Leveraging machine learning approach to identify relationships between practice facilitation strategies and practice characteristics based on the implementation research logic model.

ABSTRACT:

Background

Machine learning (ML)-a field of study dedicated to the principled extraction of knowledge from complex data-can benefit implementation science, quality improvement (QI), and primary care research. Given the general complexity of implementation research and the need to develop strategies for understanding relationships among practice characteristics and practice facilitation strategies, we chose the Implementation Research Logic Model (IRLM) as an underlying structure for the data and to identify relationships that might be associated with outcomes. This study illustrates this novel method involving ML and an IRLM in the context of a practice facilitation-supported QI program in primary care.

Methods

We applied advanced statistical methods within a machine learnin

SUBMITTER: Ye J 

PROVIDER: S-EPMC12924320 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature