0. Precision Medicine Task Force
Task Force Meeting
March 16, 2016
Leslie Kelly Hall, Co-Chair
Andy Wiesenthal, Co-Chair

1. Agenda Call to Order/Roll Call Welcome, Opening Remarks
Presentations from Subject Matter Experts
Department of Veterans Affairs (VA)
Department of Defense (DoD)
Q & A
Recap & Next Steps
Public Comment
Adjourn

2. Precision Medicine Task Force Members
Organization
Co-Chairs
Leslie Kelly Hall
Healthwise
Andrew M. Wiesenthal
Deloitte Consulting, LLP
Members
Gil Alterovitz
Harvard Medical School
Dixie Baker
Martin, Blanck, and Associates
Mary Barton
National Committee for Quality Assurance (NCQA)
Steven Keating
MIT Media Lab and Mechanical Engineering
David McCallie, Jr.
Cerner Corporation
Matthew Might
Harvard University
Andrey Ostrovsky
Care at Hand
Ketan Paranjape
Intel
Eric Rose
Intelligent Medical Objects
Joyce Sensmeier
Healthcare Information and Management Systems Society
Federal Ex Officio
James Breeling
Veterans Health Administration (VHA)
Christina Heide
Department of Health and Human Services / Office for Civil Rights
Betsy Humphreys
National Library of Medicine (NLM)
Mitra Rocca
Food and Drug Administration (FDA)
Jon White
ONC
ONC Staff
Maya Uppaluru
ONC – Federal Staff Lead

3. ONC Role in Precision Medicine Initiative
Accelerate opportunities for innovative collaboration around pilots and testing of standards that support health IT interoperability for research
Adopt policies and standards to support privacy and security of cohort participant data
Advance standards that support a participant-driven approach to patient data contribution

4. Task Force Charge
Identify opportunities for ONC to support our federal partners’ PMI efforts and related health IT/interoperability challenges, including National Cancer Institute, Food and Drug Administration, National Institutes of Health, and Department of Veterans Affairs.
Identify opportunities for ONC to collaborate with industry and pilot the use of standards to enable data donation and patient access through APIs using standards such as FHIR and OAuth 2.0.
Identify standards for uses cases to support interoperability of data types that are critical to PMI-type research and prioritize piloting the exchange of those data types based on a phased approach, that would incorporate most structured/coded data first and add additional data types in subsequent pilot phases.

5. Interoperability Pathways Critical to PMI
Minimum data set, Standards, APIs, and recommendations to facilitate interoperability
Lab
EHR
Patient
EHR
EHR
Research
Lab
Patient

6. Precision Medicine Task Force Workplan
Meetings
Task
Friday February 12, :00 AM-11:00 AM
Progress and status of current initiatives
NCI – PMI-Oncology
FDA – Precision FDA needs to harmonize data standards
Friday February 26, 2016
1:00 PM - 2:30 PM
ONC – Computable Consent
NIH – Precision Medicine Initiative Progress & Sync for Science pilots
Recap and discussion of issues to explore from other agencies 
Wednesday March 16, 2016
1:00 PM-2:30 PM
Sync for Science discussion: What are the best FHIR resources to prioritize? (e.g., meds, labs, careplans, diagnoses)
Lab data interoperability/patient access gaps
VA / DOD
Wednesday March 30, 2016
FDA focus
Patient rights and ownership of genomic pattern data
Wednesday April 13, 2016
Demographic data: what still needs to be done to improve structured data around race, ethnicity, gender, sexual orientation? What are the highest priority demographic data types for PMI?
What specific activities or pilots ONC lead to support / advance progress?

7. Precision Medicine Task Force Workplan (continued)
Meetings
Task
Thursday April 21, 2016
1:00 PM-2:30 PM
VA/DOD focus
Wednesday, May 4, 2016
9:30 am - 12:00 pm
Draft Recommendations to HITSC
Wednesday May 11, 2016
NCI focus
Wednesday May 25, 2016
Discussion of final recommendations
Friday June 3, 2016
2:00 PM-3:30 PM
Wednesday, June 8, 2016
Final recommendations to HITSC

8. Questions to Presenters
What is your agency’s specific mandate and contribution to the Precision Medicine Initiative?
Which data types are of the highest priority for your PMI-related work?
What is the minimum data set required for your PMI work?
Please share challenges or questions related to health IT standards, interoperability, and data exchange that the PMTF could address to advance your work. For example:
What existing health IT standards are you using in your PMI projects?
Are there challenges to working with those standards, or gaps that should be filled?
Are there existing standards you might consider working with if they were modified or improved in some way? What improvements or changes would you recommend?
Are there areas where you are exchanging data but robust standards don’t exist? What are the practical implications of standards gaps that your agency/stakeholders face?
What pilots could be launched to enhance technical capabilities related to data standardization, data donation or transfer (i.e., interoperability of precision medicine data)?

