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A Methodology for Creating Patient Relevant Questions Suitable for Evaluating AI Generated Health Advice
Suhani Goyal1,2, Hua-Hsin Tai3, Elisabeth Rosen3
1Clinical Informatics Center, University of Texas Southwestern Health System, Dallas, TX, USA.
None:
Artificial intelligence (AI) holds potential to assist with patient-facing communication. However, patients' interpretation and trust in AI-generated clinical responses remains underexplored. In this work, we describe a protocol for developing and validating a set of realistic patient-portal scenarios aimed at understanding how patients perceive AI-generated versus physician-generated responses to common patient portal questions. Using a modified Delphi approach and real-world clinical context, we constructed six clinical scenarios with parallel responses generated by both physicians and ChatGPT. This methods paper outlines the design, data sourcing, consensus process, and structured evaluation steps used in this study, forming a basis for future validation and implementation.
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