What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask

被引：65

作者：

Kohane, Isaac S. ^{[1
]}

Aronow, Bruce J. ^{[2
]}

Avillach, Paul ^{[1
]}

Beaulieu-Jones, Brett K. ^{[1
]}

Bellazzi, Riccardo ^{[3
,4
]}

Bradford, Robert L. ^{[5
]}

Brat, Gabriel A. ^{[1
]}

Cannataro, Mario ^{[6
,7
]}

Cimino, James J. ^{[8
]}

Garcia-Barrio, Noelia ^{[9
]}

Gehlenborg, Nils ^{[1
]}

Ghassemi, Marzyeh ^{[10
]}

Gutierrez-Sacristan, Alba ^{[1
]}

Hanauer, David A. ^{[11
]}

Holmes, John H. ^{[12
]}

Hong, Chuan ^{[1
]}

Klann, Jeffrey G. ^{[13
,14
]}

Loh, Ne Hooi Will ^{[15
]}

Luo, Yuan ^{[16
]}

Mandl, Kenneth D. ^{[17
]}

Daniar, Mohamad ^{[18
]}

Moore, Jason H. ^{[19
]}

Murphy, Shawn N. ^{[1
,20
]}

Neuraz, Antoine ^{[21
,22
]}

Ngiam, Kee Yuan ^{[15
]}

Omenn, Gilbert S. ^{[23
]}

Palmer, Nathan ^{[1
]}

Patel, Lav P. ^{[24
]}

Pedrera-Jimenez, Miguel ^{[9
]}

Sliz, Piotr ^{[17
]}

South, Andrew M. ^{[25
]}

Tan, Amelia Li Min ^{[1
,26
]}

Taylor, Deanne M. ^{[27
,28
]}

Taylor, Bradley W. ^{[29
]}

Torti, Carlo ^{[7
]}

Vallejos, Andrew K. ^{[29
]}

Wagholikar, Kavishwar B. ^{[13
,14
]}

Weber, Griffin M. ^{[1
]}

Cai, Tianxi ^{[1
]}

机构：

[1] Harvard Med Sch, Dept Biomed Informat, 10 Shattuck St, Boston, MA 02115 USA

[2] Univ Cincinnati, Cincinnati Childrens Hosp Med Ctr, Biomed Informat, Cincinnati, OH USA

[3] Univ Pavia, Dept Elect Comp & Biomed Engn, Pavia, Italy

[4] ICS Maugeri, Pavia, Italy

[5] Univ North Carolina, North Carolina Translat & Clin Sci Inst, Chapel Hill, NC 27515 USA

[6] Magna Graecia Univ Catanzaro, Data Analyt Res Ctr, Catanzaro, Italy

[7] Magna Graecia Univ Catanzaro, Dept Med & Surg Sci, Catanzaro, Italy

[8] Univ Alabama Birmingham, Informat Inst, Birmingham, AL USA

[9] 12 Octubre Univ Hosp, Dept Informat, Madrid, Spain

[10] Univ Toronto, Dept Comp Sci & Med, Toronto, ON, Canada

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

[12] Univ Penn, Perelman Sch Med, Dept Biostat Epidemiol & Informat, Philadelphia, PA 19104 USA

[13] Harvard Med Sch, Dept Med, Boston, MA 02115 USA

[14] Massachusetts Gen Hosp, Lab Comp Sci, Boston, MA 02114 USA

[15] Natl Univ Hlth Syst, Singapore, Singapore

[16] Northwestern Univ, Dept Prevent Med, Chicago, IL 60611 USA

[17] Boston Childrens Hosp, Computat Hlth Informat Program, Boston, MA USA

[18] Boston Childrens Hosp, Clin Res Informat, Boston, MA USA

[19] Univ Penn, Inst Biomed Informat, Philadelphia, PA 19104 USA

[20] Massachusetts Gen Hosp, Dept Neurol, Boston, MA 02114 USA

[21] Necker Enfant Malad Hosp, AP HP, Dept Biomed Informat, Paris, France

[22] Univ Paris, Ctr Rech Cordeliers, INSERM, UMRS 1138,Team 22, Paris, France

[23] Univ Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USA

[24] Univ Kansas, Med Ctr, Dept Internal Med, Div Med Informat, Kansas City, KS 66103 USA

[25] Wake Forest Sch Med, Dept Pediat, Sect Nephrol, Brenner Childrens Hosp, Winston Salem, NC 27101 USA

[26] Natl Univ Singapore, Dept Biomed Informat, Singapore, Singapore

[27] Childrens Hosp Philadelphia, Dept Biomed & Hlth Informat, Philadelphia, PA 19104 USA

[28] Univ Penn, Dept Pediat, Perelman Sch Med, Philadelphia, PA 19104 USA

[29] Med Coll Wisconsin, Clin & Translat Sci Inst, Milwaukee, WI 53226 USA

来源：

JOURNAL OF MEDICAL INTERNET RESEARCH | 2021年 / 23卷 / 03期

关键词：

COVID-19; electronic health records; real-world data; literature; publishing; quality; data quality; reporting standards; reporting checklist; review; statistics; CANCER;

D O I：

10.2196/22219

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

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.

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