{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,20]],"date-time":"2026-09-20T05:42:57Z","timestamp":1789882977154,"version":"4.0.1"},"reference-count":34,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Clinicians spend a substantial share of their working hours on documentation, contributing to workflow inefficiencies, reduced patient-facing time, and increased burnout. Artificial intelligence (AI) medical scribes have emerged as a promising solution to reduce this burden, yet real-world evidence remains limited and heterogeneous, and data from European health systems are especially scarce. This evaluation combines 2 complementary data sources: objective editing metadata from 236,153 notes generated by 1295 clinicians, describing operational editing behavior within the AI medical scribe, and paired self-reported survey responses from 177 fully onboarded clinicians, capturing perceived change in documentation time and clinician experience.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to evaluate the association of an AI medical scribe on documentation time and clinician experience.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This observational real-world evaluation was conducted between April 26, 2024, and October 27, 2025, using retrospective paired ratings. The study was carried out across multiple specialties in primary, secondary, and hospital care within Capio Ramsay Sant\u00e9, a large integrated health care provider operating in Sweden. Eligibility was limited to fully onboarded users, defined as clinicians who had used the scribe for at least 3 months, created more than 100 notes, generated at least 1 document or certificate, and used the conversational edit (\u201cAdd or adjust\u201d) feature at least once.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Following the introduction of the AI medical scribe, the estimated time spent on documentation per note was lower than before (4.72 vs 6.69 minutes; \u221229%,\n P<\/jats:italic>\n <.001). On a 5-point Likert scale, ratings for the ability to work without stress related to administrative tasks were higher after introduction than before (mean 3.14 vs 2.41;\n P<\/jats:italic>\n <.001; median change 0 points, 95% CI 0\u20131), as were ratings for perceived presence with patients (mean 4.33 vs 3.73;\n P<\/jats:italic>\n <.001; median change 0 points, 95% CI 0\u20131). The median editing time was 93 seconds, and it did not decrease significantly over continued use.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Among sustained, fully onboarded adopters in a European health care system, use of an AI medical scribe was associated with reductions in self-reported documentation time, administrative stress, and increase of presence with patients, consistent with findings from prior US-based studies. Because the survey cohort represents a highly selected subgroup of users who adopted and continued using the tool mainly in general practice, these associations may not generalize to clinicians who discontinued use or never fully adopted the scribe, and the generalizability across specialties remains unverified. The single-arm observational design and reliance on retrospective self-report are important considerations when interpreting these associations. A limitation of this analysis is that 138,196 notes were excluded because their recorded editing time was 0; these notes may have been used as generated, used as a starting point and later modified in the medical record system, or discarded, which limits the operational interpretation of the editing-time findings.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/90052","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T14:25:07Z","timestamp":1780928707000},"page":"e90052-e90052","source":"Crossref","is-referenced-by-count":1,"title":["Evaluation of an AI Medical Scribe After 236,153 Notes Generated Across Care Levels in a European Health System: Mixed Methods Retrospective Observational Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0209-5501","authenticated-orcid":false,"given":"Enni","family":"Sanmark","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9833-6965","authenticated-orcid":false,"given":"Ville","family":"Vartiainen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0916-1841","authenticated-orcid":false,"given":"Johan","family":"Sanmark","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7252-3437","authenticated-orcid":false,"given":"Katarina","family":"Wettin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0957-7569","authenticated-orcid":false,"given":"Lukas","family":"Saari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7418-8750","authenticated-orcid":false,"given":"Artin","family":"Entezarjou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,7,10]]},"reference":[{"issue":"7","key":"R1","doi-asserted-by":"publisher","first-page":"1128","DOI":"10.1377\/hlthaff.2017.1658","article-title":"Electronic health records associated with lower hospital mortality after systems have time to mature","volume":"37","author":"Lin","journal-title":"Health Aff"},{"issue":"3","key":"R2","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1136\/amiajnl-2012-001241","article-title":"Reduction in medication errors in hospitals due to adoption of computerized provider order entry systems","volume":"20","author":"Radley","journal-title":"J Am Med Inform Assoc"},{"issue":"4","key":"R3","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1093\/jamia\/ocz220","article-title":"Electronic health records and burnout: time spent on the electronic health record after hours and message volume associated with exhaustion but not with cynicism among primary care clinicians","volume":"27","author":"Adler-Milstein","journal-title":"J Am Med Inform Assoc"},{"issue":"2","key":"R4","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1093\/jamia\/ocy145","article-title":"Physician stress and burnout: the impact of health information technology","volume":"26","author":"Gardner","journal-title":"J Am Med Inform Assoc"},{"key":"R5","volume":"2019","author":"Tran","journal-title":"AMIA Jt Summits Transl Sci Proc"},{"issue":"4","key":"R6","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1377\/hlthaff.2016.0811","article-title":"Electronic health record logs indicate that physicians split time evenly between seeing patients and desktop medicine","volume":"36","author":"Tai-Seale","journal-title":"Health Aff"},{"issue":"6","key":"R7","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1001\/jamainternmed.2021.0256","article-title":"Differences in total and after-hours electronic health record time across ambulatory specialties","volume":"181","author":"Rotenstein","journal-title":"JAMA Intern Med"},{"issue":"5","key":"R8","doi-asserted-by":"publisher","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","journal-title":"Ann Fam Med"},{"issue":"1","key":"R9","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1055\/s-0037-1615747","article-title":"Time spent on dedicated patient care and documentation tasks before and after the introduction of a structured and standardized electronic health record","volume":"9","author":"Joukes","journal-title":"Appl Clin Inform"},{"issue":"11","key":"R10","doi-asserted-by":"publisher","first-page":"753","DOI":"10.7326\/M16-0961","article-title":"Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties","volume":"165","author":"Sinsky","journal-title":"Ann Intern Med"},{"issue":"2","key":"R11","doi-asserted-by":"publisher","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":"Owens","journal-title":"Fam Pract"},{"issue":"5","key":"R12","doi-asserted-by":"publisher","DOI":"10.1056\/CAT.25.0040","article-title":"Ambient artificial intelligence scribes: learnings after 1 year and over 2.5 million uses","volume":"6","author":"Tierney","journal-title":"NEJM Catalyst"},{"issue":"3","key":"R13","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2025.1904","article-title":"Physician perspectives on ambient AI scribes","volume":"8","author":"Shah","journal-title":"JAMA Netw Open"},{"issue":"5","key":"R14","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2024.13140","article-title":"Virtual scribes and physician time spent on electronic health records","volume":"7","author":"Rotenstein","journal-title":"JAMA Netw Open"},{"issue":"10","key":"R15","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2025.34976","article-title":"Use of ambient AI scribes to reduce administrative burden and professional burnout","volume":"8","author":"Olson","journal-title":"JAMA Netw Open"},{"issue":"12","key":"R16","doi-asserted-by":"publisher","DOI":"10.1056\/aioa2501000","article-title":"Ambient AI scribes in clinical practice: a randomized trial","volume":"2","author":"Lukac","journal-title":"NEJM AI"},{"issue":"4","key":"R17","doi-asserted-by":"publisher","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":"Haberle","journal-title":"J Am Med Inform Assoc"},{"issue":"12","key":"R18","doi-asserted-by":"publisher","DOI":"10.1056\/AIoa2400659","article-title":"Does AI-powered clinical documentation enhance clinician efficiency? A longitudinal study","volume":"1","author":"Liu","journal-title":"NEJM AI"},{"issue":"7","key":"R19","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1093\/jamia\/ocaf065","article-title":"Adoption of artificial intelligence in healthcare: survey of health system