Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations

Abstract

There is growing interest in understanding how generative artificial intelligence (GenAI) can support patients and caregivers in making informed health care decisions, known as patient-centered clinical decision support (PC CDS). In this viewpoint, we present example applications for GenAI-supported PC CDS for patients, caregivers, clinicians, and patient-clinician interactions and examine the opportunities, challenges, and potential solutions associated with these applications. We conducted a targeted document review of our work in the Agency for Healthcare Research and Quality's Clinical Decision Support Innovation Collaborative focusing on GenAI-enabled PC CDS, supplemented by snowball sampling and targeted searches to identify additional applications. Findings were refined and validated through solicited feedback from a 20-member multidisciplinary expert panel. Through our work, we highlight six critical needs that must be addressed to fully realize GenAI's potential in PC CDS: (1) engage and ensure representation of patients and caregivers in design and development; (2) build the science of effective PC CDS implementation to support patient engagement; (3) develop risk-based policies for when to use GenAI; (4) establish independent testing and vetting criteria; (5) periodically reassess to identify and address algorithmic drift and verify performance; and (6) establish policies to promote transparency and patient consent in the use of GenAI. Understanding the applications and their potential implications for health care quality is essential to further the beneficial, ethical, and safe development of GenAI-supported PC CDS.

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