lessons learned from emerge ii david j. carey, phd weis center for research marc s. williams, md...
TRANSCRIPT
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Lessons Learned From eMERGE II
David J. Carey, PhD
Weis Center for Research
Marc S. Williams, MD
Genomic Medicine Institute
Geisinger Health System
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Why lessons learned?
• Most accomplishments have been reported previously• Participation in eMERGE has contributed to fundamental
changes in approach to research at Geisinger• Areas to discuss
• Biobanking*• Consent for participation*• Phenotyping* • Genotyping/Sequencing• EHR implementation• Return of Results • Patient Engagement in research at Geisinger*
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Clinical Data
ValidatedPhenotypes
GeisingerPatients
BiobankGenomic
Data
Gene-PhenotypeAssociations
Leveraging an Integrated Health System to Create a Translational Genomics Pipeline
Discovery
Clinical Use
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Biobanking: MyCode Project
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• Comprehensive patient and community engagement project
• Central repository of blood, serum and DNA from consented participants
• Broad inclusion criteria for participation; includes pediatric participants (added 2012)
• Samples available for broad research use, including genetic analysis
• Molecular data linkable to GHS clinical data
• CLIA certification of the MyCode DNA biobank pending
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Consented MyCode Participants
As of 6/24/15 80,804 consented
participants
Currently enrolling ~1,000 participants
per week
85.3% consent rate
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Consent for Participation
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• Consenting practices and policies based on patient focus group feedback and survey data
• Opt-in consent and HIPAA authorization
• Participants enrolled during outpatient visit to a GHS clinic (primary care or specialty)
• Soon to pilot use of online and electronic consenting
• MyCode protocol and consent modified in 2013 to explicitly permit return of medically actionable results
• Participants consent to re-contact for follow-up research
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o Phenomic Analytics and Clinical Data Core provides a focal point for research use of GHS clinical data
• models EHR, billing, and administrative data in Geisinger’s enterprise data warehouse and other data sources
• extracts data for use by researchers in a manner consistent with approvals, and de-identifies data when necessary
• develops and validates phenotypes based on this data
• utilizes structured and unstructured data (e.g. via text searching or natural language processing)
o Median length of EHR data for MyCode participants is 12 years, with median of 47 clinical encounters
Phenotyping
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Research Idea
Research Idea
Initial query of
EMR/CDIS
Initial query of
EMR/CDIS
PhenotypeAlgorithmPhenotypeAlgorithm
Execute Algorithm
vs EMR/CDIS
Execute Algorithm
vs EMR/CDIS
Chart Validation
Chart Validation
•Identify informative data elements•Inclusion/exclusion criteria
•Case, control definitions•Excludes
•PPV, NPV
refine
refine
refine
ePhenotype Development and Validation
•Diagnostic and procedure codes•Lab values•Radiology reports •Pathology reports •Dates•Visit type•Progress notes (NLP)
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Genotyping/Sequencing
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Illumina Human OmniExpress Array •3,149 samples•733,202 SNP markers (MAF > 0.01)
Illumina HumanExome Array •7,800 samples •232,125 non-synonymous coding region SNVs•12,459 splice site SNVs•7,012 promoter SNVs•5,325 tag SNPs Illumina Human CoreExome Array •9,684 samples •264,909 tag SNPs•244,953 exome SNVs
Whole exome sequence data•>31,000 samples
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EHR Implementation and Informatics
• There sure are a lot of barriers
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Typical IT Org Chart
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Solutions and infrastructure
Research Informatics
•Research/Clinical liaison
•Research Informatics Core• Data
• Bioinformatics
• High Performance Computing
•Research Informatics Recruitment
• Multiple senior and junior faculty
• Chief Research Informatics Officer
Clinical Informatics
•Chief Medical Informatics Officer under CCIO
• Portion of position charged with research implementation
•Clinical Informatics Fellowship• Approved to start July 2016
• Research component to training
• Developing genomics emphasis
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Additional solutions
• IT governance that includes input from research• Reorganization of informatics structure• Partnership with other organizations
• Penn State• Ohio State• Others
• Active participation in national informatics initiatives and organizations
