achieving clinical transformation with an interoperable...
TRANSCRIPT
Achieving Clinical Transformation with an Interoperable Health IT
InfrastructureApril 12, 2015
Stanley M. Huff, MD CMIO, Intermountain Healthcare
DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.
Conflict of Interest
Stanley M. Huff, MD
Has no real or apparent conflicts of interest to report.
© HIMSS 2015
Learning Objectives
• Describe how quality measures, accountable care, and other models of advanced healthcare enable clinician transformation.
• Illustrate standard based infrastructure models, including Fast Healthcare Interoperability Resources (FHIR) profiles, that enable the development and use of interoperable applications in healthcare.
• Demonstrate real projects underway at a ‘healthcare transformation lab’ that are supporting an interoperable health IT infrastructure.
Acknowledgements• Lee Pierce• R. Scott Evans• Brent James
Intermountain Healthcare ProfileAn Integrated Health System
5
1975 1983 1994
• 22 hospitals • 33,000 employees• 22 hospitals • 33,000 employees
• 600,000 members• 25% market share• 600,000 members• 25% market share
• 200 clinics• 1,000 employed
physicians
• 200 clinics• 1,000 employed
physicians
MEANINGFUL USE
Positive Effects of MU• We got money – a net of ~$29 million so far• More physicians used the system
– From 6% to 89% of physicians meeting all measures
– From 10% to 86% with electronic orders– From 61% to 92% with coded problems
• CPOE and ePrescribing development were accelerated
• A more robust infrastructure for health information exchange
Unexpected consequences•Formulary checking•Problems with “no problems”• Immunization interface•Finding denominators•Delay of other more valuable projects
A Retrospective Opinion• Knowing what we know now…• And if we were not under the threat of increasing penalties…
• We probably would not have pursued the MU incentives…
• And our patients would be receiving better care and our clinicians would be happier
From the Office of the National Coordinator
“We are not the office of meaningful use.”
Beyond Meaningful Use
Suggested Strategy• Develop truly interoperable data exchange
standards– We need development to get to truly
interoperable standards; everything we need does not exist today
• Certify messages and services (not applications)• Mandate the use of the standards• Hold people accountable for outcomes (not process
measures)
Intermountain’s Core BusinessPerfecting the Clinical Work Process
Intermountain’s Core BusinessPerfecting the Clinical Work Process
Foundational LeadersDr. Homer Warner
– Medical informatics founder– 1950s – computer assisted
CV decision support– 1970s – HELP system
developed
Dr. Brent James
– CQI - Standardization of clinical care through data analysis
Intermountain’s Clinical Programs
• Aligns care team in the process of care (9 Clinical Programs)
– Physician specialists– Nurses– Data experts– Administrators– IT– Other caregivers
• Develops, implements, and sustains evidence-based care using information systems and data
• Goal is to deliver the best care to every patient every time
16
Transforming Patient Care
Decision Support
Improved CareIdeas
Research
DataDataPatientCare
PatientCare
ActionAction
InsightInsightEDWEDW
ClinicalClinical FinancialFinancial
ClaimsClaims Pt. SatisfPt. Satisf
DeviceDevice & More& More
Data IntegrationData Integration
OTHERS
EDW Conceptual Architecture
Data SourcesInternal
External
Data AccessEnterprise Data Warehouse
BI ToolsEMR
Pharmacy
Claims
Lab
Finance
State/Federal
SO
UR
CE
Dat
a M
arts
SU
BJE
CT D
ata Marts
Master Reference Data
EMREMR
Patient AcctPatient Acct
ClaimsClaims
Primary CarePrimary Care
Women & NewbornWomen & Newborn
AHRAHR
Surgical ServSurgical Serv
Supply ChainSupply Chain
CardiovascularCardiovascular
Patient Sat.Patient Sat.
