New research from Yale Cancer Center provides a new understanding of patients’ views of artificial intelligence (AI) in health care. While comfort level varied by clinical application, most respondents had positive views about AI’s ability to improve care. Concerns surfaced when potential for misdiagnosis, privacy breaches, reduced time with clinicians, and increased costs were discussed. The findings were published recently in JAMA Network Open.
The research team surveyed a total of 926 respondents across the United States (471 women [50.9%], 455 men [49.1%]) and most patients believed that AI would make health care much better (10.9%) or somewhat better (44.5%). 66% of respondents deemed AL very important in their diagnosis or treatment and 29.8% stated AI was somewhat important. Responses were similar by age and race and ethnicity. Most respondents were very concerned or somewhat concerned about AI’s unintended consequences, including misdiagnosis (91.5%), privacy breaches (70.8%), less time with clinicians (69.6%), and higher health care costs (68.4%).
Comfort with AI varied by clinical application. For example, 12.3% of respondents were very comfortable and 42.7% were somewhat comfortable with AI reading chest radiographs, but only 6.0% were very comfortable and 25.2% were somewhat comfortable about AI making cancer diagnoses. A higher proportion of respondents who self-identified as being members of racial and ethnic minority groups indicated being very concerned about these issues, compared with white respondents.
“Our group was somewhat surprised that there were different levels of comfort regarding AI across clinical venues. Much of the work in medical AI is focused on trying to identify the various arenas in which AI can successfully impact healthcare for patients, but rarely do we ask ourselves which areas patients really want AI to impact their health care,” said Sanjay Aneja, MD, assistant professor of therapeutic radiology at Yale Cancer Center and Smilow Cancer Hospital and senior author on the publication.
“In many ways, our work highlights a potential blind spot among AI researchers, which needs to be addressed as these technologies become more common in clinical practice. Patient education, concerns, and comfort levels should be taken into consideration when planning for integration of AI.”
Funding for the study was provided by the Yale SPORE in Lung Cancer and a Conquer Cancer Career Development Award from American Society of Clinical Oncology. The following Yale authors contributed to this study: Yuan Lu, ScD and Harlan Krumholz, MD, SM.