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Return of Results
• Listen to the voice of the participant
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Majority of focus group
participants
Majority of focus group
participants
Said they wanted any and all results pertaining to their health
Wanted the results returned to them and their clinicians at the same time
And wanted the results deposited in their electronic health records
Revised MyCode Consentpermitti
ng return of results
Revised MyCode Consentpermitti
ng return of results
Approved by Geisinger’s
IRB in October
2013
participant engagementparticipant engagement significant change in consent policy
significant change in consent policy
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MyCode participant engagement
MyCode participant engagement
surveysfocus
groups
semi-structured interviews
deliberative engagement
forums
Participant
experiences of
return of results
Participant
experiences of
return of results
Challenges
concerning
familial implicati
ons
Challenges
concerning
familial implicati
ons
Challenges
concerning
pediatric participa
nts
Challenges
concerning
pediatric participa
nts
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Return of Results
• Details presented tomorrow in workgroup update
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Patient Engagement
• Need to move from patients as subjects to patients as partners
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Identification of outcomes important to patients
Provision of insight on patient decision making
Provision of expertise that clinicians and investigators do not possess: the expertise developed by patients in the course of their experience—of illness and of care
Input on language and cultural issues important in recruitment, dissemination, etc.
the value of patient perspectives
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From the definition of a research topic & the formulation of a study question through the identification of a study population & the selection of interventions, comparators, and outcomes to measure & through the conduct of the study & the analysis of results & culminating in the dissemination of research findings into clinical practice, researchers should ensure patient centered outcome research results accurately and effectively inform health decisions important to patients.
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Revised Strategic
Plan
Revised Strategic
Plan
First “high-level” recommendation: Adopt concept of an enterprise-wide Learning Health System, reflecting a continuous cycle of integrated discovery, innovation, implementation, assessment, and reengineering in all aspects of the combined clinical and research mission, all carried out in the context of community engagement and impact.
Second “high-level” recommendation: Embrace engagement of and partnership with Geisinger patients and others in the Geisinger community and family, as fundamental to all activities of a true Learning Health System dedicated to the transformation of health and health care.
Recommend-ations
Formulated and
Presented
Recommend-ations
Formulated and
Presented
Formation of a Working Group
on Patient Engagement
Formation of a Working Group
on Patient Engagement
January 2014 Research Strategic Planning Retreat
January 2014 Research Strategic Planning Retreat
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Care
Care Improvement
Research and
Discovery
Patients receive
information about
treatment and care
Patients are surveyed for
their opinions
about their care
Patients are informed
about discovery activities
that utilize patient data
Patients are asked about
their preferences
for treatment
Patients serve as hospital
advisors or on advisory
groups
Patients support
sharing of data,
specimens
Geisinger’s Engagement Framework
Treatment decisions are based
on patient preferences,
medical evidence & clinical judgment
Patients co-lead safety and
quality improvement
initiatives
Patients serve as co-
investigators in discovery activitiesPatients
serve as advisors to discovery initiatives
Continuum of engagement
Levels of EngagementConsultation and
Disclosure InvolvementPartnership and
Shared Leadership
Adapted from “Patient Engagement.” Health Policy Brief. Health Affairs, February 14, 2013
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strategies for patient engagement in research and discovery
pre-engagement
pre-engagement
identifying patient
partners & participants
identifying patient
partners & participants
engaging hard to reach communities
engaging hard to reach communities
supporting patient
partners & participants
supporting patient
partners & participants
supporting patient partners in dissemination
& implementation
supporting patient partners in dissemination
& implementation
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Advancing Patient Engagement in Research and Discovery @ Geisinger
Existing and Needed ExpertiseAn Initial Assessment
June 2015
Assessment
Framework(or
model)
Assessment
Framework(or
model)