A framework for examining patient attitudes regarding applications of artificial intelligence in healthcare. (March 2022)

• Record Type: Journal Article
• Authors: Richardson, Jordan P.; Curtis, Susan; Smith, Cambray; Pacyna, Joel; Zhu, Xuan; Barry, Barbara; Sharp, Richard R.
• Is Part Of: Digital health. Volume 8(2022)
• Publication Date: 2022-03
• Subjects: Artificial intelligence -- patient perspectives -- bioethics; Medical care -- Data processing -- Periodicals; Medical informatics -- Periodicals; 362.10285
• DOI: 10.1177/20552076221089084
• Languages: English
• ISSNs: 2055-2076

Abstract

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.