{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T07:17:48Z","timestamp":1792480668477,"version":"4.5.0"},"reference-count":33,"publisher":"Georg Thieme Verlag KG","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Artificial intelligence (AI) scribes use advanced speech recognition and natural language processing to automate clinical documentation and ease administrative burden. However, little is known about the effect of AI scribes on clinicians, patients, and organizations.<\/jats:p>\n                  <jats:p>This study aimed to (1) propose an evaluation framework to guide future AI scribe implementations, (2) describe the effect of AI scribes along the domains proposed in the developed evaluation framework, and (3) identify gaps in the AI scribe implementation literature to be evaluated in future studies.<\/jats:p>\n                  <jats:p>Databases including Embase, Embase Classic, and Ovid Medline were searched, and a manual review was conducted of the New England Journal of Medicine AI. Studies published after 2021 that reported on the implementation of AI scribes in health care were included. Descriptive analysis was undertaken. Quality assessment was undertaken using the Newcastle\u2013Ottawa Scale. The nominal group technique was used to develop an evaluation framework.<\/jats:p>\n                  <jats:p>Eleven studies met the inclusion criteria, with 10 published in 2024. The most frequently used AI scribe was Dragon Ambient eXperience (n\u2009=\u20097, 64%). While clinicians often reported improved documentation quality, AI scribe accuracy varied, frequently requiring manual edits and raising occasional concerns about errors. Nine of 10 studies reported improvements in at least one efficiency metric, and seven of ten studies highlighted positive effects on clinician wellness and burnout. Patient experience was assessed in three studies, all reporting favorable outcomes.<\/jats:p>\n                  <jats:p>AI scribes represent a promising tool for improving clinical efficiency and alleviating documentation burden. This systematic review highlights the potential benefits of AI scribes, including reduced documentation time and enhanced clinician satisfaction, while also identifying critical challenges such as variable adoption, performance limitations, and gaps in evaluation.<\/jats:p>","DOI":"10.1055\/a-2597-2017","type":"journal-article","created":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T20:08:06Z","timestamp":1746043686000},"page":"1121-1135","source":"Crossref","is-referenced-by-count":59,"title":["Clinical Implementation of Artificial Intelligence Scribes in Health Care: A Systematic Review"],"prefix":"10.1055","volume":"16","author":[{"given":"Hadeel","family":"Hassan","sequence":"additional","affiliation":[{"name":"Division of Haematology\/Oncology, The Hospital for Sick Children, Toronto, Canada"},{"name":"Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy R.","family":"Zipursky","sequence":"additional","affiliation":[{"name":"Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada"},{"name":"Department of Emergency Medicine, The Hospital for Sick Children, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naveed","family":"Rabbani","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacqueline G.","family":"You","sequence":"additional","affiliation":[{"name":"Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, United States"},{"name":"Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriel","family":"Tse","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Stanford University, Stanford, California, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evan","family":"Orenstein","sequence":"additional","affiliation":[{"name":"Information Services and Technology, Children's Healthcare of Atlanta, Atlanta Georgia, United States"},{"name":"Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mondira","family":"Ray","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chase","family":"Parsons","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stella","family":"Shin","sequence":"additional","affiliation":[{"name":"Information Services and Technology, Children's Healthcare of Atlanta, Atlanta Georgia, United States"},{"name":"Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory","family":"Lawton","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karim","family":"Jessa","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, The Hospital for Sick Children, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lillian","family":"Sung","sequence":"additional","affiliation":[{"name":"Division of Haematology\/Oncology, The Hospital for Sick Children, Toronto, Canada"},{"name":"Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam P.","family":"Yan","sequence":"additional","affiliation":[{"name":"Division of Haematology\/Oncology, The Hospital for Sick Children, Toronto, Canada"},{"name":"Program in Child Health Evaluative Sciences, Peter Gilgan Research Institute, The Hospital for Sick Children, Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2025,9,19]]},"reference":[{"issue":"04","key":"ref2","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1007\/s12553-021-00568-0","article-title":"Digital