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What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask Open Access (recommended)

Kohane IS, Aronow BJ, Avillach P, Beaulieu-Jones BK, Bellazzi R, Bradford RL, Brat GA, Cannataro M, Cimino JJ, Garcia-Barrio N, Gehlenborg N, Ghassemi M, Gutierrez-Sacristan A, Hanauer DA, Holmes JH, Hong C, Klann JG, Loh NHW, Luo Y, Mandl KD, Daniar M, Moore JH, Murphy SN, Neuraz A, Ngiam KY, Omenn GS, Palmer N, Patel LP, Pedrera-Jimenez M, Sliz P, South AM, Tan ALM, Taylor DM, Taylor BW, Torti C, Vallejos AK, Wagholikar KB, Weber GM, Cai TX, Consortium Clinical C. What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask. Journal of Medical Internet Research. 2021;23(3):9.

Descriptions

Resource type(s)
Article
Keyword
COVID-19
electronic health records
real-world data
literature
publishing
quality
data quality
reporting standards
reporting checklist
review
statistics
Rights
Attribution 4.0 International

Creator
Kohane, Isaac S.
Aronow, Bruce J.
Avillach, Paul
Beaulieu-Jones, Brett K.
Bellazzi, Riccardo
Bradford, Robert L.
Brat, Gabriel A.
Cannataro, Mario
Cimino, James J.
Garcia-Barrio, Noelia
Gehlenborg, Nils
Ghassemi, Marzyeh
Gutierrez-Sacristan, Alba
Hanauer, David A.
Holmes, John H.
Hong, Chuan
Klann, Jeffrey G.
Loh, Ne Hooi Will
Luo, Yuan
Mandl, Kenneth D.
Daniar, Mohamad
Moore, Jason H.
Murphy, Shawn N.
Neuraz, Antoine
Ngiam, Kee Yuan
Omenn, Gilbert S.
Palmer, Nathan
Patel, Lav P.
Pedrera-Jimenez, Miguel
Sliz, Piotr
South, Andrew M.
Tan, Amelia Li Min
Taylor, Deanne M.
Taylor, Bradley W.
Torti, Carlo
Vallejos, Andrew K.
Wagholikar, Kavishwar B.
Weber, Griffin M.
Cai, Tianxi
The Consortium For Clinical Characterization Of COVID-19 By EHR (4CE)
Abstract
Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.
Related URL
Publisher
JMIR PUBLICATIONS, INC
Date Created
2021-03-02
Original Identifier
(PMID) 33600347
Grants and funding
NCATS NIH HHSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Center for Advancing Translational Sciences (NCATS) [UL1 TR001420, UL1 TR001111] Funding Source: Medline; NCI NIH HHSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Cancer Institute (NCI) [U01 CA198934] Funding Source: Medline; NHLBI NIH HHSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [L40 HL148910, K23 HL148394] Funding Source: Medline; NLM NIH HHSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Library of Medicine (NLM) [R01 LM013345] Funding Source: Medline
DOI
10.2196/22219

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