Artificial intelligence tools in supporting healthcare professionals for tailored patient care

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.

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Publication Details

Journal
npj Digital Medicine
Published
2025-04-16
DOI
https://doi.org/10.1038/s41746-025-01604-3
Citations
12
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
29.77

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article

Artificial intelligence tools in supporting healthcare professionals for tailored patient care

Michael L. Chen, Tina Hernandez‐Boussard, Fátima Rodríguez, Carolyn I. Rodríguez et al.
12 citations
npj Digital Medicine
Machine Learning in Healthcare
29.77
article

Artificial intelligence tools in supporting healthcare professionals for tailored patient care

Michael L. Chen, Tina Hernandez‐Boussard, Fátima Rodríguez, Carolyn I. Rodríguez, Jonathan H. Chen, Eleni Linos, Shawheen J. Rezaei, Steven M. Asch, Sun Ho Kim, Summer S. Han, Jiyeong Kim, Rayhan A. Lal, Susan M. Seav, Chrysoula Dosiou, Tugce Akcan
article en
12 citations

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.

npj Digital MedicineVol. 8(1)
VA Palo Alto Health Care System (US), Cardiovascular Institute of the South (US), Stanford University (US)
National Institutes of Health
Openalex Percentile: Top 0%
Machine Learning in Healthcare
29.77
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