Leveraging machine learning approach to identify relationships between practice facilitation strategies and practice...

Area of Science:

• Implementation Science
• Machine Learning
• Primary Care Research

Background:

• Machine learning (ML) offers advanced methods for extracting knowledge from complex data, beneficial for implementation science, quality improvement (QI), and primary care.
• The Implementation Research Logic Model (IRLM) provides a framework to understand relationships between practice characteristics, facilitation strategies, and outcomes in implementation research.
• This study applies ML and IRLM to a primary care QI program supported by practice facilitation.

Purpose of the Study:

• To illustrate a novel method combining ML and IRLM for analyzing implementation data.
• To assess the impact of practice attributes and facilitation strategies on the successful implementation of QI interventions.
• To identify relationships between contextual factors, facilitation strategies, and study outcomes in pragmatic research.

Main Methods:

• Applied advanced statistical methods within an ML framework to data from the Healthy Hearts in the Heartland (H3) study.
• Utilized Principal Component Analysis (PCA) for feature selection and Structural Equation Modeling (SEM) for analyzing relationships.
• Incorporated practice facilitators' knowledge for contextual factor validation.

Main Results:

• Identified 20 contextual factors and mapped practice facilitation strategies (Doing Tasks, Project Management, Consulting, Teaching, Coaching) to the IRLM.
• All five facilitation strategies demonstrated statistically significant associations with the implementation of QI interventions (P < 0.05).
• Facilitation strategies showed a greater impact on intervention implementation compared to the Change Process Capability Questionnaire (CPCQ) score.

Conclusions:

• The synergy of ML and IRLM effectively identifies links between context, implementation strategies, and outcomes in pragmatic research.
• All tested facilitation strategies were significantly associated with completed QI interventions.
• Understanding these relationships empowers practice facilitators to improve intervention adaptation, implementation, and capacity building in primary care settings.