Primary care physicians' experiences with case finding for practice-based care management.

Area of Science:

• Health Services Research
• Primary Care Medicine
• Digital Health

Background:

• Effective case finding is crucial for care management program success, impacting health outcomes and costs.
• Current research predominantly relies on claims data for case finding.
• Primary care physicians' (PCPs) selection processes for care management are not fully understood.

Purpose of the Study:

• To explore how PCPs identify patients for practice-based care management.
• To investigate how risk prediction models can supplement PCP-led case finding.

Main Methods:

• Qualitative study involving 12 semi-structured interviews with PCPs from 10 primary care practices in Germany.
• Interviews focused on patient selection criteria and evaluation of claims data-based risk prediction.
• Qualitative content analysis was performed using ATLAS.ti software.

Main Results:

• Physician criteria for patient selection included interpretation of eligibility criteria, physician-related factors (e.g., "knowing the patient"), and patient-related factors (e.g., willingness and ability to participate, manageable care needs).
• PCPs indicated that claims data-based risk prediction could support their existing case-finding methods.
• Key patient factors included "willingness to participate," "ability to participate" (language skills, cognitive status), and "manageable care needs."

Conclusions:

• A combined approach using PCP clinical judgment and claims data risk modeling may optimize case finding for primary care management.
• Further research is necessary to determine the most effective case-finding strategies for practice-based care management.