{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T15:08:54Z","timestamp":1774451334245,"version":"3.50.1"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"NHLBI","doi-asserted-by":"publisher","award":["K08 HL146963"],"award-info":[{"award-number":["K08 HL146963"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"NHLBI","doi-asserted-by":"publisher","award":["K08 HL146963-02S1"],"award-info":[{"award-number":["K08 HL146963-02S1"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005831","name":"Foundation for Anesthesia Education and Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005831","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Partners Innovation, Brigham Research Institute"},{"DOI":"10.13039\/100000080","name":"Anesthesia Patient Safety Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000080","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To evaluate and understand pregnant patients\u2019 perspectives on the implementation of artificial intelligence (AI) in clinical care with a focus on opportunities to improve healthcare technologies and healthcare delivery.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>We developed an anonymous survey and enrolled patients presenting to the labor and delivery unit at a tertiary care center September 2019\u2013June 2020. We investigated the role and interplay of patient demographic factors, healthcare literacy, understanding of AI, comfort levels with various AI scenarios, and preferences for AI use in clinical care.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Of the 349 parturients, 57.6% were between the ages of 25\u201334\u00a0years, 90.1% reported college or graduate education and 69.2% believed the benefits of AI use in clinical care outweighed the risks. Cluster analysis revealed 2 distinct groups: patients more comfortable with clinical AI use (Pro-AI) and those who preferred physician presence (AI-Cautious). Pro-AI patients had a higher degree of education, were more knowledgeable about AI use in their daily lives and saw AI use as a significant advancement in medicine. AI-Cautious patients reported a lack of human qualities and low trust in the technology as detriments to AI use.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Patient trust and the preservation of the human physician-patient relationship are critical in moving forward with AI implementation in healthcare. Pregnant individuals are cautiously optimistic about AI use in their care.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Our findings provide insights into the status of AI use in perinatal care and provide a platform for driving patient-centered innovations.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocac200","type":"journal-article","created":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T18:37:45Z","timestamp":1666031865000},"page":"46-53","source":"Crossref","is-referenced-by-count":25,"title":["A survey of pregnant patients\u2019 perspectives on the implementation of artificial intelligence in clinical care"],"prefix":"10.1093","volume":"30","author":[{"given":"William","family":"Armero","sequence":"first","affiliation":[{"name":"Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, Massachusetts, USA"},{"name":"David Geffen School of Medicine at UCLA , Los Angeles, California, USA"}]},{"given":"Kathryn J","family":"Gray","sequence":"additional","affiliation":[{"name":"Division of Maternal-Fetal Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, Massachusetts, USA"}]},{"given":"Kara G","family":"Fields","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, Massachusetts, USA"}]},{"given":"Naida M","family":"Cole","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, Massachusetts, USA"},{"name":"Department of Anesthesia and Critical Care, The University of Chicago , Chicago, Illinois, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6268-1540","authenticated-orcid":false,"given":"David W","family":"Bates","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital , Boston, Massachusetts, USA"},{"name":"Department of Health Care Policy and Management, Harvard T.H. Chan School of Public Health , Boston, Massachusetts, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7367-3394","authenticated-orcid":false,"given":"Vesela P","family":"Kovacheva","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, Massachusetts, USA"}]}],"member":"286","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"issue":"2","key":"2022121408274160600_ocac200-B1","doi-asserted-by":"crossref","first-page":"94","DOI":"10.7861\/futurehosp.6-2-94","article-title":"The potential for artificial intelligence in healthcare","volume":"6","author":"Davenport","year":"2019","journal-title":"Future Healthc J"},{"key":"2022121408274160600_ocac200-B2","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1038\/s41746-020-00324-0","article-title":"The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online 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