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Other industries have successfully implemented workflow automation to address these concerns, and lessons learned from those experiences may inform its application in health care.<\/jats:p><jats:p>Objective\u2003Our aim was to identify and synthesize (1) current approaches in workflow automation across industries, (2) opportunities for applying workflow automation in health care, and (3) considerations for designing and implementing workflow automation that may be relevant to health care.<\/jats:p><jats:p>Methods\u2003We conducted a targeted review of peer-reviewed and gray literature on automation approaches. We identified relevant databases and terms to conduct the searches across sources and reviewed abstracts to identify 123 relevant articles across 11 disciplines.<\/jats:p><jats:p>Results\u2003Workflow automation is used across industries such as finance, manufacturing, and travel to increase efficiency, productivity, and quality. We found automation ranged from low to full automation, and this variation was associated with task and technology characteristics. The level of automation is linked to how well a task is defined, whether a task is repetitive, the degree of human intervention and decision-making required, and the sophistication of available technology. We found that identifying automation goals and assessing whether those goals were reached was critical, and ongoing monitoring and improvement would help to ensure successful automation.<\/jats:p><jats:p>Conclusion\u2003Use of workflow automation in other industries can inform automating health care workflows by considering the critical role of people, process, and technology in design, testing, implementation, use, and ongoing monitoring of automated workflows. Insights gained from other industries will inform an interdisciplinary effort by the Office of the National Coordinator for Health Information Technology to outline priorities for advancing health care workflow automation.<\/jats:p>","DOI":"10.1055\/s-0041-1731744","type":"journal-article","created":{"date-parts":[[2021,7,28]],"date-time":"2021-07-28T23:14:52Z","timestamp":1627514092000},"page":"686-697","source":"Crossref","is-referenced-by-count":70,"title":["Identifying Opportunities for Workflow Automation in Health Care: Lessons Learned from Other Industries"],"prefix":"10.1055","volume":"12","author":[{"given":"Teresa","family":"Zayas-Cab\u00e1n","sequence":"additional","affiliation":[{"name":"Office of the National Coordinator for Health Information Technology, Washington, District of Columbia, United States"}]},{"given":"Saira Naim","family":"Haque","sequence":"additional","affiliation":[{"name":"RTI International, Research Triangle Park, North Carolina, United States"}]},{"given":"Nicole","family":"Kemper","sequence":"additional","affiliation":[{"name":"Clinovations Government\u2009+\u2009Health, Washington, District of Columbia, United States"}]}],"member":"194","published-online":{"date-parts":[[2021,7,28]]},"reference":[{"key":"ref1","volume-title":"Institute of Medicine (US) Committee on Quality of Health Care in America","year":"2001"},{"key":"ref2","volume-title":"Institute of Medicine (US) Committee on Quality of Health Care in America","year":"2000"},{"key":"ref3","volume-title":"Advances in Patient Safety: Organizational workflow and its impact on work quality","author":"C Cain","year":"2008"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"i2139","DOI":"10.1136\/bmj.i2139","article-title":"Medical error-the third leading cause of death in the US","volume":"353","author":"M A Makary","year":"2016","journal-title":"BMJ"},{"issue":"12","key":"ref9","first-page":"8","article-title":"Workflow peaks and pratfalls","volume":"35","year":"2014","journal-title":"Health Manag Technol"},{"issue":"07","key":"ref11","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1097\/MLR.0000000000000916","article-title":"In data we trust? 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