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A survey of pregnant patients' perspectives on the implementation of artificial intelligence in clinical care.
- Source :
-
Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2022 Dec 13; Vol. 30 (1), pp. 46-53. - Publication Year :
- 2022
-
Abstract
- Objective: To evaluate and understand pregnant patients' perspectives on the implementation of artificial intelligence (AI) in clinical care with a focus on opportunities to improve healthcare technologies and healthcare delivery.<br />Materials and Methods: We developed an anonymous survey and enrolled patients presenting to the labor and delivery unit at a tertiary care center September 2019-June 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.<br />Results: Of the 349 parturients, 57.6% were between the ages of 25-34 years, 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.<br />Discussion: 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.<br />Conclusion: Our findings provide insights into the status of AI use in perinatal care and provide a platform for driving patient-centered innovations.<br /> (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Details
- Language :
- English
- ISSN :
- 1527-974X
- Volume :
- 30
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of the American Medical Informatics Association : JAMIA
- Publication Type :
- Academic Journal
- Accession number :
- 36250788
- Full Text :
- https://doi.org/10.1093/jamia/ocac200