9. Department of Veterans Affairs Million Veteran Program
James Breeling, MD
VHA Office of Research & Development
Director - Bioinformatics

10. PMI-MVP: Bottom Line Goals
Continue enrollment to at least a million by 2020
Internal VA decision to ‘keep on going’ after reaching 1M
Expand secure and agile computational capacity to serve >1000 simultaneous VA and non-VA users by 2020
Safe/secure, CLIA-compliant biorepository with back-up
Establish mechanisms to return results responsibly to:
providers and EHR
participants
Improve health of Veterans and general public
through Precision Medicine

11. MVP Accomplishments to Date
Enrolled over >450,000 Veterans, at a current rate of ~100,000/year
DNA analyses completed:
SNP genotyping on 400,000 DNA samples (200,000 with quality control/curation)
Exome sequencing on ~30,000 , Whole genome sequencing on ~2000
Established 2 public-private partnerships (Lockheed Martin, Seven Bridges) through cooperative research and development agreements (CRADAs) to define security, identity authentication and computational architecture requirements to scale up data access to researchers nationwide
Exploring federal and academic partnerships (DOE, Stanford)
Initiated 3 alpha-test and 5 beta-test scientific projects to demonstrate early scientific utility and test the computing infrastructure needs for scaling up
Alpha: schizophrenia/bipolar disorder, PTSD, Gulf War Illness
Beta: multi-substance abuse, cardiovascular disease, metabolic disease, chronic kidney disease and age-related macular degeneration (AMD)
Published three scientific papers in peer-reviewed journals

12. Active funded MVP Projects
Type of Project
Topic
Affiliations (VA sites not listed)
Alpha test
Schizophrenia and Bipolar Disorder
(CSP#572)
University of Miami; Mt. Sinai School of Medicine; Yale; Harvard; Stanford
PTSD in Veterans (CSP#575B)
UC San Diego; Yale
Gulf War Illness (CSP#2006)
Duke, Yale
Beta test
Cardiovascular Disease
Emory; Harvard; Boston University
Chronic Kidney Disease
Vanderbilt; University of Tennessee Health Science Center
Cardio-metabolic Disease
University of Pennsylvania; Stanford; Albany Medical College; University of Massachusetts; Harvard; Arizona State University
Multi-substance Abuse Disorders
Yale; University of Pennsylvania
Macular degeneration
Case Western Reserve

13. MVP Enrollment Update
Status as of March 7, 2016 • invitations mailed 3,500,824 • baseline surveys returned 546,267 • distribution of appt & walk-in 47% & 53% • consent forms (& blood) 458,229 • crude enrollment rate 13.0%

14. MVP Enrollment Sites

15. Data Types: Chemical Analysis

16. Health IT: VA Analytic Ecosystem
REGION 1
REGION 2
REGION 3
REGION 4 Vx Vy Vn R2 Vx Vy Vn R1 Vx Vy Vn R4 Vx Vy Vn R3
CDW GP BI AN RD FR
CDW System Facts:
Source system:
VISTA: 130
Other Major Systems: 7
Extract tools:
VISTA NRT Journal Reader
VISTA Batch Extractor
Data facts:
Domains of information:
Rows of data: billion
Columns of data: 22,000+
Tables of data: 840+
Data quality program
Active Users: 30,000/Month
Vibrant user community
CDW Sample Data Facts:
Unique Veterans: 20 million
Outpatient encounters: 1.6 billion
Inpatient admissions: 9 million
Clinical orders: 3.2 billion
Lab tests: 5.6 billion
Pharmacy fills: 1.5 billion
Radiology procedures: 162 million
Vital signs: 2.3 billion
Text notes: 2.0 billion
Enterprise
CDW Analytic Enclaves:
GP: General Purpose
BI: Business Intelligence
AN: Analytics and Informatics
RD: Health Services R&D (VINCI)
FR – Field Reporting
CDW Analytic Capabilities:
Primary/Secondary/Data Mart Structures
Data Standardization
Metadata Services
Business Intelligence Reporting & Dashboards Tools
Geospatial Mapping Tools and Images
SAS/Grid High Performance Compute Grid
Natural Language Processing Engines
Hadoop Cluster