Data Warehouse Profile 15 TB Oracle Data Warehouse ~9000 queriable tables ~150,000,000 queries per month 95,000,000,000 rows of data
40 FTEs 29 data architects (data input) 11 business intelligence
developers (data for reports) Coordination with clinical and
business areas
Case Studies
Elective Induction CPM
Per
cent
<39
Wee
ksElective Labor Induction <39 Weeks
Elective Induction CPM
Elective Induction CPM
Per
cent
<39
Wee
ks
0%
5%
10%
15%
20%
25%
30%
35%
J1999
FMAMJJASONDJ2000
FMAMJJASONDJ2001
FMAMJJASONDJ2002
FMAMJJASONDJ2003
FMAMJJASONDJ2004
FMAMJJASONDJ2005
FMAMJJASONDJ2006
FMAMJJASONDJ2007
FMAMJJASONDJ2008
FMAMJJASONDJ2009
FMAMJJAS
Month
Elective Delivers <39 Weeks
Colon Surgery: Evidence Based Interventions and Associated Measures
Intervention MeasurePatient Education EnrollmentEarly Mobilization After Surgery
Activity – PT / Nursing walking, transfers, etc.
Appropriate IV Fluid Admin Fluid AdministrationNarcotic Sparing Analgesia Med Administration, Morphine
EquivalenceEarly enteral nutrition Diet Administration
Bowel/Emesis/Flatus Financial Measures
26
Colon Surgery Care Process Report
27
Colon Surgery Care Process - Financials
28
Colon Surgery
• Results: $1.2 million annual savings, LOS decreased from 8.44 to 6.75, while maintaining or improving clinical quality
• 2010 Computerworld Business Intelligence Award – Driving Process Change with BI
• Lack of evidence-based medicine
• Hospitals and physicians are paid for
volume
• Patients are (far too often) not
engaged
Care Delivery in the US: Three Problems…
Massive over utilization
Massive over utilization
Lead to…
Shared Accountability Goals
Goals: 1.Better care (for patients); 2.Better health (for the population we
serve);3.Sustainable costs (for patients and
other payers).
Pro
vide
Evi
denc
e-ba
sed
Car
e
Alig
n In
cent
ives
Eng
age
Pat
ient
s
© Intermountain Healthcare, 2013
FFS PHMFFS PHM
Business Model Implications
Payment Model ImplicationsProviders will be paid for “value”
• Efficient delivery• Efficient utilization• Prevention • Wellness
These become “part of the job”
Physician Payment Model Beta
Current Model – FFS
Beta Payment Model
Service
Qua
lity
Total Cost o
f Care
Prod
uctiv
ity
Quality: Performance Measures
Quality: Patient List
Cost: Population-Based Measurement
Service
Population Health: Patient-Level Detail
STANDARDS BASED SERVICES FOR SHARING DATA, APPLICATIONS, AND ADVANCED DECISION SUPPORT
Decision Support Modules
• Antibiotic Assistant• Ventilator weaning• ARDS protocols • Nosocomial infection
monitoring• MRSA monitoring and
control• Prevention of Deep
Venous Thrombosis• Infectious disease
reporting to public health
• Diabetic care• Pre-op antibiotics• ICU glucose protocols• Ventilator disconnect• Infusion pump errors• Lab alerts• Blood ordering• Order sets• Patient worksheets• Post MI discharge meds
We can’t keep up!• We have ~150 decision support rules or modules
• We have picked the low hanging fruit• There is a need to have 5,000 decision support rules or modules
• There is no path from 150 to get to 5,000 unless we fundamentally change the ecosystem
HSPC Mission Statement
Improve health by creating a vibrant, open marketplace for
healthcare applications
CommercialEHR
CommercialEHR
Heterogeneous Systems
Home GrownSystem
Home GrownSystem
SystemIntegratorSystem
IntegratorVA
SystemVA
System
Applications Being Built• Neonatal Bilirubin Protocol• Pediatric Growth Chart & BP Centiles• Pulmonary Embolism Protocol• Problem Management
What other kinds of Apps are likely to appear?• Decision support
– Complex or evolving logic– Visualization
• Patient -- Provider data sharing– Simultaneous provider’s view & patient view
• Integration of external data into EHR workflow– Population Health – bilateral data flow– “Real time” HIE integration
• National scale services– Genomics (Smarter ordering, PGX, etc.)
