Artificial intelligence tools in supporting healthcare professionals for tailored patient care
Jiyeong Kim, Michael L. Chen, Shawheen J. Rezaei, Tina Hernandez‐Boussard, Jonathan H. Chen, Fátima Rodríguez, Summer S. Han, Rayhan A. Lal, Sun Ho Kim, Chrysoula Dosiou, Susan M. Seav, Tugce Akcan, Carolyn I. Rodríguez, Steven M. Asch, Eleni Linos
Abstract
Artificial intelligence (AI) tools to support clinicians in providing patient-centered care can contribute to patient empowerment and care efficiency. We aimed to draft potential AI tools for tailored patient support corresponding to patients' needs and assess clinicians' perceptions about the usefulness of those AI tools. To define patients' issues, we analyzed 528,199 patient messages of 11,123 patients with diabetes by harnessing natural language processing and AI. Applying multiple prompt-engineering techniques, we drafted a series of AI tools, and five endocrinologists evaluated them for perceived usefulness and risk. Patient education and administrative support for timely and streamlined interaction were perceived as highly useful, yet deeper integration of AI tools into patient data was perceived as risky. This study proposes assorted AI applications as clinical assistance tailored to patients' needs substantiated by clinicians' evaluations. Findings could offer essential ramifications for developing potential AI tools for precision patient care for diabetes and beyond.