Artificially Intelligent Simulated Patients in Undergraduate Surgical Teaching: A Single Blinded Randomized Controlled Study

INTRODUCTION: Self-directed learning (SDL) and reflection are critically important for clinicians. There is limited evidence describing the utilization of artificial intelligence (AI) to support medical SDL. AI simulated patients (AISP) may allow for high-fidelity, reflective educational interactions. We aimed to determine how SDL with AISP interaction compared to standard SDL in the development of clinical reasoning skills. METHODS: This was a single-institution randomized controlled study in early clinical years' undergraduate students, learning about gallstone disease. For 90% power and a 20% noninferiority margin, 36 participants were randomized either to an intervention group using an AISP or to a control group using current educational resources. Both groups underwent a standardized clinical skills assessment. Quantitative and qualitative data were collected. RESULTS: Twenty-seven participants completed the study. The intervention group demonstrated statistical noninferiority compared with the control group (assessment scores of 13.1 vs. 12.1, respectively, p = 0.11). In addition, there were fewer borderline grades, and significantly more distinction grades in the intervention group than control (6 vs. 1, respectively, p = 0.037), suggesting the AISP may have improved performance in clinical management. The qualitative data suggested widespread satisfaction and enthusiasm for AISPs. CONCLUSION: Our results suggest that AISPs are comparable to traditional resources in developing undergraduate clinical skills, and may contribute to improved academic performance in undergraduate surgery. Globally, there is an appetite for their introduction into the clinical curriculum. Real patient interaction is the standard. However, AISPs may have a supplementary role and are likely to become increasingly prominent in medical curricula.