• mHealth / mobile apps– Connecting consumer apps to their EHR data!– Counterpart to Apple’s HealthKit?
• Informatics Research– Clear IP rights (vs. source code approaches)– Local or multi-site
Apps that address specific focused problems…
• Provider-facing services– Focused decision support– Visualization– Disease management– Specialty workflows
• National Shared Services– Genomic testing & CDS– Pharmacogenomic screening– CDC Ebola screening?– CDC immunization forecaster– Prior Authorization / Appropriateness
App 1
EHR
App 2 App 3
Like Google Maps…
Apps that enable data sharing…
• Next-gen Interoperability– Population Health integration– HIE integration– Data capture for research– Clinical Trial recruiting
EHR2
App 1
EHR3
EHR1
Like Facebook…
Apps that empower patients / consumers…
• Apps as Prescriptions– Chronic disease
management– Pt-Provider Communication– Remote monitoring– Outcome capture & Clinical
Effectiveness Monitoring
SMART Phone App
Pop HealthEHR
Like ???? …
Questions
Stanley M. Huff, MDChief Medical Informatics OfficerIntermountain HealthcareSalt Lake City, [email protected]
Appendix
Current Situation• Each EHR vendor uses proprietary models and terminology to
represent clinical data– Some standardization of codes is now occurring, but– Data is not consistent vendor to vendor, or even organization to
organization within the same vendor• This means that:
– Sharing of data is difficult– Sharing of executable software across vendors is impossible– Each useful application is created or re-created on each
different platform– There are unmet needs for health care applications and
decision support– Software costs are higher than they need to be
Characteristics of a new Ecosystem• Consistent and unambiguous data collection• Data stored and accessed through truly semantically interoperable services
• Sharing of data for direct patient care, population based analytics, and research
• Sharing of applications, executable clinical decision support and knowledge
IsoSemantic Models – Example of Problem
e.g. “Suspected Lung Cancer”
(from Dr. Linda Bird)
Data Comes in Different Shapes and Colors
Finding – Suspected Lung Cancer
Finding – Suspected CancerLocation – Lung
Finding – CancerLocation – LungCertainty – Suspected(Let’s say this is the preferred shape)
Data Standardized in the Service
Shape and color of data in the local database
Shape and code translation
Application
Data in preferred shape
Applicationand User
Partial Interoperability
TermTranslators
Standard Terms(Non-standard Structure)
Applicationand User
Application
Local databases,CDA, HL7 V.2, etc.
Preferred Strategy – Full Interoperability
Local databases,CDA, HL7 V.2, etc
Term andStructureTranslators
Application
Standard StructureAND Standard Terms
(As defined by CIMI Models)
Applicationand User
Req
uire
men
ts
Reasons to do it on the server side• Person writing the translation is most likely to understand the
meaning of the data in their own database.• The person writing the translation only has to understand their own
data and the preferred model.– They can optimize query execution for their own system
• The query for the data is simpler. If the application has to write a query that will work for all shapes, the query will be inefficient to process by every system.
Different Physical EHR Implementations
Services based onFormal, Logical
Models
Applications, including advanced decision support,
protocols and guidelines using
Standard Services
http://smartplatforms.org/smart-on-fhir/
FHIR – The “Public API” for Healthcare?
FHIR = Fast Health Interoperability Resource– Emerging HL7 Standard (DSTU 2 soon)– More powerful & less complex than HL7 V3
ReSTful API– ReST = Representational State Transfer – basis for Internet Scale– Resource-oriented rather than Remote Procedure Call (nouns > verbs)– Easy for developers to understand and use
FHIR Resources– Well-defined, simple snippets of data that capture core clinical entities– Build on top of existing HL7 data types– Resources are the “objects” in a network of URI reference links
FHIR: Core Resources (99 in DSTU2)
• AdverseReaction• CarePlan• Condition• Device• DiagnosticOrder• DiagnosticReportt• Encounter• FamilyHistory• ImagingStudy• Immunization
• MedicationAdministration• MedicationDispense• MedicationPrescription• Observation• Order• Organization• Patient• Practitioner• Procedure• More….
