Journal of the American Medical Informatics Association
Volume 26, Issue 8-9, 2019, Pages 847-854
Research-grade data in the real world: Challenges and opportunities in data quality from a pragmatic trial in community-based practices (Article)
Divney A.A.* ,
Lopez P.M. ,
Huang T.T. ,
Thorpe L.E. ,
Trinh-Shevrin C. ,
Islam N.S.
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a
CUNY Graduate School of Public Health and Health Policy, Center for Systems and Community Design, 55 W. 125th Street, New York, NY 10027, United States, NYU-CUNY Prevention Research Center, New York, NY, United States
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b
NYU-CUNY Prevention Research Center, New York, NY, United States, Department of Population Health, NYU School of Medicine, New York, NY, United States
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c
CUNY Graduate School of Public Health and Health Policy, Center for Systems and Community Design, 55 W. 125th Street, New York, NY 10027, United States, NYU-CUNY Prevention Research Center, New York, NY, United States
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d
NYU-CUNY Prevention Research Center, New York, NY, United States, Department of Population Health, NYU School of Medicine, New York, NY, United States
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e
NYU-CUNY Prevention Research Center, New York, NY, United States, Department of Population Health, NYU School of Medicine, New York, NY, United States
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f
NYU-CUNY Prevention Research Center, New York, NY, United States, Department of Population Health, NYU School of Medicine, New York, NY, United States
Abstract
Randomized controlled trials face cost, logistic, and generalizability limitations, including difficulty engaging racial/ethnic minorities. Real-world data (RWD) from pragmatic trials, including electronic health record (EHR) data, may produce intervention evaluation findings generalizable to diverse populations. This case study of Project IMPACT describes unique barriers and facilitators of optimizing RWD to improve health outcomes and advance health equity in small immigrant-serving community-based practices. Project IMPACT tested the effect of an EHR-based health information technology intervention on hypertension control among small urban practices serving South Asian patients. Challenges in acquiring accurate RWD included EHR field availability and registry capabilities, cross-sector communication, and financial, personnel, and space resources. Although using RWD from community-based practices can inform health equity initiatives, it requires multidisciplinary collaborations, clinic support, procedures for data input (including social determinants), and standardized field logic/rules across EHR platforms. © 2019 The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved.
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Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071355679&doi=10.1093%2fjamia%2focz062&partnerID=40&md5=c1d3ddf617d7b304d9bd3d4d14121f1b
DOI: 10.1093/jamia/ocz062
ISSN: 10675027
Original Language: English