17. CDW Phenotype Data Domains
Patients: 22 M
Lab Results
7.7B
Clinical Orders
4.5B
Immunizations
71 M
Appointments
1.4B
Pharmacy Fills
2.2B
Clinical Notes
3.2B
Health Factors
2.2B
Encounters
2.4 B
Radiology Proc
202 M
Vital Signs
3.3B
Consults
315 M
Admissions
17 M
Surgeries
14 M
Oncology
1.3 M
CDW has 68 data domains

18. Data Types: Phenotyping
Dependency on VINCI development, OMOP and NLP tools
Automated/semi-automated interface with VINCI

19. HPC Genomic Analytic Environment
Access Authorization by Governance System
OCR Vendor
Molecular Analysis Labs
Query
Mart
Aggregate Query Portal
Analysis
Environment
Consent Manager
Study Mart
GenISIS
Warehouse
Honest
Broker
VA/
VINCI
Non VA
Clinical Data
NDI, Registry
Survey Data
Molecular data
Researcher

20. High Level Architecture of Genomics HPC

21. MVP ‘Ecosystem’ of Partners
Industry Partners
Academic Partners

22. Industry Partner Deliverables
Role
Deliverable(s)
Lockheed Martin Healthcare
IT integrator
MVP security architecture; improved federal partner interoperability; cohort selection tools
Seven Bridges
Genomics analysis pipelines and applications
Hybrid cloud development; genotype-phenotype graph analysis
Google Genomics
Genomics analyses
Next generation sequencing analyses

23. Academic Partner Deliverables
Role/Deliverable
Stanford
Genomic pipeline and analysis
Yale
Johns Hopkins
Genomics computation
U Maryland
UMIACS
MAX
Advanced computer science
networking

24. MVP participation available to all Veterans and DoD
PMI-MVP: Improve the health of Veterans and general public through Precision Medicine
MVP participation available to all Veterans and DoD
State-of-the-art, high capacity (>1000 users), and secure computational environment
Expand MVP data access
VA Investigators
Consent
HIPAA
Surveys
Veterans
MVP
Participants
EHR/VINCI
Non-VA Investigators
DoD
DNA
plasma
Sequence
GenISIS
State-of-the art and secure
bio-repository
Scientific discoveries and publications
Return results to providers, EHR and participants
(CLIA collection/storage, clinical decision support and genetic counseling)

25. The 7 Principle Health Pillars Translating Science to Clinical Care
Financing
Program Management
Storage + Compute + Networking + Privacy & Security
Sequencing Operations
Analytics
Reporting / Dissemination
Systems Integration
HORIZONTAL CAPABILITIES
Pharmacogenomics
Population Health Screening
Carrier Testing
Rare Disease Diagnosis
NGS-informed cancer Care
Chromic Disease management
Wellness / Performance Training
Health System VERTICAL Pillars
Quantifiable Clinical Benefits
Positive Economic Outcomes
Obvious Personal Utility
Hallmarks of Successful Programs:

26. Veterans Infrastructure for Personalized Medicine
Bio Bank
Sequencing
Genomic Case Repository
Phenotypes
EMR
Data
Scalable Study Frameworks/APIs
Knowledge bases
VALUE CREATION
Data Sharing
& Collaboration
Data &
Infrastructure Access
Validated
Predictive Models
Discovery
Development
Deployment
National Science
Programs
Research &Development
Activities
Public Health
Genomics
Disease Gene Discovery
Understanding Genetic Variation
Translational Medicine
Predictive Models of Risk
Biomarker validation
Diagnostics Development
Adaptive Clinical Trials
Drug Development
Pharmacogenomics Reports
Prenatal Testing / Carrier Screening
Personalized Cancer Therapy
Chronic Disease Management
Wellness Guidance

27. Demonstrations of Interoperability
DAVINCI
Research program aimed at bringing selected health IT domains from DoD to VA
Will use to assist phenotyping for suitable patients.
VA-DoD Interagency Agreement for the Millennium Cohort
Consented data from ~201,000 active duty
~118,000 have transitioned to VA care
~4,187 already enrolled in MVP
VA-DoD IAA - recruitment of this cohort to MVP
VA-NIH – Interagency Agreement to use MVP to recruit and enroll to the NIH-PMI effort
VA-Department of Energy
Investigating use of DOE facilities to host genotype/phenotype information and explore different computational platforms
Work on security and privacy and access controls
Working on Networking (Internet 2 and/or ESNet) for large scale data transfers
Other Federal partners already working with DOE include NCI, NIH, FDA and CDC