scribe utility and barriers to implementation in clinical practice: a scoping review","volume":"11","author":"S Ghatnekar","year":"2021","journal-title":"Health Technol (Berl)"},{"issue":"02","key":"ref3","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.amjmed.2019.08.034","article-title":"Physician stress and burnout","volume":"133","author":"S W Yates","year":"2020","journal-title":"Am J Med"},{"issue":"05","key":"ref4","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1055\/a-2385-1654","article-title":"Defining documentation burden (DocBurden) and excessive DocBurden for all health professionals: a scoping review","volume":"15","author":"D R Levy","year":"2024","journal-title":"Appl Clin Inform"},{"issue":"01","key":"ref5","doi-asserted-by":"crossref","first-page":"e6450","DOI":"10.1097\/GOX.0000000000006450","article-title":"Artificial intelligence scribe and large language model technology in healthcare documentation: advantages, limitations, and recommendations","volume":"13","author":"S A Mess","year":"2025","journal-title":"Plast Reconstr Surg Glob Open"},{"key":"ref8","volume-title":"The Human Factors in the Adoption of Ambient Artificial Intelligence Scribe Technology: Towards Informed and User-centered Implementation of AI in Healthcare","author":"I Basha","year":"2024"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.jdin.2024.02.009","article-title":"Artificial intelligence-driven digital scribes in clinical documentation: pilot study assessing the impact on dermatologist workflow and patient encounters","volume":"15","author":"D Y Cao","year":"2024","journal-title":"JAAD Int"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"n71","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 statement: an updated guideline for reporting systematic reviews","volume":"372","author":"M J Page","year":"2021","journal-title":"BMJ"},{"issue":"01","key":"ref11","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/s41746-021-00432-5","article-title":"The digital scribe in clinical practice: a scoping review and research agenda","volume":"4","author":"M M van Buchem","year":"2021","journal-title":"NPJ Digit Med"},{"issue":"01","key":"ref12","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"J R Landis","year":"1977","journal-title":"Biometrics"},{"issue":"10","key":"ref13","doi-asserted-by":"crossref","first-page":"e549","DOI":"10.1016\/S2589-7500(20)30219-3","article-title":"Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension","volume":"2","author":"S Cruz Rivera","year":"2020","journal-title":"Lancet Digit Health"},{"issue":"02","key":"ref14","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1038\/s41591-021-01229-5","article-title":"DECIDE-AI: new reporting guidelines to bridge the development-to-implementation gap in clinical artificial intelligence","volume":"27","author":"B Vasey","year":"2021","journal-title":"Nat Med"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1038\/s41591-022-01772-9","article-title":"Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI","volume":"28","author":"B Vasey","year":"2022","journal-title":"Nat Med"},{"issue":"09","key":"ref16","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1038\/s41591-020-1034-x","article-title":"Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension","volume":"26","author":"X Liu","year":"2020","journal-title":"Nat Med"},{"issue":"12","key":"ref18","doi-asserted-by":"publisher","DOI":"10.1056\/AIoa2400659","article-title":"Does AI-powered clinical documentation enhance clinician efficiency? A longitudinal study","volume":"1","author":"T L Liu","year":"2024","journal-title":"NEJM AI"},{"issue":"04","key":"ref19","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1093\/jamia\/ocae022","article-title":"The impact of nuance DAX ambient listening AI documentation: a cohort study","volume":"31","author":"T Haberle","year":"2024","journal-title":"J Am Med Inform Assoc"},{"issue":"02","key":"ref20","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1093\/fampra\/cmad092","article-title":"The association between use of ambient voice technology documentation during primary care patient encounters, documentation burden, and provider burnout","volume":"41","author":"L M Owens","year":"2024","journal-title":"Fam Pract"},{"issue":"09","key":"ref21","doi-asserted-by":"crossref","first-page":"e2432460","DOI":"10.1001\/jamanetworkopen.2024.32460","article-title":"AI-powered clinical documentation and clinicians' electronic health record experience: a nonrandomized clinical trial","volume":"7","author":"T L Liu","year":"2024","journal-title":"JAMA Netw Open"},{"issue":"13","key":"ref23","doi-asserted-by":"crossref","first-page":"2625","DOI":"10.1007\/s11606-024-08924-2","article-title":"Impact of an artificial intelligence-based solution on clinicians' clinical documentation experience: initial findings using ambient listening technology","volume":"39","author":"J L Galloway","year":"2024","journal-title":"J Gen Intern