# 64
HL7 FHIR Resources and Profiles
Observation
Lab Obs Patient Obs Family Hx Obs
Qn Lab Obs Titer Lab ObsQual Lab Obs
Hematocrit Serum Glucose Urine Sodium
FHIR Resource
FHIR Profiles
Invariant Profile Structure – CIMI Leaf Node Content
The Risk – competing proprietary FHIR profilesWomen, FHIR, and other Dangerous Things
EHR as Platform: Market Forces
“EHRs are becoming commodity platforms. The winner will be the EHR vendor that provides the best platform for innovation – the most open and most extensible platform.”
--- CEO of a major IDN
• Self determination – ability to meet own needs• Desire for vendor independence• Don’t want to rely on proprietary extensions or process• Need clean separation of IP rights (commercialization)
EHR as Platform: Government Forces
• Use “atomic” data elements, not just documents• Require EHRs (vendor/provider) to expose “open”
APIs
• Dismissive of current (MU1 & MU2) efforts• Design systems for research uses, not just clinical care• Focus on “Apps” not monolithic solutions• Give the patient more control over uses of his data
JASON Report: “A Robust Health Data Infrastructure”
JASON Task Force –Recommendations
• A Coordinated National Architecture– Modeled on Internet principles (loose coupling) for scale
• Data Sharing Arrangements (DSA) for governance• All EHRs should deploy a “Public API”
– Implement “Core Data Services & Profiles” – FHIR– Expectation to deploy the API – Permit non-discriminatory access to the API
• API becomes part of CEHRT• Measures and transparency for usage of the APIs
The Healthcare Services Platform Consortium (HSPC)
Sample of Participants
• HL7 FHIR – Grahame Grieve• SMART – Josh Mandel• Cerner – David McCallie, Marc
Overhage• Epic – Janet Campbell• VA – Jonathan Nebeker, Paul
Nichol• openEHR – Thomas Beale • Open Health Tools – David
Carlson• Harris – Vishal Agrawal• Intermountain Healthcare• Systems Made Simple – Viet
Nguyen• LSU – Frank Opelka, Wayne
Wilbright, John Couk
• Center for Medical Interoperability – Todd Cooper
• RelayHealth – Arien Malec• NLM – Clem McDonald• Infocare Healthcare – Herb
White• Mayo Clinic – Cris Ross• Clinical Architecture – Shaun
Shakib• Cognitive Medical Systems –
Doug Burke• IBM – Jeff Rogers, Dennis Leahy• ASU – Aziz Boxwalla, Robert
Greenes• Regenstrief Institute – Douglas
Martin
Essential Functions of the Consortium
• Select the standards for interoperable services– Standards for models, terminology, security, authorization, context sharing,
transport protocols, etc.– Modeling: SNOMED, LOINC, RxNorm – FHIR Profiles – do it together– Publish the models, and development instructions openly, licensed free-for-use
• Provide testing, conformance evaluation, and certification of software– Gold Standard Reference Architecture and its Implementation– We will work with an established company to provide this service– Fees that off set the cost of certification will be charged to those who
certify their software
• Implementation of the standard services by vendors against their database and infrastructure
– Everyone does not have to do every service– There must be a core set of services that enable a marketplace
HSPC wiki• https://healthservices.atlassian.net/wiki/display/HSPC/Healthcare+Se
rvices+Platform+Consortium
72
73
Open Is Happening
Boston Childrens: SMART Growth Chart
SMART Growth Chart – Parent’s View
Intermountain: SMART Neonatal Bilirubin Alerts
77
Commercial: VisualDX
78
Commercial: VisualDx