Artificial intelligence integration in healthcare: perspectives and trends in a survey of U.S. health system leaders

TLDR

Examination of changes in AIDPM integration and governance since 2021 focuses on large language models and health equity considerations, with a particular focus on large language models and health equity considerations.

摘要

Background The healthcare sector is rapidly integrating artificial intelligence-derived predictive models (AIDPM) to enhance clinical decision support, operational efficiency, and patient experiences. However, research on management strategies for AIDPM acquisition, deployment, and governance remains limited. This study examines changes in AIDPM integration and governance since 2021, with a particular focus on large language models and health equity considerations. Results Our survey of health system leaders achieved a 49% response rate (32/65). While 84% of institutions reported using AIDPM in clinical practice, only 53% had established dedicated teams for these models. Compared to 2021, there was a significant increase in representation from experts in clinical informatics, operations, and quality improvement on AIDPM teams. Most organizations (41%) primarily purchased AIDPM from external