Customer Stories

Artificial Intelligence (AI) in Clinical Skills Assessments

February 3, 2026

Tara G. Edmonds, Tanci Clark, Zac Babb, John Andrews III, and F. Shawn Galin
University of Alabama at Birmingham / Birmingham, AL
Zoltan Fodroczi
Elevate Healthcare: elevatehealth.net

Introduction

Simulation-based education has become a cornerstone of preparing health professions learners for safe, effective clinical practice.

Objective Structured Clinical Examinations (OSCEs) and standardized patient (SP) encounters are widely used to assess clinical skills, communication, and clinical reasoning in a structured and reproducible way; nevertheless, maintaining high-quality assessment at scale is increasingly difficult. Recruiting and training raters, ensuring SP checklist quality, and reviewing video recordings are time-and labor-intensive processes.

In parallel, recent advances in artificial intelligence (AI)—particularly large language models (LLMs)—have opened new possibilities for automating parts of documentation review and scoring, while keeping human faculty firmly “in the loop.”

This case study describes a collaborative pilot between the University of Alabama at Birmingham (UAB) Office of Standardized Patient Education (OSPE) and Elevate Healthcare, evaluating the feasibility and quality of AI-graded transcripts for assessing SP checklist performance in a clinical skills assessment context.

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