{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T01:09:14Z","timestamp":1773191354504,"version":"3.50.1"},"reference-count":88,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T00:00:00Z","timestamp":1741910400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"University of Washington Population Health Initiative Tier 1","award":["#STUDY00015691"],"award-info":[{"award-number":["#STUDY00015691"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Artificial Intelligence (AI)-based approaches for extracting Social Drivers of Health (SDoH) from clinical notes offer healthcare systems an efficient way to identify patients\u2019 social needs, yet we know little about the acceptability of this approach to patients and clinicians. We investigated patient and clinician acceptability through interviews.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>We interviewed primary care patients experiencing social needs (n\u2009=\u200919) and clinicians (n\u2009=\u200914) about their acceptability of \u201cSDoH autosuggest,\u201d an AI-based approach for extracting SDoH from clinical notes. We presented storyboards depicting the approach and asked participants to rate their acceptability and discuss their rationale.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Participants rated SDoH autosuggest moderately acceptable (mean\u2009=\u20093.9\/5 patients; mean\u2009=\u20093.6\/5 clinicians). Patients\u2019 ratings varied across domains, with substance use rated most and employment rated least acceptable. Both groups raised concern about information integrity, actionability, impact on clinical interactions and relationships, and privacy. In addition, patients raised concern about transparency, autonomy, and potential harm, whereas clinicians raised concern about usability.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Despite reporting moderate acceptability of the envisioned approach, patients and clinicians expressed multiple concerns about AI systems that extract SDoH. Participants emphasized the need for high-quality data, non-intrusive presentation methods, and clear communication strategies regarding sensitive social needs. Findings underscore the importance of engaging patients and clinicians to mitigate unintended consequences when integrating AI approaches into care.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Although AI approaches like SDoH autosuggest hold promise for efficiently identifying SDoH from clinical notes, they must also account for concerns of patients and clinicians to ensure these systems are acceptable and do not undermine trust.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocaf046","type":"journal-article","created":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T14:15:37Z","timestamp":1741961737000},"page":"855-865","source":"Crossref","is-referenced-by-count":1,"title":["Patient and clinician acceptability of automated extraction of social drivers of health from clinical notes in primary care"],"prefix":"10.1093","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1826-7005","authenticated-orcid":false,"given":"Serena Jinchen","family":"Xie","sequence":"first","affiliation":[{"name":"Biomedical Informatics and Medical Education, School of Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"given":"Carolin","family":"Spice","sequence":"additional","affiliation":[{"name":"Biomedical Informatics and Medical Education, School of Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"given":"Patrick","family":"Wedgeworth","sequence":"additional","affiliation":[{"name":"Biomedical Informatics and Medical Education, School of Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"given":"Raina","family":"Langevin","sequence":"additional","affiliation":[{"name":"Biomedical Informatics and Medical Education, School of Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5798-2664","authenticated-orcid":false,"given":"Kevin","family":"Lybarger","sequence":"additional","affiliation":[{"name":"Information Sciences and Technology, George Mason University , Fairfax, VA 22030,","place":["United States"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9956-038X","authenticated-orcid":false,"given":"Angad Preet","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"given":"Brian R","family":"Wood","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"given":"Jared W","family":"Klein","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Washington, School of Medicine , Seattle, WA 98195,","place":["United States"]}]},{"given":"Gary","family":"Hsieh","sequence":"additional","affiliation":[{"name":"Human Centered Design & Engineering, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"given":"Herbert C","family":"Duber","sequence":"additional","affiliation":[{"name":"Washington State Department of Health , Olympia, WA 98501,","place":["United States"]},{"name":"Department of Emergency Medicine, University of Washington , Seattle, WA 98195,","place":["United States"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4932-7314","authenticated-orcid":false,"given":"Andrea L","family":"Hartzler","sequence":"additional","affiliation":[{"name":"Biomedical Informatics and Medical Education, School of Medicine, University of Washington , Seattle, WA 98195,","place":["United 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