Process-Level Assessment of Diagnostic Reasoning With a Clinical Simulation Video and Free-Text Responses: Nationwide Cross-Sectional Study of Resident Physicians (Preprint)

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BACKGROUND Multiple-choice assessments may not fully capture how learners generate diagnostic hypotheses, justify them using multimodal clinical information, and translate them into initial management. Clinical simulation video (CSV) items with free-text responses may provide process-level information, but coding such responses at a national scale is resource-intensive. OBJECTIVE The study examines whether the following three process markers derived from a CSV free-text item are associated with General Medicine In-Training Examination (GM-ITE) total scores: diagnostic hypothesis generation, diagnostic justification, and initial management. METHODS This cross-sectional study used data from the 2023 GM-ITE. A patient-reenactment CSV item depicting hypoglycemia as a stroke mimic was administered as an add-on and excluded from the official score. Eligible participants were examinees who completed the item and consented to its use in research. Free-text responses were normalized using a constrained generative AI-assisted workflow and independently re-coded by at least two authors using an expert-informed codebook. Associations between the three process markers and GM-ITE total scores were evaluated. Joint patterns of hypoglycemia listing and hypoglycemia-directed management were examined using four mutually exclusive groups, and an exploratory diagnosis-by-management interaction was tested. RESULTS A total of 6,584 participants were included in the analytic cohort. Hypoglycemia was listed first by 248 (3.8%) participants and within the top three by 1,363 (20.7%). Unadjusted GM-ITE total scores were 48.3, 46.8, and 44.4 among participants who listed hypoglycemia first, second or third, and not within the top three, respectively (P<.001). Among participants who listed hypoglycemia, scores were 43.9, 46.2, 46.1, and 47.6 across clue-category counts of 0, 1, 2, and 3 or more, respectively (P=.001). Hypoglycemia-directed management was associated with a higher score among participants who listed hypoglycemia (47.2 vs 45.5; mean difference=1.68, 95% CI 0.47-2.88), but with a lower score among those who did not list hypoglycemia (42.0 vs 44.5; mean difference=-2.48, 95% CI -3.41 to -1.56; interaction P<.001). In adjusted sensitivity analyses, listing hypoglycemia first (adjusted coefficient=3.19, 95% CI 2.27-4.11), each additional clue category (adjusted coefficient=0.82, 95% CI 0.50-1.14), and hypoglycemia-directed management (adjusted coefficient=1.43, 95% CI 1.02-1.85) remained associated with higher GM-ITE total scores. The diagnosis-by-management interaction remained statistically significant after adjustment (adjusted interaction coefficient=2.90, 95% CI 1.53-4.26; P<.001). CONCLUSIONS Process markers derived from a CSV free-text response were associated with an established measure of clinical competence. The alignment between an explicitly generated diagnostic hypothesis and the selected management action may provide additional information beyond either component alone. These findings suggest the feasibility of using human-verified, AI-assisted normalization to analyze free-text responses in large cohorts.

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