Recommended Citation
Hasan M, Riutta S, Mckillip R, Patton J, Jalan A. Examining Attitudes Towards AI Tools in Graduate Medical Education and Healthcare Practice. Presented at Scientific Day; May 20, 2026; Milwaukee, WI.
Abstract
Background/Significance:
Artificial intelligence (AI) tools are rapidly being introduced into clinical and research workflows, including documentation support, data analysis, and decision augmentation. Successful integration of these tools will depend on user trust, perceived appropriateness, and ethical comfort. Misalignment between institutional implementation strategies and frontline clinician attitudes may influence adoption, safe use, and long-term impact on patient care and research integrity. However, little is known about how health system–affiliated clinicians, educators, and researchers perceive AI use across professional roles and training levels. To this end, we conducted a survey-based study to gather information on how AI tool use is perceived by our colleagues.
Purpose:
To collect data regarding attitudes towards AI use tool among individuals affiliated with research activities, clinical operations, or with residency and fellowship programs.
Methods:
A REDCap survey was sent to emails on the Advocate Health Midwest Scientific Day listserv as of 10/17/25 (n=2,238). Each email address received a unique link, sent up to 11 times between 11/21/25-2/17/26. Survey questions gathered demographics (job role, clinical area, age group), prior AI tool knowledge, and attitudes regarding AI tool use in medical education, research, and direct patient care.
Results:
A total of 363 participants answered at least one AI tool-related question on the survey; 8 did not answer all survey questions. Respondents included attending physicians (32%), residents and fellows (19%), scientists and research support staff (16%), GME faculty physicians (15%), and other clinical and research-affiliated individuals (18%). Most respondents had exposure to AI tools prior to the survey (89%). The majority of participants believed AI tools could be used in some capacity in medical education (88%), in research with disclosure of use (85%), and in direct patient care (94%). Individuals selecting a job role of resident, fellow, GME faculty, or attending were more favorable of the use of AI tools in medical education (94% vs. 73%), research (89% vs. 78%), and patient care (97% vs. 87%) compared to individuals selecting a job role of scientist or research support.
Conclusion:
Participants were familiar with AI tools and generally supportive of their use in various aspects of medical education, research, and direct patient care. Clinical-focused individuals overall were more likely to support AI tool use compared to research-focused individuals.
Presentation Notes
Presented at Scientific Day; May 20, 2026; Milwaukee, WI.
Full Text of Presentation
wf_yes
Document Type
Oral/Podium Presentation
Examining Attitudes Towards AI Tools in Graduate Medical Education and Healthcare Practice
Background/Significance:
Artificial intelligence (AI) tools are rapidly being introduced into clinical and research workflows, including documentation support, data analysis, and decision augmentation. Successful integration of these tools will depend on user trust, perceived appropriateness, and ethical comfort. Misalignment between institutional implementation strategies and frontline clinician attitudes may influence adoption, safe use, and long-term impact on patient care and research integrity. However, little is known about how health system–affiliated clinicians, educators, and researchers perceive AI use across professional roles and training levels. To this end, we conducted a survey-based study to gather information on how AI tool use is perceived by our colleagues.
Purpose:
To collect data regarding attitudes towards AI use tool among individuals affiliated with research activities, clinical operations, or with residency and fellowship programs.
Methods:
A REDCap survey was sent to emails on the Advocate Health Midwest Scientific Day listserv as of 10/17/25 (n=2,238). Each email address received a unique link, sent up to 11 times between 11/21/25-2/17/26. Survey questions gathered demographics (job role, clinical area, age group), prior AI tool knowledge, and attitudes regarding AI tool use in medical education, research, and direct patient care.
Results:
A total of 363 participants answered at least one AI tool-related question on the survey; 8 did not answer all survey questions. Respondents included attending physicians (32%), residents and fellows (19%), scientists and research support staff (16%), GME faculty physicians (15%), and other clinical and research-affiliated individuals (18%). Most respondents had exposure to AI tools prior to the survey (89%). The majority of participants believed AI tools could be used in some capacity in medical education (88%), in research with disclosure of use (85%), and in direct patient care (94%). Individuals selecting a job role of resident, fellow, GME faculty, or attending were more favorable of the use of AI tools in medical education (94% vs. 73%), research (89% vs. 78%), and patient care (97% vs. 87%) compared to individuals selecting a job role of scientist or research support.
Conclusion:
Participants were familiar with AI tools and generally supportive of their use in various aspects of medical education, research, and direct patient care. Clinical-focused individuals overall were more likely to support AI tool use compared to research-focused individuals.
Affiliations
Advocate Lutheran General Hospital, Aurora UW Medical Group, Aurora Sinai Medical Center, Advocate Christ Medical Center, Aurora Health Center Midtown