{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T19:46:03Z","timestamp":1775072763682,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2017,5,30]],"date-time":"2017-05-30T00:00:00Z","timestamp":1496102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000016","name":"US Department of Health and Human Services","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000016","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>We sought to understand the types of clinical processes, such as image and medication ordering, that are disrupted during electronic health record (EHR) downtime periods by analyzing the narratives of patient safety event report data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>From a database of 80\u2009381 event reports, 76 reports were identified as explicitly describing a safety event associated with an EHR downtime period. These reports were analyzed and categorized based on a developed code book to identify the clinical processes that were impacted by downtime. We also examined whether downtime procedures were in place and followed.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The reports were coded into categories related to their reported clinical process: Laboratory, Medication, Imaging, Registration, Patient Handoff, Documentation, History Viewing, Delay of Procedure, and General. A majority of reports (48.7%, n\u2009=\u200937) were associated with lab orders and results, followed by medication ordering and administration (14.5%, n\u2009=\u200911). Incidents commonly involved patient identification and communication of clinical information. A majority of reports (46%, n\u2009=\u200935) indicated that downtime procedures either were not followed or were not in place. Only 27.6% of incidents (n\u2009=\u200921) indicated that downtime procedures were successfully executed.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Patient safety report data offer a lens into EHR downtime\u2013related safety hazards. Important areas of risk during EHR downtime periods were patient identification and communication of clinical information; these should be a focus of downtime procedure planning to reduce safety hazards.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>EHR downtime events pose patient safety hazards, and we highlight critical areas for downtime procedure improvement.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocx057","type":"journal-article","created":{"date-parts":[[2017,5,4]],"date-time":"2017-05-04T11:09:46Z","timestamp":1493896186000},"page":"187-191","source":"Crossref","is-referenced-by-count":49,"title":["Implications of electronic health record downtime: an analysis of patient safety event reports"],"prefix":"10.1093","volume":"25","author":[{"given":"Ethan","family":"Larsen","sequence":"first","affiliation":[{"name":"Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA"}]},{"given":"Allan","family":"Fong","sequence":"additional","affiliation":[{"name":"National Center for Human Factors in Healthcare, MedStar Health, Washington, DC, USA"}]},{"given":"Christian","family":"Wernz","sequence":"additional","affiliation":[{"name":"Department of Health Administration, Virginia Commonwealth University, Richmond, VA, USA"}]},{"given":"Raj M","family":"Ratwani","sequence":"additional","affiliation":[{"name":"National Center for Human Factors in Healthcare, MedStar Health, Washington, DC, USA"},{"name":"Department of Emergency Medicine, Georgetown University of School of Medicine, Washington, DC, USA"}]}],"member":"286","published-online":{"date-parts":[[2017,5,30]]},"reference":[{"key":"2020110612452648300_ocx057-B1","article-title":"Adoption of Electronic Health Record Systems among U.S. Non-Federal Acute Care Hospitals: 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