{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T10:41:10Z","timestamp":1782556870147,"version":"3.54.5"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2021,12,9]],"date-time":"2021-12-09T00:00:00Z","timestamp":1639008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>We use EHR meta-data from ambulatory care clinicians in 366 health systems using the Epic EHR system in the United States from December 2019 to December 2020. We used descriptive statistics for clinician EHR use including active-use time across clinical activities, time after-hours, and messages received. Multivariable regression to evaluate total and after-hours EHR work adjusting for daily volume and organizational characteristics, and to evaluate the association between messages and EHR time.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Clinician time spent in the EHR per day dropped at the onset of the pandemic but had recovered to higher than prepandemic levels by July 2020. Time spent actively working in the EHR after-hours showed similar trends. These differences persisted in multivariable models. In-Basket messages received increased compared with prepandemic levels, with the largest increase coming from messages from patients, which increased to 157% of the prepandemic average. Each additional patient message was associated with a 2.32-min increase in EHR time per day (P\u2009&amp;lt;\u2009.001).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Clinicians spent more total and after-hours time in the EHR in the latter half of 2020 compared with the prepandemic period. This was partially driven by increased time in Clinical Review and In-Basket messaging.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Reimbursement models and workflows for the post-COVID era should account for these demands on clinician time that occur outside the traditional visit.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocab268","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T20:18:52Z","timestamp":1637180332000},"page":"453-460","source":"Crossref","is-referenced-by-count":161,"title":["Assessing the impact of the COVID-19 pandemic on clinician ambulatory electronic health record use"],"prefix":"10.1093","volume":"29","author":[{"given":"A Jay","family":"Holmgren","sequence":"first","affiliation":[{"name":"Center for Clinical Informatics and Improvement Research, University of California San Francisco, San Francisco, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"N Lance","family":"Downing","sequence":"additional","affiliation":[{"name":"Department of Medicine, Stanford University, Palo Alto, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5596-6393","authenticated-orcid":false,"given":"Mitchell","family":"Tang","sequence":"additional","affiliation":[{"name":"Harvard University, Cambridge, Massachusetts, USA"},{"name":"Harvard Business School, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Sharp","sequence":"additional","affiliation":[{"name":"Department of Medicine, Stanford University, Palo Alto, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Longhurst","sequence":"additional","affiliation":[{"name":"Department of Medicine, UC San Diego Health, La Jolla, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert S","family":"Huckman","sequence":"additional","affiliation":[{"name":"Harvard Business School, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,12,9]]},"reference":[{"issue":"3","key":"2022012920413720400_ocab268-B1","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1001\/jamainternmed.2020.5928","article-title":"Trends in outpatient care delivery and telemedicine during the COVID-19 pandemic in the US","volume":"181","author":"Patel","year":"2021","journal-title":"JAMA Intern Med"},{"key":"2022012920413720400_ocab268-B2","author":"Fox","year":"2020"},{"issue":"6","key":"2022012920413720400_ocab268-B3","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1093\/jamia\/ocaa067","article-title":"Telehealth transformation: COVID-19 and the rise of virtual care","volume":"27","author":"Wosik","year":"2020","journal-title":"J Am Med Inform Assoc"},{"key":"2022012920413720400_ocab268-B4","author":"Galewitz","year":"2020"},{"issue":"3","key":"2022012920413720400_ocab268-B5","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.jacc.2020.05.038","article-title":"Fewer hospitalizations for acute cardiovascular conditions during the COVID-19 pandemic","volume":"76","author":"Bhatt","year":"2020","journal-title":"J Am Coll Cardiol"},{"issue":"6","key":"2022012920413720400_ocab268-B6","doi-asserted-by":"crossref","first-page":"1142","DOI":"10.1093\/jamia\/ocx080","article-title":"Electronic health record adoption in US hospitals: the emergence of a digital \u201cadvanced use\u201d divide","volume":"24","author":"Adler-Milstein","year":"2017","journal-title":"J Am Med Inform Assoc"},{"issue":"18","key":"2022012920413720400_ocab268-B7","doi-asserted-by":"crossref","first-page":"1679","DOI":"10.1056\/NEJMp2003539","article-title":"Virtually Perfect? 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