Transcript DIGITizE Update_David Nolen_07.07

Displaying and Integrating Genetic
Information Through the EHR
Action Collaborative
DIGITizE AC
Can We Deploy
Health Information Technology
that Safely Brings the Benefits of
Genetics to Far More Patients?
How Quickly Can We Do So?
Can We Create
Inter-institutional Foundational
Health Information Technology
Infrastructure that Increases the
Power of Genetics
That will be helpful now but also stand the
test of time?
Strategy
• Assemble Stakeholders
• Identify areas of agreement
• Transform into an inter-institutional project
coordination group
Stakeholders
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Government
Providers
Laboratories
Vendors
Patients Representatives
Standards Organizations
Membership
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Sandy Aronson, Partners HealthCare
J.D. Nolen, Cerner
Mark Adams, Good Start Genetics
Gil Alterovitz, Harvard Medical School
Brian Anderson, athenahealth
Jane Atkinson, NIDCR
Larry Babb, Partners HealthCare
Dixie Baker, Martin, Blanck and Associates
Gillian Bell, Moffitt Cancer Center
Chris Chute, Johns Hopkins University
Chris Coffin, Invitae
Mauricio De Castro, U.S. Air Force
Carol Edgington, McKesson
Laurel Estabrooks, Soft Computer Corporation
Robert Freimuth, Mayo Clinic
Geoff Ginsburg, Duke University
Jennifer Hall, University of Minnesota
Stephanie Hallam, Good Start Genetics
Heather Halvorson, U.S. Air Force
Gillian Hooker, NextGxDx
Stan Huff, Intermountain Healthcare
Kristen Janes, Kaiser Permanente
Andrew Kasarskis, Mount Sinai School of Medicine
Anthony Kerlavage, NCI
Deborah Lange-Kuitse, McKesson
Debra Leonard, University of Vermont
Steve Lincoln, Invitae
Ira Lubin, CDC
Elaine Lyon, ARUP Laboratories
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John Mattison, Kaiser
Larry Meyer, VA
Blackford Middleton, Vanderbilt University
Doug Moeller, McKesson
Scott Moss, Epic
James O'Leary, Genetic Alliance
Erin Payne, Northrop Grumman
Brian Pech, Kaiser Permanente
Teji Rakhra-Burris, Duke University
Priyadarshini Ravindran, Allscripts
Mary Relling, St. Jude Children's Research Hospital
Wendy Rubinstein, NCBI
Hoda Sayed-Friel, Meditech
Megan Schmidt, Sunquest Information Systems
Jud Schneider, NextGxDx
Sam Shekar, Northrop Grumman
Brian Shirts, University of Washington
Brad Strock, Epic
Jeff Struewing, NHGRI
Charles Tuchinda, First Databank
Deepak Voora, Duke University
Michael Watson, ACMG
Scott Weiss, Partners HealthCare
Jon White, ONC
Bob Wildin, NHGRI
Ken Wiley, NHGRI
Marc Williams, Geisinger
Grant Wood, Intermountain Healthcare
Identify Areas of Agreement
Framework for Increasing Support for
Genetics in the EHR Ecosystem
PGx Use Case Patterns
Germline Use Case
Patterns
Somatic Use Case
Patterns
Objective
Learn how to work together
while producing near term
benefit for patients
Simple use cases are good for this
Don’t Boil the Ocean
Boil some initial cups while standing on firm ground
Framework for Increasing Support for
Genetics in the EHR Ecosystem
PGx Use Case Patterns
Germline Use Case
Patterns
Initial
PGx Use Case
Types
Specific
Example
Initial
PGx Use Case
Types
Specific
Example
Somatic Use Case
Patterns
Abacavir – HLA-B57:01
• Approximately 6% of patient are
hypersensitive to Abacavir
• Hypersensitivity can produce life threatening
reaction
• Genetic test can predict hypersensitivity
Martin et al, 2012 CPIC Guidelines
Thiopurine - TPMT
• Metabolic effect
• Prescribing too high a dose places patient at
risk for myelosuppression
• Test is required to accurately dose
Reilling et al, 2011 CPIC Guideline
Key Pharmacogenomic
Use Cases Types
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Use Case Types
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Incorporating Genetic Results into EHR User Interfaces
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Adding genetic tests in order sets
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Clinical Decision Support (CDS) identifies when a test
should be ordered (pre-test alert*)
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CDS identifes when a drug order is inconsistent with a
test result (post-order alert*)
* Note pre and post order status refers to the status of the test order as opposed to the drug order
Project Coordination
Example of Cross Institutional
Dependencies
• A use case calls for providers to implement a CDS rule
that requires data from the EHR ecosystem
• To supply the required data, EHR ecosystem vendors
need to receive data from lab system vendors
• To instantiate the required data flows, lab and EHR
ecosystem vendors need better defined standards
• Standards organizations need feedback from lab and
provider organizations to produce needed refinements
The Action Collaborative has the breadth of
membership required to manage these types of issues
Interdependency
Providers
Data
Labs
Interdependency
Providers
Data
Interoperability and functionality
EHR Vendors
LIS Vendors
Supporting
Vendors
Labs
Interdependency
Providers
Data
Interoperability and functionality
EHR Vendors
Cooperation /
Interfaces
LIS Vendors
Supporting
Vendors
Labs
Interdependency
Providers
Data
Interoperability and functionality
EHR Vendors
Cooperation /
Interfaces
LIS Vendors
Supporting
Vendors
Standards and Ontologies
Standards &
Ontology
Organizations
Labs
Interdependency
Providers
Data
Interoperability and functionality
EHR Vendors
Cooperation /
Interfaces
LIS Vendors
Supporting
Vendors
Input
Standards and Ontologies
Standards &
Ontology
Organizations
Labs
Interdependency
Providers
Data
Labs
Interoperability and functionality
EHR Vendors
Cooperation /
Interfaces
Proof of what is possible/helpful
Gov
Agencies
LIS Vendors
Supporting
Vendors
Input
Standards and Ontologies
Standards &
Ontology
Organizations
Interdependency
Funding / Reimbursement Environment that
Makes this Possible
Providers
Data
Labs
Interoperability and functionality
EHR Vendors
Cooperation /
Interfaces
Proof of what is possible/helpful
Gov
Agencies
LIS Vendors
Supporting
Vendors
Input
Standards and Ontologies
Standards &
Ontology
Organizations
The Good News
Providers
Labs
EHR Vendors
Cooperation /
Interfaces
LIS Vendors
Patients
Supporting
Vendors
Standards &
Ontology
Organizations
Gov
Agencies
Lucky Choice in Baseline Rules
• Not dependent on structured variant transfer
• Warn every time potentially desirable
• Existing standards work
Implementation Guide
• Backed by existing
standards (HL7,
LOINC)
• Positioned to
handle FHIRbased resources
• Leverages current
HIT technology
Pilot Teams
• DIGITizE is currently
working with
interested healthcare
organizations who
want to implement
• A pilot team typically
involves organizational
clinical and EMR/LIS IT
staff and an outside
reference lab
Where to Next
• Potential areas
– FHIR-based decision support (aka CDS Hooks)
– Quality-based outcomes
– Content standardization
Questions?