George Washington University School of Medicine and Health Sciences Washington, DC
Athanasios S. Naum, BS1, Robert Gordon, DO2, Maxwell S. Madani, BA1, Lucas Miecho. Heilbroner, BA1, Kris Kokoneshi, BA1, Abdelrhman Refaey, MD3, Calvin Tabetah, MD1, Mrudula Bandaru, MD2, Zeina Bani Hani, MBBS2, Susie J. Park, MD1, Valerie S. Stark, MD, MPH2, Ahmed Ebeid, MD4, Marie L. Borum, MD, EdD, MPH, FACG3 1George Washington University School of Medicine and Health Sciences, Washington, DC; 2Department of Medicine, George Washington University School of Medicine and Health Sciences, Washington, DC; 3Division of Gastroenterology and Liver Disease, Department of Medicine, George Washington University School of Medicine and Health Sciences, Washington, DC; 4Transplant Institute, Department of Surgery, George Washington University School of Medicine and Health Science, Washington, DC Introduction: Artificial intelligence (AI) is increasingly utilized in healthcare settings, offering transformative potential across clinical domains. In 2024, 66% of physicians surveyed reported AI use in clinical practice compared to 38% in 2023. The rapid adoption of AI in clinical settings without wide-spread formalized training raises concern for potential misuse. This study aims to compare AI use across degrees of training from medical students to attendings and evaluate differences in use between gastroenterology (GI) versus internal medicine providers (IM). Methods: A cross-sectional survey was conducted utilizing REDCap software. The survey included 25 items designed to collect demographic data as well as information regarding AI use and training in clinical settings. The survey was distributed to a convenience sample of healthcare professionals including medical students, residents, fellows, and attendings. Data was collected over a 2-month period. Results were analyzed utilizing descriptive and inferential statistics. Statistical significance was set at p< 0.05. Results: There were 120 respondents including 26 attendings, 11 fellows, 26 residents, and 57 medical students. 83.5% of all respondents report AI use, with 42.6% reporting daily use. 61.5% of all attendings reported clinical AI use compared to 92.3% of residents (p=0.008) and 87.8% of medical students (p=0.006). 73.7% of GI providers, including fellows and attendings, report clinical AI use. 47.3% of GI providers report not feeling confident in their ability to effectively use AI in clinical settings compared to 12% of their IM counterparts (p=0.001). No GI provider reported any formal education in the use of artificial intelligence compared to 25% of IM providers (p=0.018). 56.1% of IM providers reported knowledge of which AI programs were HIPAA compliant vs. 15.8% of GI providers (p=0.003). 100% of GI providers reported they believe that formal AI education should be incorporated into medical education. Discussion: The use of AI in medicine is increasing rapidly with over 70% of GI providers reporting its use in their clinical practice. However, GI providers are significantly less confident in their ability to effectively use AI compared to their IM counterparts and have had significantly less formal training in its clinical use. Moreover, medical students and residents use AI significantly more than attendings. With the increasing use of AI as a clinical tool, it is crucial to incorporate education on its safe and effective use.
Disclosures: Athanasios Naum indicated no relevant financial relationships. Robert Gordon indicated no relevant financial relationships. Maxwell Madani indicated no relevant financial relationships. Lucas Heilbroner indicated no relevant financial relationships. Kris Kokoneshi indicated no relevant financial relationships. Abdelrhman Refaey indicated no relevant financial relationships. Calvin Tabetah indicated no relevant financial relationships. Mrudula Bandaru indicated no relevant financial relationships. Zeina Bani Hani indicated no relevant financial relationships. Susie Park indicated no relevant financial relationships. Valerie Stark indicated no relevant financial relationships. Ahmed Ebeid indicated no relevant financial relationships. Marie Borum indicated no relevant financial relationships.
Athanasios S. Naum, BS1, Robert Gordon, DO2, Maxwell S. Madani, BA1, Lucas Miecho. Heilbroner, BA1, Kris Kokoneshi, BA1, Abdelrhman Refaey, MD3, Calvin Tabetah, MD1, Mrudula Bandaru, MD2, Zeina Bani Hani, MBBS2, Susie J. Park, MD1, Valerie S. Stark, MD, MPH2, Ahmed Ebeid, MD4, Marie L. Borum, MD, EdD, MPH, FACG3. P6178 - Artificial Intelligence Use Patterns Amongst Medical Trainees and Professionals: An Institutional Study, ACG 2025 Annual Scientific Meeting Abstracts. Phoenix, AZ: American College of Gastroenterology.
