Risk Stratification Methods and Provision of Care Management Services in Comprehensive Primary Care Initiative Practices

Abstract

Purpose: Risk-stratified care management is essential to improving population health in primary care settings, but evidence is limited on the type of risk stratification method and its association with care management services.

Methods: We describe risk stratification patterns and association with care management services for primary care practices in the Comprehensive Primary Care (CPC) initiative. We undertook a qualitative approach to categorize risk stratification methods being used by CPC practices and tested whether these stratification methods were associated with delivery of care management services.

Results: CPC practices reported using 4 primary methods to stratify risk for their patient populations: a practice-developed algorithm (n = 215), the American Academy of Family Physicians' clinical algorithm (n = 155), payer claims and electronic health records (n = 62), and clinical intuition (n = 52). CPC practices using practice-developed algorithm identified the most number of high-risk patients per primary care physician (282 patients, P = .006). CPC practices using clinical intuition had the most high-risk patients in care management and a greater proportion of high-risk patients receiving care management per primary care physician (91 patients and 48%, P =.036 and P =.128, respectively).

Conclusions: CPC practices used 4 primary methods to identify high-risk patients. Although practices that developed their own algorithm identified the greatest number of high-risk patients, practices that used clinical intuition connected the greatest proportion of patients to care management services.

Keywords: chronic care; comprehensive health care; patient care management; payment reform; primary health care.