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Metrics for assessing physician activity using electronic health record log data.
Sinsky, Christine A; Rule, Adam; Cohen, Genna; Arndt, Brian G; Shanafelt, Tait D; Sharp, Christopher D; Baxter, Sally L; Tai-Seale, Ming; Yan, Sherry; Chen, You; Adler-Milstein, Julia; Hribar, Michelle.
Affiliation
  • Sinsky CA; Department of Medicine, American Medical Association, Chicago, Illinois, USA.
  • Rule A; Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Oregon, USA.
  • Cohen G; Department of Medicine, Mathematica, Washington, DC, USA.
  • Arndt BG; Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA.
  • Shanafelt TD; Division of Hematology, Department of Medicine, Stanford University, Stanford, California, USA.
  • Sharp CD; Division of Hematology, Department of Medicine, Stanford University, Stanford, California, USA.
  • Baxter SL; Division of General Internal Medicine, Department of Medicine, Stanford University, Stanford, California, USA.
  • Tai-Seale M; Department of Biomedical Informatics, University of California, San Diego, San Diego, California, USA.
  • Yan S; Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, San Diego, California, USA.
  • Chen Y; Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.
  • Adler-Milstein J; Department of Medicine, Sutter Health, Walnut Creek, California, USA.
  • Hribar M; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
J Am Med Inform Assoc ; 27(4): 639-643, 2020 04 01.
Article in En | MEDLINE | ID: mdl-32027360
ABSTRACT
Electronic health record (EHR) log data have shown promise in measuring physician time spent on clinical activities, contributing to deeper understanding and further optimization of the clinical environment. In this article, we propose 7 core measures of EHR use that reflect multiple dimensions of practice efficiency total EHR time, work outside of work, time on documentation, time on prescriptions, inbox time, teamwork for orders, and an aspirational measure for the amount of undivided attention patients receive from their physicians during an encounter, undivided attention. We also illustrate sample use cases for these measures for multiple stakeholders. Finally, standardization of EHR log data measure specifications, as outlined here, will foster cross-study synthesis and comparative research.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Physicians / Task Performance and Analysis / Efficiency / Electronic Health Records Limits: Humans Language: En Journal: J Am Med Inform Assoc Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Physicians / Task Performance and Analysis / Efficiency / Electronic Health Records Limits: Humans Language: En Journal: J Am Med Inform Assoc Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country: Estados Unidos