A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare

Background While use of artificial intelligence (AI) in healthcare is increasing, little is known about how patients view healthcare AI. Characterizing patient attitudes and beliefs about healthcare AI and the factors that lead to these attitudes can help ensure patient values are in close alignment...

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Main Authors: Jordan P. Richardson, Susan Curtis, Cambray Smith, Joel Pacyna, Xuan Zhu, Barbara Barry, Richard R. Sharp
Format: Article
Language:English
Published: SAGE Publishing 2022-03-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076221089084
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author Jordan P. Richardson
Susan Curtis
Cambray Smith
Joel Pacyna
Xuan Zhu
Barbara Barry
Richard R. Sharp
author_facet Jordan P. Richardson
Susan Curtis
Cambray Smith
Joel Pacyna
Xuan Zhu
Barbara Barry
Richard R. Sharp
author_sort Jordan P. Richardson
collection DOAJ
description Background While use of artificial intelligence (AI) in healthcare is increasing, little is known about how patients view healthcare AI. Characterizing patient attitudes and beliefs about healthcare AI and the factors that lead to these attitudes can help ensure patient values are in close alignment with the implementation of these new technologies. Methods We conducted 15 focus groups with adult patients who had a recent primary care visit at a large academic health center. Using modified grounded theory, focus-group data was analyzed for themes related to the formation of attitudes and beliefs about healthcare AI. Results When evaluating AI in healthcare, we found that patients draw on a variety of factors to contextualize these new technologies including previous experiences of illness, interactions with health systems and established health technologies, comfort with other information technology, and other personal experiences. We found that these experiences informed normative and cultural beliefs about the values and goals of healthcare technologies that patients applied when engaging with AI. The results of this study form the basis for a theoretical framework for understanding patient orientation to applications of AI in healthcare, highlighting a number of specific social, health, and technological experiences that will likely shape patient opinions about future healthcare AI applications. Conclusions Understanding the basis of patient attitudes and beliefs about healthcare AI is a crucial first step in effective patient engagement and education. The theoretical framework we present provides a foundation for future studies examining patient opinions about applications of AI in healthcare.
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spelling doaj.art-c91c2d70b47e478a817897fca0651c792022-12-21T23:34:16ZengSAGE PublishingDigital Health2055-20762022-03-01810.1177/20552076221089084A framework for examining patient attitudes regarding applications of artificial intelligence in healthcareJordan P. Richardson0Susan Curtis1Cambray Smith2Joel Pacyna3Xuan Zhu4Barbara Barry5Richard R. Sharp6 Biomedical Ethics Research Program, , Rochester, MN, USA Biomedical Ethics Research Program, , Rochester, MN, USA Biomedical Ethics Research Program, , Rochester, MN, USA Biomedical Ethics Research Program, , Rochester, MN, USA Kern Center for the Science of Healthcare Delivery, , Rochester, MN, USA Kern Center for the Science of Healthcare Delivery, , Rochester, MN, USA Biomedical Ethics Research Program, , Rochester, MN, USABackground While use of artificial intelligence (AI) in healthcare is increasing, little is known about how patients view healthcare AI. Characterizing patient attitudes and beliefs about healthcare AI and the factors that lead to these attitudes can help ensure patient values are in close alignment with the implementation of these new technologies. Methods We conducted 15 focus groups with adult patients who had a recent primary care visit at a large academic health center. Using modified grounded theory, focus-group data was analyzed for themes related to the formation of attitudes and beliefs about healthcare AI. Results When evaluating AI in healthcare, we found that patients draw on a variety of factors to contextualize these new technologies including previous experiences of illness, interactions with health systems and established health technologies, comfort with other information technology, and other personal experiences. We found that these experiences informed normative and cultural beliefs about the values and goals of healthcare technologies that patients applied when engaging with AI. The results of this study form the basis for a theoretical framework for understanding patient orientation to applications of AI in healthcare, highlighting a number of specific social, health, and technological experiences that will likely shape patient opinions about future healthcare AI applications. Conclusions Understanding the basis of patient attitudes and beliefs about healthcare AI is a crucial first step in effective patient engagement and education. The theoretical framework we present provides a foundation for future studies examining patient opinions about applications of AI in healthcare.https://doi.org/10.1177/20552076221089084
spellingShingle Jordan P. Richardson
Susan Curtis
Cambray Smith
Joel Pacyna
Xuan Zhu
Barbara Barry
Richard R. Sharp
A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
Digital Health
title A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
title_full A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
title_fullStr A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
title_full_unstemmed A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
title_short A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
title_sort framework for examining patient attitudes regarding applications of artificial intelligence in healthcare
url https://doi.org/10.1177/20552076221089084
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