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

Title: What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask
Authors: Kohane I. S.; Aronow B. J.; Avillach P.; Beaulieu-Jones B. K.; Bellazzi R.; Bradford R. L.; Brat G. A.; Cannataro M.; Cimino J. J.; Garcia-Barrio N.; Gehlenborg N.; Ghassemi M.; Gutierrez-Sacristan A.; Hanauer D. A.; Holmes J. H.; Hong C.; Klann J. G.; Loh N. H. W.; Luo Y.; Mandl K. D.; Daniar M.; Moore J. H.; Murphy S. N.; Neuraz A.; Ngiam K. Y.; Omenn G. S.; Palmer N.; Patel L. P.; Pedrera-Jimenez M.; Sliz P.; South A. M.; Tan A. L. M.; Taylor D. M.; Taylor B. W.; Torti C.; Vallejos A. K.; Wagholikar K. B.; Weber G. M.; Cai T.; Albayrak A.; Amendola D. F.; Anthony L. L. L. J.; Atz A.; Bell D. S.; Bellasi A.; Benoit V.; Beraghi M.; Sobrino J. L. B.; Bernaux M.; Bey R.; Martinez A. B.; Boeker M.; Bonzel C. -L.; Booth J.; Bosari S.; Bourgeois F. T.; Breant S.; Bucalo M.; Burgun A.; Cao A.; Caucheteux C.; Champ J.; Chiovato L.; Colicchio T. K.; Cormont S.; Cossin S.; Craig J.; Bermudez J. L. C.; Dagliati A.; Daniel C.; Davoudi A.; Devkota B.; Dubiel J.; DuVall S. L.; Esteve L.; Fan S.; Follett R. W.; Gaiolla P. S. A.; Ganslandt T.; Barrio N. G.; Geva A.; Gradinger T.; Gramfort A.; Griffier R.; Griffon N.; Grisel O.; Haverkamp C.; Hilka M.; Horki P.; Hutch M. R.; Issitt R.; Jannot A. S.; Jouhet V.; Keller M. S.; Kirchoff K.; Krantz I. D.; Kraska D.; Krishnamurthy A. K.; L'Yi S.; Le T. T.; Leblanc J.; Lemaitre G.; Lenert L.; Leprovost D.; Liu M.; Lynch K. E.; Mahmood S.; Maidlow S.; Malovini A.; Mao C.; Martel P.; Masino A. J.; Matheny M. E.; Maulhardt T.; McDuffie M. T.; Mensch A.; Minicucci M. F.; Moal B.; Morris J. S.; Morris M.; Moshal K. L.; Mousavi S.; Mowery D. L.; Murad D. A.; Obeid J.; Okoshi M. P.; Olson K. L.; Orlova N.; Ostasiewski B. D.; Paris N.; Jimenez M. P.; Prokosch H. U.; Prudente R. A.; Ramoni R. B.; Raskin M.; Rieg S.; Dominguez G. R.; Salamanca E.; Samayamuthu M. J.; Sandrin A.; Schiver E.; Schuettler J.; Scudeller L.; Sebire N.; Balazote P. S.; Serre P.; Serret-Larmande A.; Silvio D.; Son J.; Spiridou A.; Tan B. W. Q.; Tan B. W. L.; Tanni S. E.; Tibollo V.; Tippmann P.; Varoquaux G.; Vie J. -J.; Visweswaran S.; Waitman L. R.; Wassermann D.; William Y.; Xia Z.; Zambelli A.; Carmona A.; Sonday C.; Balshi J.
Contributors: Kohane, I; Aronow, B; Avillach, P; Beaulieu-Jones, B; Bellazzi, R; Bradford, R; Brat, G; Cannataro, M; Cimino, J; Garcia-Barrio, N; Gehlenborg, N; Ghassemi, M; Gutierrez-Sacristan, A; Hanauer, D; Holmes, J; Hong, C; Klann, J; Loh, N; Luo, Y; Mandl, K; Daniar, M; Moore, J; Murphy, S; Neuraz, A; Ngiam, K; Omenn, G; Palmer, N; Patel, L; Pedrera-Jimenez, M; Sliz, P; South, A; Tan, A; Taylor, D; Taylor, B; Torti, C; Vallejos, A; Wagholikar, K; Weber, G; Cai, T; Albayrak, A; Amendola, D; Anthony, L; Atz, A; Bell, D; Bellasi, A; Benoit, V; Beraghi, M; Sobrino, J; Bernaux, M; Bey, R; Martinez, A; Boeker, M; Bonzel, C; Booth, J; Bosari, S; Bourgeois, F; Breant, S; Bucalo, M; Burgun, A; Cao, A; Caucheteux, C; Champ, J; Chiovato, L; Colicchio, T; Cormont, S; Cossin, S; Craig, J; Bermudez, J; Dagliati, A; Daniel, C; Davoudi, A; Devkota, B; Dubiel, J; Duvall, S; Esteve, L; Fan, S; Follett, R; Gaiolla, P; Ganslandt, T; Barrio, N; Geva, A; Gradinger, T; Gramfort, A; Griffier, R; Griffon, N; Grisel, O; Haverkamp, C; Hilka, M; Horki, P; Hutch, M; Issitt, R; Jannot, A; Jouhet, V; Keller, M; Kirchoff, K; Krantz, I; Kraska, D; Krishnamurthy, A; L'Yi, S; Le, T
Publisher Information: JMIR Publications, Inc.; CA
Publication Year: 2021
Collection: Università degli Studi di Milano-Bicocca: BOA (Bicocca Open Archive)
Subject Terms: COVID-19; Data quality; Electronic health record; Literature; Publishing; Quality; Real-world data; Reporting checklist; Reporting standard; Review; Statistic
Description: 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.
Document Type: article in journal/newspaper
File Description: ELETTRONICO
Language: English
Relation: info:eu-repo/semantics/altIdentifier/pmid/33600347; info:eu-repo/semantics/altIdentifier/wos/WOS:000624293400004; volume:23; issue:3; journal:JMIR. JOURNAL OF MEDICAL INTERNET RESEARCH; https://hdl.handle.net/10281/526921
DOI: 10.2196/22219
Availability: https://hdl.handle.net/10281/526921; https://doi.org/10.2196/22219
Rights: info:eu-repo/semantics/openAccess ; license:Creative Commons ; license uri:http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.D5C666B
Database: BASE