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Informatics-Enabled Community Engagement in the Washington Heights Informatics Infrastructure for Comparative Effectiveness Research (WICER) Project Suzanne.

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Presentation on theme: "Informatics-Enabled Community Engagement in the Washington Heights Informatics Infrastructure for Comparative Effectiveness Research (WICER) Project Suzanne."— Presentation transcript:

1 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

2 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.

3 Goals of WICER Comprehensive understanding of the Washington Heights/Inwood population Facilitate research with this population Demonstrate infrastructure capabilities for comparative effectiveness research

4 Washington Heights/Inwood 5 zip codes: 10031, 10032, 10033, 10034, Represents significant issues in health care disparities

5 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

6 WICER Data Coordinator Researcher Coordinator In patient Out patient Home care Long term Trial Survey Local Databases Clinical Encounters Research Encounters Research Data Warehouse RedX Integration Platform Research Data Access Data Access Expert Clinician Patient Community Members

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

8 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

9 Survey Populations Community – 3,940 Ambulatory Clinics – 1,200 Community Outreach Center – 800

10 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

11 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

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

13 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

14 Key Lessons from Focus Groups  More is more  Culture matters

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19 Your Blood Pressure Risks of High Blood Pressure Stroke Cerebrovascular accident Heart attack Myocardial infarction Kidney failure Renal failure Vision loss Hypertensive retinopathy Blood vessel Damage Atherosclerosis

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21 Days with Adequate Physical Activity in the Last Month Jill Jones 54 years old year-old females in Washington Heights year-old females nationwide

22 Physical Activity Jill Jones 54 years old year-old females in Washington Heights year-old females nationwide Image from Pictorial bar graph

23 Physical Activity

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27 Community-based Organizations Focus groups Elicitation of information needs and desired formats

28 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 (EnTICE 3 )

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31 The EnTICE 3 Framework and Sample Infographic

32 EnTICE 3 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 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”

33 EnTICE 3 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)

34 Governance Infrastructure  Structures and processes that control data ₋ Query and extract ₋Store new data ₋Access control ₋Audit access  Underlies EnTICE 3 and other components

35 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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