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Informatics-Enabled Community Engagement in the Washington Heights Informatics Infrastructure for Comparative Effectiveness Research (WICER) Project Suzanne Bakken, PhD, RN, FAAN, FACMI School of Nursing and Department of Biomedical Informatics Columbia University 1R01HS019853, R01HS022961
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Informatics-Enabled Community Engagement in the Washington Heights Informatics Infrastructure for

Comparative Effectiveness Research (WICER) Project

Suzanne Bakken, PhD, RN, FAAN, FACMISchool of Nursing and Department of Biomedical Informatics

Columbia University

1R01HS019853, R01HS022961

Community Engagement in Context of the Learning Health Systems

• Building a strong fabric of trust among stakeholders through communication and demonstration of value

• Principles as a foundation for fabric of trust: – Build a shared learning environment– Engage health and health care, population and patient– Leverage existing programs and policies

• Difficulty of building a strong fabric of trust among racial and ethnic minorities – Low participation rates in research studies– Low participation rates in biobanks– Limited use of information technologies for health-related

purposes.

Goals of WICER

• Comprehensive understanding of the Washington Heights/Inwood population

• Facilitate research with this population• Demonstrate infrastructure capabilities for

comparative effectiveness research

Washington Heights/Inwood

• 5 zip codes: 10031, 10032, 10033, 10034, 10040

• Represents significant issues in health care disparities

WICER Components• Research data warehouse - Wilcox • Research data explorer (RedX) and I2B2 for viewing

research data warehouse – Wilcox• Informatics support for recruitment and integrating

clinical and research workflows – Weng• Comparative effectiveness studies – Bigger, Feldman

(Visiting Nurse Service of New York)• Community survey – Bakken, Boden-Albala, Fleck

WICER Data

Coordinator

Researcher

Coordinator

In patient

Out patient

Home care

Long term

Trial

Survey

LocalDatabases

Clinical Encounters

Research Encounters

ResearchData

WarehouseRedX

Integration Platform

ResearchData Access

Data Access Expert

Clinician

Clinician

Clinician

Clinician

Patient

Community Members

Community Engagement• Survey design and implementation• Returning data to community• Role of informatics

Community Survey• Demographics

– Including socio-economic status• Anthropometric measures and vital signs

– Blood pressure, height, weight, waist circumference• Surveys (incorporate selected PROMIS measures) including

– Nutrition– Physical activity– Social role performance– Health and illness perceptions– Self health assessment– Depression– Medication adherence– Quality of life– Health literacy

• Baseline and follow-up approximately 1 year apart• Some overlap with BRFSS and NYC Community Health Survey – Yoon eGEMS

publication

Survey Populations

• Community– 3,940

• Ambulatory Clinics– 1,200

• Community Outreach Center– 800

Survey Design and Implementation• CTSA-funded Columbia-Community Partnership for Health

(CCPH)• Free community blood pressure screening and education at

CCPH• Focus groups to inform survey content• Data collection by bilingual community health workers from

Washington Heights/Inwood in homes, community organizations, and local businesses as well as CCPH and clinics

• Incorporation of snowball sampling methods• Compensation for participant time with incentives of value to

residents (e.g., grocery coupons)• Asked about top health concerns

Building a Strong Fabric of Trust

• Participation rates in research studies – increased enrollment rates for WICER referrals to other studies

• Participation rates in biobanks – exceeded biospecimen collection goals

• Use of information technologies for health-related purposes – only 7% had used information technology for health purposes, but most participants agreed to linkage of survey data to clinical data

Returning Data to the Community• Survey respondents• Community-based Organizations

Returning Survey Data to Participants• Established WICER visualization working group that

includes investigators from a variety of disciplines including nursing, medicine, public health, biomedical informatics, engineering, human factors, communication, art, fashion, theater

• Creation of infographics of varying levels of complexity based on cognitive tasks

• Focus groups regarding preference and acceptability• Basic research regarding comprehension• Applied research related to actionability in consumer-facing

and provider-facing applications• Process reported in Arcia et al. AMIA 2013

Key Lessons from Focus Groups More is more Culture matters

Your Blood Pressure Risks of High Blood Pressure

StrokeCerebrovascular

accident

Heart attackMyocardial infarction

Kidney failureRenal failure

Vision lossHypertensive retinopathy

Blood vessel DamageAtherosclerosis

Days with Adequate Physical Activity in the Last Month

Jill Jones54 years old

50-60 year-old femalesin Washington Heights

50-60 year-old femalesnationwide

22

15

25

Physical Activity

Jill Jones54 years old

50-60 year-old femalesin Washington Heights

50-60 year-old femalesnationwide

Image from http://advgraphic2.blogspot.com/2011/01/icons-of-graphic-design.html

Pictorial bar graph

Physical Activity

Community-based Organizations• Focus groups• Elicitation of information needs and

desired formats

Informatics Approaches• Simple topic modeling• Community web site as mechanism of

return of survey data to respondents• Electronic Tailored Infographics for

Community Engagement, Education, and Empowerment (EnTICE3)

The EnTICE3 Framework and Sample Infographic

EnTICE3 Requirements

Construct individual- and community- level visualizations₋ adapt to change

₋ reusable, generalizable

“change the color & size”, “replace star icons with banana icons”, “change the age group from 18-35 to 18-25”, ...

“same bar graph, but using different survey variables”, “generate the bar graph for a different dataset”, “display this chart in another website”, “a different institution wants a similar visualization”

EnTICE3 Requirements

• Construct individual- and community- level visualizations₋ adapt to change

■ iterative approach■ prototype → production

₋ reusable, generalizable■ modular, generic services■ web standards (HTML, HTTP)■ web components (encapsulated interactive

templates)

Governance Infrastructure

Structures and processes that control data₋ Query and extract₋ Store new data₋ Access control₋ Audit access

Underlies EnTICE3 and other components

Conclusions• Significant barriers to research participation exist for

populations at high risk for health disparities• Community engagement approaches essential to reach

such participants• Ethical imperative to return data to those that

contribute it in a way that is comprehensible and actionable for improving health

• Important component of a learning health system• Requires continued engagement and iterative

refinement


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