INTRODUCTION: Health care reimbursement is increasingly based on quality. Little is known about how clinic-level patient characteristics affect quality, particularly in community health centers (CHCs). METHODS: Using data from electronic health records for 4019 diabetic patients from 23 primary care CHCs in the OCHIN practice-based research network, we calculated correlations between a clinic's patient panel characteristics and rates of delivery of diabetes preventive services in 2007. Using regression models, we estimated the proportion of variability in clinics' preventive services rates associated with the variability in the clinics' patient panel characteristics. We also explored whether clinics' performance rates were affected by how patient panel denominators were defined. RESULTS: Clinic rates of hemoglobin testing, influenza immunizations, and lipid screening were positively associated with the percentage of patients with continuous health insurance coverage and negatively associated with the percentage of uninsured patients. Microalbumin screening rates were positively associated with the percentage of racial minorities in a clinic's panel. Associations remained consistent with different panel denominators. CONCLUSIONS: Clinic variability in delivery rates of preventive services correlates with differences in clinics' patient panel characteristics, particularly the percentage of patients with continuous insurance coverage. Quality scores that do not account for these differences could create disincentives to clinics providing diabetes care for vulnerable patients.
INTRODUCTION: Health care reimbursement is increasingly based on quality. Little is known about how clinic-level patient characteristics affect quality, particularly in community health centers (CHCs). METHODS: Using data from electronic health records for 4019 diabeticpatients from 23 primary care CHCs in the OCHIN practice-based research network, we calculated correlations between a clinic's patient panel characteristics and rates of delivery of diabetes preventive services in 2007. Using regression models, we estimated the proportion of variability in clinics' preventive services rates associated with the variability in the clinics' patient panel characteristics. We also explored whether clinics' performance rates were affected by how patient panel denominators were defined. RESULTS: Clinic rates of hemoglobin testing, influenza immunizations, and lipid screening were positively associated with the percentage of patients with continuous health insurance coverage and negatively associated with the percentage of uninsured patients. Microalbumin screening rates were positively associated with the percentage of racial minorities in a clinic's panel. Associations remained consistent with different panel denominators. CONCLUSIONS: Clinic variability in delivery rates of preventive services correlates with differences in clinics' patient panel characteristics, particularly the percentage of patients with continuous insurance coverage. Quality scores that do not account for these differences could create disincentives to clinics providing diabetes care for vulnerable patients.
Entities:
Keywords:
Diabetes Mellitus; Health Care Systems; Health Insurance; Health Policy
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