Adoption of Machine Learning in US Hospital Electronic Health Record Systems: Retrospective Observational Study.

ABSTRACT:

Background

While machine learning (ML) technologies have shifted from development to real-world deployment over the past decade, US health care providers and hospital administrators have increasingly embraced ML, particularly through its integration with electronic health record (EHR) systems. This evolving landscape underscores the need for empirical evidence on ML adoption and its determinants; however, the relationship between hospital characteristics and ML integration within EHR systems remains insufficiently explored.

Objective

This study aimed to examine the current state of ML adoption within EHR systems across US general acute care hospitals and to identify hospital characteristics associated with ML implementation.

Methods

We used linked data between the 202

SUBMITTER: Huang H 

PROVIDER: S-EPMC12688049 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature