{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T18:56:40Z","timestamp":1790967400852,"version":"4.1.0"},"reference-count":15,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Hum Factors"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Administrative workload in general practice limits time for direct patient care. AI-assisted documentation has been proposed as a way to reduce the documentation burden, but evidence from routine primary care settings remains limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to evaluate general practitioners\u2019 (GPs) acceptance of AI-assisted documentation and its association with documentation time and clinical note quality in routine Danish general practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a quantitative pragmatic pre-post quality improvement evaluation in Danish general practice. A total of 20 GPs documented 239 consultations before and 236 consultations after implementation of an AI-assisted documentation system. Documentation quality, structure, clinical clarity, and documentation time categories were self-assessed using standardized audit forms completed immediately after each consultation. Technology acceptance and usability were assessed using the technology acceptance model (TAM) and the System Usability Scale (SUS).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Self-assessed documentation structure increased from 3.99 to 4.45, while self-reported documentation time categories decreased from 2.85 to 2.29. Technology acceptance and usability were high (TAM domain means 3.76-4.19; SUS mean 77.5). GP-level paired analyses showed moderate improvements in structure and clarity and a reduction in documentation time. Combined blinded external assessments showed higher postimplementation scores for quality, structure, and clinical clarity, although reviewer-specific ratings diverged, and interrater reliability was low. The association between documentation time and perceived quality was negligible. TAM and SUS indicated high clinician acceptance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI-assisted documentation was associated with lower self-reported documentation time categories while maintaining or modestly improving perceived clinical note quality. These findings support the feasibility of AI-assisted documentation in primary care, while highlighting the need for controlled studies with objective time measurement and longer follow-up.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/94431","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T18:35:08Z","timestamp":1788892508000},"page":"e94431-e94431","source":"Crossref","is-referenced-by-count":0,"title":["AI-Assisted Clinical Documentation in Routine Danish General Practice: Quantitative Pre-Post Study"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9255-2292","authenticated-orcid":false,"given":"Louise N\u00f8rgaard","family":"Olsen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8657-0391","authenticated-orcid":false,"given":"Philipp","family":"Harbig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8636-1670","authenticated-orcid":false,"given":"Anna Bay","family":"Laurberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1029-8297","authenticated-orcid":false,"given":"Jacob","family":"Laurberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0327-9564","authenticated-orcid":false,"given":"Morten Haaning","family":"Charles","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,10,2]]},"reference":[{"issue":"10","key":"R1","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":"15","key":"R2","doi-asserted-by":"publisher","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":"Bundy","journal-title":"J Gen Intern Med"},{"issue":"5","key":"R3","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1007\/s11606-022-07834-5","article-title":"Physician note composition patterns and time on the EHR across specialty types: a national, cross-sectional study","volume":"38","author":"Rotenstein","journal-title":"J Gen Intern Med"},{"issue":"1","key":"R4","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-025-02157-4","article-title":"Artificial intelligence (AI) - 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