Clinical Language Evaluation With AI for Residents (CLEAR2) - A Pilot Randomized Controlled Trial
The University of Texas Health Science Center, Houston
Summary
The purpose of this study is to refine and test existing enterprise-grade large language model (LLM) based on generative artificial intelligence (AI), to assess the feasibility and acceptability of LLM-based feedback, to assess the ability of LLM-based feedback to improve residents' communications,to explore the ability of standardized patients to assess residents' communication and to explore the ability of residents to self-assess their communication complexity
Eligibility
- Age range
- 18–50 years
- Sex
- All
- Healthy volunteers
- Yes
Inclusion Criteria: * McGovern Medical School (MMS) general surgery residents * postgraduate year (PGY) 1-5
Interventions
- Behavioraleducational LLM-based feedback tool
Participants will have their verbal communications with standardized patients (SP) regarding 3 different scenarios recorded, transcribed, and analyzed in real-time by the large language model (LLM) and will receive feedback as suggestions and alternative scripts. These will be reviewed by residents between SP scenarios
Location
- The University of Texas Health Science Center at HoustonHouston, Texas