28. Department of Defense (DoD)
Terry M. Rauch, Director of Research & Development Policy & Oversight Office of the Assistant Secretary of Defense (Health Affairs) Defense Health Headquarters

29. The President’s Precision Medicine Initiative
To enable a new era of medicine through research, technology, and policies that empower patients, researchers, and providers to work together toward development of individualized care. 29

30. PMI: VA & DOD partnering
Opening up MVP to active duty men and women who wish to participate
VA/DOD partnership will:
expand research opportunities
Enhance the quality of data available to both VA and DOD
Leverage the natural progression from active duty military to Veteran status

31. The Millennium Cohort Study
Constructed to prospectively assess long-term health among Service members with representatives from all branches of the U.S. Armed Forces including active duty, Reserve, and National Guard members, with follow-up continuing beyond participants’ separation from military service.
Deployment-related investigations of mental and physical health conditions have been completed, including major depression, post-traumatic stress disorder (PTSD), suicide, eating disorders and weight change, alcohol misuse, cigarette smoking, hypertension, respiratory conditions, diabetes, sleep, and mortality. 31

32. The Millennium Cohort Study
Participants are surveyed at approximate 3-year intervals both during and following service.
Approximately 45% of participants were Army personnel, followed by Air Force (29%), Navy (16%), Marine Corps (9%), and Coast Guard (2%) at the time of enrollment. Most participants were on active duty (66%) while the remainder consisted of Reserves or National Guard (34%).
As of March 2015, 62% of participants deployed at least once in support of the wars in Iraq and Afghanistan, with 28% deployed multiple times. In addition, approximately 1,800 participants are deceased (0.9%). 32

33. MVP/MCS Preliminary Work
In order to define the co-enrolled MCS-MVP population, the scrambled birth dates/SSNs across cohorts have been compared. There are 116,777 MCS enrollees who are enrolled in the VA Healthcare System and are eligible for enrollment into MVP (approximately half live within 50 miles of an active MVP recruitment site).
Of these, 4,151 have already enrolled in MVP. A total of 34,747 first invitational MVP mailings had previously been sent to the dual enrollees, with 4,748 positive responses and 1,829 opt-outs (30% of the opt-out have agreed to be contacted again in the future). Consistent with the larger MVP cohort, an 8% enrollment rate is demonstrated for participants who respond via mail. 33

34. MVP/MCS Preliminary Work
Work continues to examine the population of available MCS enrollees not enrolled in MVP (N = ~112,000) for recruitment purposes.
Ongoing work comparing the MVP and MCS survey questions to determine content overlap has identified significant commonality across the survey domains and questions, in particular, among military/environmental experiences and health outcomes.
Future plans include potential modification and revision to the surveys for streamlined data collection efforts, as well as validation efforts of the self-report data across studies. 34

35. MVP/MCS Plan
To recruit separated and active duty personnel into MVP, a phased approach will be implemented.
Initial efforts will focus on recruitment of MCS enrollees, and transition to enrollment of active duty military personnel, with recruitment efforts drawing from the approximately 50 VA Medical Centers nationwide and expanding to new DoD-based MVP sites.
We will use existing and modified MVP recruitment strategies to enroll 75,000 active duty and separated military personnel into MVP. 35

36. Phased MVP/MCS Plan
Phase 1 will concentrate on mailings to MCS participants enrolled in VA inviting them to participate in MVP;
Phase 2 will recruit active duty and separated MCS participants into MVP not enrolled in VA;
Phase 3 will recruit non-enrolled MCS DoD active duty personnel at VA MVP sites; and
Phase 4 will recruit DoD active duty personnel at new DoD-based MVP sites. 36

37. Data Coordination
Expand MVP to include non-VA data by obtaining military service and health history from the Department of Defense (DoD).
In addition to supplying the history of deployment and service related exposures/disabilities, the DoD databases provides the unique ability to develop longitudinal phenotypes dating back to enlistment in the armed services.
The framework is in place to handle data movement to and from the secure VA data system to DoD programs. 37

38. Questions
“Medically Ready Force Ready Medical Force” 38

39. Recap & Next Steps