Implementing Risk Stratification in Primary Care: Challenges and Strategies.

Area of Science:

• Health Services Research
• Primary Care Medicine
• Health Informatics

Background:

• Risk stratification (RS) in primary care aids in understanding patient needs.
• RS may improve health outcomes and reduce costs by targeting high-need patients.

Purpose of the Study:

• To understand key considerations and experiences of primary care practices implementing RS models.

Main Methods:

• Conducted semistructured interviews with 34 stakeholders from 15 primary care practices.
• Qualitatively analyzed interview data regarding RS implementation.

Main Results:

• Key decisions involved choosing algorithms (established vs. self-created), using clinical intuition, assigning risk scores, and integrating RS into care delivery.
• Practices using clinical intuition found it time-consuming but trusted scores more; data limitations and score display were challenges.
• Gaining care team buy-in required iterative improvements and workflow integration.

Conclusions:

• Iterative approaches to RS implementation are crucial, influenced by practice capacity (health IT, staffing, resources).
• Successful RS involves iterative changes, combining automation with human processes, staff education, and readily accessible risk scores.