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

Stackholders Government Providers Laboratories Vendors Patients Representatives Standards Organizations

Membership 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 John Mattison, Kaiser Permanente 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

Framework for Increasing Support for Genetics in the EHR Ecosystem Don’t Boil the Ocean Initial PGx Use Case Types PGx Use Case Patterns Germline Use Case Patterns Somatic Use Case Patterns Specific Example Boil some initial cups while standing on firm ground

Abacavir – HLA-B57:01 Approximately 6% of European ancestry patients 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 #Use Case Types 1Incorporating Genetic Results into EHR User Interfaces 2Adding genetic tests in order sets 3Clinical Decision Support (CDS) identifies when a test should be ordered (pre-test alert*) 4CDS 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 Labs Providers Data

Interdependency Labs Providers EHR Vendors LIS Vendors Supporting Vendors Data Interoperability and functionality

Interdependency Labs Providers EHR Vendors LIS Vendors Supporting Vendors Data Cooperation / Interfaces Interoperability and functionality

Interdependency Labs Providers EHR Vendors LIS Vendors Supporting Vendors Standards & Ontology Organizations Data Cooperation / Interfaces Standards and Ontologies Interoperability and functionality

Interdependency Labs Providers EHR Vendors LIS Vendors Supporting Vendors Standards & Ontology Organizations Data Cooperation / Interfaces Standards and Ontologies Input Interoperability and functionality

Interdependency Labs Providers EHR Vendors LIS Vendors Supporting Vendors Standards & Ontology Organizations Gov Agencies Data Cooperation / Interfaces Standards and Ontologies Input Interoperability and functionality Proof of what is possible/helpful

Interdependency Labs Providers EHR Vendors LIS Vendors Supporting Vendors Standards & Ontology Organizations Gov Agencies Data Cooperation / Interfaces Standards and Ontologies Input Interoperability and functionality Proof of what is possible/helpful Funding / Reimbursement Environment that Makes this Possible

The Good News Labs Providers EHR Vendors LIS Vendors Supporting Vendors Standards & Ontology Organizations Gov Agencies Cooperation / Interfaces Patients

Lucky Choice in Baseline Rules Not dependent on structured variant transfer Warn every time potentially desirable Existing standards work

Implementation Guide Rational LOINC Transfer Codes Suggested Rules

Where to Next More Use Cases – Germline – Somatic Structured Variant Transfers Things the community feels we can help with