The overall goal of this project is to advance comparative effectiveness research designed to improve hypertension care delivery and population outcomes by building on an existing institution-focused data infrastructure to create a robust community-focused data infrastructure that will support the kinds of innovative studies needed to effectively tackle seemingly intractable public health problems. This will be done through the Washington Heights/Inwood Informatics Infrastructure for Community-Centered Comparative Effectiveness Research (WICER). WICER contains a research data warehouse that integrates patient-level data, including clinical data from multiple facilities, settings and sites of care, with person-level self-reported information and will map the linked data to variables that support prospective comparative effectiveness research studies. It also will provide tools to support researchers in accessing this infrastructure to perform retrospective analyses and recruit patients for research studies. We will then demonstrate how this infrastructure can support three comparative effectiveness studies on hypertension. These three studies will relate to the diagnosis, treatment and management of hypertension in patients. Our project will augment an existing data infrastructure, enhance access through state of the science tools, and achieve greater integration of both the data and the health care organizations that contribute to it. This in turn will enable us to conduct both the proposed and subsequent comparative effectiveness studies generating evidence to inform effective diagnosis and treatment of hypertension, and ultimately a wider range of related community health problems.

Public Health Relevance

This research has the potential to improve the evidence base for treatment hypertension and other clinical conditions for a medically underserved, minority, low income, immigrant patient population. Currently, the evidence base for care delivery is not strong for this population, resulting in disparities in health care and outcomes. Insights gained through working with this specific population will then be generalizable to other such communities and populations.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZHS1-HSR-A (04))
Program Officer
Randhawa, Gurvaneet
Project Start
Project End
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Budget End
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Fiscal Year
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Columbia University (N.Y.)
Internal Medicine/Medicine
Schools of Medicine
New York
United States
Zip Code
Yoon, Sunmoo; Choi, Thomas; Odlum, Michelle et al. (2018) Machine Learning to Identify Behavioral Determinants of Oral Health in Inner City Older Hispanic Adults. Stud Health Technol Inform 251:253-256
Yoon, Sunmoo; Odlum, Michelle; Lee, Yeonsuk et al. (2018) Applying Deep Learning to Understand Predictors of Tooth Mobility Among Urban Latinos. Stud Health Technol Inform 251:241-244
Arcia, Adriana; Woollen, Janet; Bakken, Suzanne (2018) A Systematic Method for Exploring Data Attributes in Preparation for Designing Tailored Infographics of Patient Reported Outcomes. EGEMS (Wash DC) 6:2
Co Jr, Manuel C; Bakken, Suzanne (2018) Influence of the Local Food Environment on Hispanics' Perceptions of Healthy Food Access in New York City. Hisp Health Care Int 16:76-84
Masterson Creber, Ruth M; Fleck, Elaine; Liu, Jianfang et al. (2017) Identifying the Complexity of Multiple Risk Factors for Obesity Among Urban Latinas. J Immigr Minor Health 19:275-284
Arcia, Adriana; Suero-Tejeda, Niurka; Bales, Michael E et al. (2016) Sometimes more is more: iterative participatory design of infographics for engagement of community members with varying levels of health literacy. J Am Med Inform Assoc 23:174-83
Bjarnadottir, R I; Millery, M; Fleck, E et al. (2016) Correlates of online health information-seeking behaviors in a low-income Hispanic community. Inform Health Soc Care 41:341-9
Yoon, Sunmoo; Gutierrez, Jose (2016) Behavior Correlates of Post-Stroke Disability Using Data Mining and Infographics. Br J Med Med Res 11:
Unertl, Kim M; Schaefbauer, Chris L; Campbell, Terrance R et al. (2016) Integrating community-based participatory research and informatics approaches to improve the engagement and health of underserved populations. J Am Med Inform Assoc 23:60-73
Yoon, Sunmoo; Co Jr, Manuel C; Suero-Tejeda, Niurka et al. (2016) A Data Mining Approach for Exploring Correlates of Self-Reported Comparative Physical Activity Levels of Urban Latinos. Stud Health Technol Inform 225:553-7

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