can get from the record to pathology report and the tissue blocks to answer biologic questions
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Research SPIN
• Auto coding of pathology reports• Free text searching of pathology reports• Peer-to-peer links between many nodes
– Boston– Pittsburgh– UCLA– All hospitals in Indianapolis
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Future• Don’t think we will see monoliths every where.
Rather, message coupled systems• For every system pushed into monolith 1-2 new
ones pop up at our institution.– Prosolve cardiac echo– Witt cath lab system– _____Endoscopy system– Otter transplant system– ______ ICU system
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Future
• Strong common/replicated master files– Patient master ( Easy in GB)– Provider master ( may be described in dec 03)– Orderables master– Result master– Geographic location master – Printer locations
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Evidence based coding
• Selected structured data collection• Hopefully – evidence based • We need to find out which variables are
predictive or decisive– Stiels Ottawa Ankle Rule
• Narrative continues to reign
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Leap in amount of non-structured non text data
• Digital voice– Speech understanding ( has to be successful
some time.• Photos• Video – record the whole encounter
(Charlie Safran)• Scanned documents (To get totally
electronic record )
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Predictions
• Preempt disease rather than perfect desperation care– Empty the hospitals– A major disease, e.g diabetes will be cured
• Community-based clinical systems
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Wireless- everybody, everywhere to everyplace - (WEEE)
• Clinical data and info services as available as the air– Real time alerts and updates to Provider carried
systems – Hi-grade video conferencing between provider and
patient.• More care in lower acuity settings, Home health care replaces
other forms if more care shifted to lower acuity settings– Wireless patient monitoring direct to provider systems– Image reading (radiology, pathology) from afar
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Evidence based coding
• Hopefully – evidence based data collection• First determine which variables are
predictive or decisive in guidelines• Stiels Ottawa Ankle Rule• Miles to go before mostly coding
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Leap in amount of non-structural data
• Digital voice– Speech
• Photo and video – record the whole encounter (Charlie Safran)
• Scanned data
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Some Observations
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The Keyboard Lives• For order entry and note writing is the
fastest entry mechanism available– Faster than mousing– Faster than hand writing recognition– Faster than thumb typing (but it is faster than
hand writing recognition• All new MDs can type.
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Paper lives
• Input: you can’t avoid scanning documents if you want a complete record
• Output: 1 trillion laser printed pages n 2001, printer vendors predict 6 trillion pages in 2006
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Paper lives
• Paper generated by computer may be with us
forever• Paper is Light weight and portable• Extra-ordinary resolution
– Best UXGA 1600x1200– Page (@ 2400 dpi) 18,000 x 24,000
• Printers getting cheaper and better all of the time • Easy to annotateI
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The prefect PDA or “carried computer” not here yet
• Screen too small• Lacks a keyboard – the king of input• Most clinical applications need wireless
connection• But battery life too short (or box too big
when battery adequate )
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Our wireless invention: The Popcorn Man’s “PDA”
[RR-Input]
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Radio LinkTablet Computers
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Tomorrows Cyborg wireless
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Ski mask wearable computer
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Cool wearable computer