{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T08:28:31Z","timestamp":1771230511470,"version":"3.50.1"},"reference-count":7,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2020,2,4]],"date-time":"2020-02-04T00:00:00Z","timestamp":1580774400000},"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":[[2020,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The rise of clinician burnout has been correlated with the increased adoption of electronic health records (EHRs). Some vendors have used data entry logs to measure the amount of time spent using the EHR and have developed metrics of provider efficiency. Initial attempts to utilize these data have proven difficult as it is not always apparent whether variations reflect provider behavior or simply the metric definitions. Metric definitions are also updated intermittently without warning, making longitudinal assessment problematic. Because the metrics are based on proprietary algorithms, they are impossible to validate without costly time\u2013motion studies and are also difficult to compare across institutions and vendors. Clinical informaticians must partner with vendors in order to develop industry standards of EHR use, which could then be used to examine the impact of EHRs on clinician burnout.<\/jats:p>","DOI":"10.1093\/jamia\/ocz222","type":"journal-article","created":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T20:16:43Z","timestamp":1576613803000},"page":"644-646","source":"Crossref","is-referenced-by-count":23,"title":["Have you got the time? Challenges using vendor electronic health record metrics of provider efficiency"],"prefix":"10.1093","volume":"27","author":[{"given":"Jonathan D","family":"Hron","sequence":"first","affiliation":[{"name":"Department of Pediatrics, Division of General Pediatrics, Boston Children\u2019s Hospital, Massachusetts, USA"},{"name":"Department of Pediatrics,\u00a0Harvard Medical School, Boston, Massachusetts, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eli","family":"Lourie","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA"},{"name":"Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,2,4]]},"reference":[{"issue":"2","key":"2020110613095205700_ocz222-B1","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1093\/jamia\/ocy145","article-title":"Physician stress and burnout: the impact of health information technology","volume":"26","author":"Gardner","year":"2019","journal-title":"J Am Med Informatics Assoc"},{"key":"2020110613095205700_ocz222-B2","first-page":"1","article-title":"Why doctors hate their computers","author":"Gawande","year":"2018","journal-title":"New Yorker, Annals of Medicine"},{"issue":"5","key":"2020110613095205700_ocz222-B3","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1370\/afm.2121","article-title":"Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations","volume":"15","author":"Arndt","year":"2017","journal-title":"Ann Fam Med"},{"issue":"1","key":"2020110613095205700_ocz222-B4","doi-asserted-by":"crossref","first-page":"50","DOI":"10.7326\/M18-0139","article-title":"Physician burnout in the electronic health record era: are we ignoring the real cause?","volume":"169","author":"Downing","year":"2018","journal-title":"Ann Intern Med"},{"issue":"4","key":"2020110613095205700_ocz222-B5","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1197\/jamia.M2373","article-title":"The extent and importance of unintended consequences related to computerized provider order entry","volume":"14","author":"Ash","year":"2007","journal-title":"J Am Med Informatics Assoc"},{"issue":"03","key":"2020110613095205700_ocz222-B6","doi-asserted-by":"crossref","first-page":"924","DOI":"10.4338\/ACI-2017-04-0054","article-title":"Designing an individualized EHR learning plan for providers","volume":"08","author":"Stevens","year":"2017","journal-title":"Appl Clin Inform"},{"key":"2020110613095205700_ocz222-B7","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1542\/peds.142.1MA7.611","article-title":"Targeting pajama time: efforts to reduce physician burnout through electronic medical record (EMR) improvements","volume":"142 (1 Meeting Abstract","author":"Webber","year":"2018","journal-title":"Pediatrics"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/jamia\/article-pdf\/27\/4\/644\/34152743\/ocz222.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/jamia\/article-pdf\/27\/4\/644\/34152743\/ocz222.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,24]],"date-time":"2023-09-24T04:07:16Z","timestamp":1695528436000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/27\/4\/644\/5722320"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,4]]},"references-count":7,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2020,2,4]]},"published-print":{"date-parts":[[2020,4,1]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocz222","relation":{},"ISSN":["1527-974X"],"issn-type":[{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,4]]},"published":{"date-parts":[[2020,2,4]]}}}