priorities, successes, and challenges","volume":"32","author":"Poon","journal-title":"J Am Med Inform Assoc"},{"key":"R20","unstructured":"Medical. MDCG 2019-11: guidance on qualification and classification of software in regulation (EU) 2017\/745\u2014 MDR and regulation (EU) 2017\/746\u2014IVDR. European Commission; 2019. URL: https:\/\/health.ec.europa.eu\/system\/files\/2020-09\/md_mdcg_2019_11_guidance_en_0.pdf [Accessed 20-06-2026]"},{"key":"R21","volume":"L117","journal-title":"Off J Eur Union"},{"key":"R22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2024.105687","article-title":"Electronic health records and data exchange in the WHO European region: a subregional analysis of achievements, challenges, and prospects","volume":"194","author":"Tornero Costa","journal-title":"Int J Med Inform"},{"key":"R23","doi-asserted-by":"publisher","DOI":"10.21037\/jmai-24-257","article-title":"Use of artificial intelligence to transcribe and summarise general practice consultations","volume":"8","author":"Haniff","journal-title":"J Med Artif Intell"},{"key":"R24","doi-asserted-by":"publisher","DOI":"10.2196\/60020","article-title":"Impact of a digital scribe system on clinical documentation time and quality: usability Study","volume":"3","author":"van Buchem","journal-title":"JMIR AI"},{"issue":"11-12","key":"R25","doi-asserted-by":"publisher","first-page":"1645","DOI":"10.1111\/jocn.15718","article-title":"Is nursing and midwifery clinical documentation a burden? An empirical study of perception versus reality","volume":"30","author":"Cooper","journal-title":"J Clin Nurs"},{"issue":"2","key":"R26","doi-asserted-by":"publisher","DOI":"10.1002\/emp2.12923","article-title":"Accuracy of physician self-estimation of time spent during patient care in the emergency department","volume":"4","author":"Reznek","journal-title":"J Am Coll Emerg Physicians Open"},{"issue":"1","key":"R27","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1258\/135581907779497576","article-title":"A comparison of self-reported and observational work sampling techniques for measuring time in nursing tasks","volume":"12","author":"Ampt","journal-title":"J Health Serv Res Policy"},{"issue":"11","key":"R28","doi-asserted-by":"publisher","first-page":"1467","DOI":"10.1001\/jamainternmed.2018.3956","article-title":"Association of medical scribes in primary care with physician workflow and patient experience","volume":"178","author":"Mishra","journal-title":"JAMA Intern Med"},{"key":"R29","doi-asserted-by":"publisher","DOI":"10.2196\/76743","article-title":"Real-world evidence synthesis of digital scribes using ambient listening and generative artificial intelligence for clinician documentation workflows: rapid review","volume":"4","author":"Kanaparthy","journal-title":"JMIR AI"},{"key":"R30","doi-asserted-by":"publisher","DOI":"10.1177\/00469580231159318","article-title":"The race to retain healthcare workers: a systematic review on factors that impact retention of nurses and physicians in hospitals","volume":"60","author":"de Vries","journal-title":"Inquiry"},{"issue":"6","key":"R31","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1111\/joim.12752","article-title":"Physician burnout: contributors, consequences and solutions","volume":"283","author":"West","journal-title":"J Intern Med"},{"key":"R32","unstructured":"Orienting AI toward health workforce well-being: examining risks and opportunities. National Academy of Medicine. Dec 2024. URL: https:\/\/nam.edu\/event\/orienting-ai-toward-health-workforce-well-being\/ [Accessed 19-06-2026]"},{"issue":"2","key":"R33","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1093\/jamia\/ocae304","article-title":"Ambient artificial intelligence scribes: utilization and impact on documentation time","volume":"32","author":"Ma","journal-title":"J Am Med Inform Assoc"},{"key":"R34","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2025.1691499","article-title":"Assessing the quality of AI-generated clinical notes: validated evaluation of a large language model ambient scribe","volume":"8","author":"Palm","journal-title":"Front Artif Intell"}],"container-title":["JMIR Medical Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/medinform.jmir.org\/2026\/1\/e90052","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T22:24:30Z","timestamp":1785536670000},"score":1,"resource":{"primary":{"URL":"https:\/\/medinform.jmir.org\/2026\/1\/e90052"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,10]]},"references-count":34,"URL":"https:\/\/doi.org\/10.2196\/90052","relation":{},"ISSN":["2291-9694"],"issn-type":[{"value":"2291-9694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,10]]},"article-number":"v14i7e90052"}}