Equity and bias in electronic health records data

被引：5

作者：

Boyd, Andrew D. ^{[1
]}

Gonzalez-Guarda, Rosa ^{[2
]}

Lawrence, Katharine ^{[3
]}

Patil, Crystal L. ^{[4
]}

Ezenwa, Miriam O. ^{[5
]}

O'Brien, Emily C. ^{[6
]}

Paek, Hyung ^{[7
]}

Braciszewski, Jordan M. ^{[8
]}

Adeyemi, Oluwaseun ^{[9
]}

Cuthel, Allison M. ^{[9
]}

Darby, Juanita E. ^{[4
]}

Zigler, Christina K. ^{[11
]}

Ho, P. Michael ^{[11
]}

Faurot, Keturah R. ^{[12
]}

Staman, Karen ^{[10
]}

Leigh, Jonathan W. ^{[4
]}

Dailey, Dana L. ^{[13
,17
]}

Cheville, Andrea ^{[14
]}

Del Fiol, Guilherme ^{[15
]}

Knisely, Mitchell R. ^{[2
]}

Marsolo, Keith

Richesson, Rachel L. ^{[16
]}

Schlaeger, Judith M.

机构：

[1] Univ Illinois, Dept Biomed & Hlth Informat Sci, Chicago, IL 60607 USA

[2] Duke Univ, Sch Nursing, Durham, NC USA

[3] NYU, Grossman Sch Med, Dept Populat Hlth, New York, NY USA

[4] Univ Illinois, Coll Nursing, Chicago, IL USA

[5] Univ Florida, Coll Nursing, Gainesville, FL USA

[6] Duke Univ, Sch Med, Dept Populat Hlth Sci, Durham, NC USA

[7] Yale Univ, New Haven, CT USA

[8] Henry Ford Hlth, Detroit, MI USA

[9] NYU, Grossman Sch Med, Ronald O Perelman Dept Emergency Med, New York, NY USA

[10] Duke Univ, Sch Med, Durham, NC USA

[11] Univ Colorado, Sch Med, Div Cardiol, Aurora, CO USA

[12] Univ N Carolina, Sch Med, Dept Phys Med & Rehabil, Chapel Hill, NC USA

[13] St Ambrose Univ, Davenport, IA USA

[14] Mayo Clin, Comprehens Canc Ctr, Rochester, MN USA

[15] Univ Utah, Sch Med, Dept Biomed Informat, Salt Lake City, UT USA

[16] Univ Michigan, Med Sch, Dept Learning Hlth Sci, Ann Arbor, MI USA

[17] Univ Iowa, Iowa City, IA USA

来源：

CONTEMPORARY CLINICAL TRIALS | 2023年 / 130卷

关键词：

Health equity; Patient -reported outcomes; Social determinants of health; Community engagement; Health literacy;

D O I：

10.1016/j.cct.2023.107238

中图分类号：

R-3 [医学研究方法]; R3 [基础医学];

学科分类号：

1001 ;

摘要：

Embedded pragmatic clinical trials (ePCTs) are conducted during routine clinical care and have the potential to increase knowledge about the effectiveness of interventions under real world conditions. However, many pragmatic trials rely on data from the electronic health record (EHR) data, which are subject to bias from incomplete data, poor data quality, lack of representation from people who are medically underserved, and implicit bias in EHR design. This commentary examines how the use of EHR data might exacerbate bias and potentially increase health inequities. We offer recommendations for how to increase generalizability of ePCT results and begin to mitigate bias to promote health equity.

引用

页数：3

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