Lessons Learned From eMERGE II

David J. Carey, PhD

Weis Center for Research

Marc S. Williams, MD

Genomic Medicine Institute

Geisinger Health System

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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3

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

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

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

EHR Implementation and Informatics

• There sure are a lot of barriers

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Typical IT Org Chart

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

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

Advancing Patient Engagement in Research and Discovery @ Geisinger

Existing and Needed ExpertiseAn Initial Assessment

June 2015

Assessment

Framework(or

model)

Assessment

Framework(or

model)