Med"},{"issue":"02","key":"ref25","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1093\/jamia\/ocae295","article-title":"Ambient artificial intelligence scribes: physician burnout and perspectives on usability and documentation burden","volume":"32","author":"S J Shah","year":"2025","journal-title":"J Am Med Inform Assoc"},{"issue":"15","key":"ref27","doi-asserted-by":"crossref","first-page":"2995","DOI":"10.1007\/s11606-024-08870-z","article-title":"Can the administrative loads of physicians be alleviated by AI-facilitated clinical documentation?","volume":"39","author":"H Bundy","year":"2024","journal-title":"J Gen Intern Med"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"e2200166","DOI":"10.1200\/CCI.22.00166","article-title":"Implementing digital scribes to reduce electronic health record documentation burden among cancer care clinicians: a mixed-methods pilot study","volume":"7","author":"O T Nguyen","year":"2023","journal-title":"JCO Clin Cancer Inform"},{"key":"ref29","first-page":"892","article-title":"Medical scribes have a variable impact on documentation workflows","volume":"290","author":"A Rule","year":"2022","journal-title":"Stud Health Technol Inform"},{"issue":"03","key":"ref30","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1055\/s-0044-1787007","article-title":"Toward alleviating clinician documentation burden: a scoping review of burden reduction efforts","volume":"15","author":"E A Sloss","year":"2024","journal-title":"Appl Clin Inform"},{"issue":"04","key":"ref31","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1093\/jamia\/ocz223","article-title":"Metrics for assessing physician activity using electronic health record log data","volume":"27","author":"C A Sinsky","year":"2020","journal-title":"J Am Med Inform Assoc"},{"issue":"11","key":"ref32","doi-asserted-by":"crossref","first-page":"784","DOI":"10.7326\/M18-1422","article-title":"Estimating the attributable cost of physician burnout in the United States","volume":"170","author":"S Han","year":"2019","journal-title":"Ann Intern Med"},{"issue":"02","key":"ref33","doi-asserted-by":"crossref","first-page":"160","DOI":"10.7812\/TPP\/23.015","article-title":"Time out: the impact of physician burnout on patient care quality and safety in perioperative medicine","volume":"27","author":"P Shin","year":"2023","journal-title":"Perm J"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"e54811","DOI":"10.2196\/54811","article-title":"Evaluating the prevalence of burnout among health care professionals related to electronic health record use: systematic review and meta-analysis","volume":"12","author":"Y Wu","year":"2024","journal-title":"JMIR Med Inform"},{"issue":"03","key":"ref36","doi-asserted-by":"crossref","first-page":"ooab047","DOI":"10.1093\/jamiaopen\/ooab047","article-title":"A qualitative study of provider burnout: do medical scribes hinder or help?","volume":"4","author":"S Corby","year":"2021","journal-title":"JAMIA Open"},{"issue":"01","key":"ref37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.7326\/M20-0428","article-title":"The productivity requirements of implementing a medical scribe program","volume":"174","author":"T J Miksanek","year":"2021","journal-title":"Ann Intern Med"},{"issue":"02","key":"ref38","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.annemergmed.2020.07.031","article-title":"Effect of medical scribes on throughput, revenue, and patient and provider satisfaction: a systematic review and meta-analysis","volume":"77","author":"M Gottlieb","year":"2021","journal-title":"Ann Emerg Med"},{"issue":"02","key":"ref39","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1093\/jamia\/ocae304","article-title":"Ambient artificial intelligence scribes: utilization and impact on documentation time","volume":"32","author":"S P Ma","year":"2025","journal-title":"J Am Med Inform Assoc"},{"issue":"7650","key":"ref40","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1136\/bmj.39489.470347.AD","article-title":"GRADE: an emerging consensus on rating quality of evidence and strength of recommendations","volume":"336","author":"G H Guyatt","year":"2008","journal-title":"BMJ"},{"issue":"03","key":"ref42","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1007\/s11606-023-08497-6","article-title":"Chatting beyond ChatGPT: advancing equity through AI-driven language interpretation","volume":"39","author":"L Bakdash","year":"2024","journal-title":"J Gen Intern Med"}],"container-title":["Applied Clinical Informatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2597-2017.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T00:46:12Z","timestamp":1772066772000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2597-2017"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,30]]},"references-count":33,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2025,8,6]]},"published-print":{"date-parts":[[2025,8]]}},"URL":"https:\/\/doi.org\/10.1055\/a-2597-2017","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["1869-0327"],"issn-type":[{"value":"1869-0327","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,4,30]]},"published":{"date-parts":[[2025,4,30]]}}}