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To understand their appropriate application, we asked 3 key questions: (1) To what extent are hard-stop alerts effective in improving patient health and healthcare delivery outcomes? (2) What are the adverse events and unintended consequences of hard-stop alerts? (3) How do hard-stop alerts compare to soft-stop alerts?<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods and Materials<\/jats:title><jats:p>Studies evaluating computerized hard-stop alerts in healthcare settings were identified from biomedical and computer science databases, gray literature sites, reference lists, and reviews. Articles were extracted for process outcomes, health outcomes, unintended consequences, user experience, and technical details.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of 32 studies, 15 evaluated health outcomes, 16 process outcomes only, 10 user experience, and 4 compared hard and soft stops. Seventy-nine percent showed improvement in health outcomes and 88% in process outcomes. Studies reporting good user experience cited heavy user involvement and iterative design. Eleven studies reported on unintended consequences including avoidance of hard-stopped workflow, increased alert frequency, and delay to care. Hard stops were superior to soft stops in 3 of 4 studies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Hard stops can be effective and powerful tools in the CDS armamentarium, but they must be implemented judiciously with continuous user feedback informing rapid, iterative design. Investigators must report on associated health outcomes and unintended consequences when implementing IT solutions to clinical problems.<\/jats:p><\/jats:sec>","DOI":"10.1093\/jamia\/ocy112","type":"journal-article","created":{"date-parts":[[2018,7,27]],"date-time":"2018-07-27T03:40:59Z","timestamp":1532662859000},"page":"1556-1566","source":"Crossref","is-referenced-by-count":113,"title":["Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review"],"prefix":"10.1093","volume":"25","author":[{"given":"Emily M","family":"Powers","sequence":"first","affiliation":[{"name":"Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, USA"},{"name":"Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA"}]},{"given":"Richard N","family":"Shiffman","sequence":"additional","affiliation":[{"name":"Yale Center for Medical Informatics, Yale University School of Medicine, 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