OBJECTIVES: The authors explored the role of casemix adjustment when profiling outcomes of ambulatory care. METHODS: The authors reviewed the medical records of 656 patients with hypertension, diabetes, or chronic obstructive pulmonary disease (COPD) receiving care at one of three Department of Veterans Affairs medical centers. Outcomes included measures of physiological control for hypertension and diabetes, and of exacerbations for COPD. Predictors of poor outcomes, including physical examination findings, symptoms, and comorbidities, were identified and entered into regression models. Observed minus expected performance was described for each site, both before and after casemix adjustment. RESULTS: Risk-adjustment models were developed that were clinically plausible and had good performance properties. Differences existed among the three sites in the severity of the patients being cared for. For example, the percentage of patients expected to have poor blood pressure control were 35% at site 1, 37% at site 2, and 44% at site 3 (P < 0.01). Casemix-adjusted measures of performance were different from unadjusted measures. Sites that were outliers (P < 0.05) with one approach had observed performance no different from expected with another approach. CONCLUSIONS: Casemix adjustment models can be developed for outpatient medical conditions. Sites differ in the severity of patients they treat, and adjusting for these differences can alter judgments of site performance. Casemix adjustment is necessary when profiling outpatient medical conditions.
OBJECTIVES: The authors explored the role of casemix adjustment when profiling outcomes of ambulatory care. METHODS: The authors reviewed the medical records of 656 patients with hypertension, diabetes, or chronic obstructive pulmonary disease (COPD) receiving care at one of three Department of Veterans Affairs medical centers. Outcomes included measures of physiological control for hypertension and diabetes, and of exacerbations for COPD. Predictors of poor outcomes, including physical examination findings, symptoms, and comorbidities, were identified and entered into regression models. Observed minus expected performance was described for each site, both before and after casemix adjustment. RESULTS: Risk-adjustment models were developed that were clinically plausible and had good performance properties. Differences existed among the three sites in the severity of the patients being cared for. For example, the percentage of patients expected to have poor blood pressure control were 35% at site 1, 37% at site 2, and 44% at site 3 (P < 0.01). Casemix-adjusted measures of performance were different from unadjusted measures. Sites that were outliers (P < 0.05) with one approach had observed performance no different from expected with another approach. CONCLUSIONS: Casemix adjustment models can be developed for outpatient medical conditions. Sites differ in the severity of patients they treat, and adjusting for these differences can alter judgments of site performance. Casemix adjustment is necessary when profiling outpatient medical conditions.
Authors: Chuan-Fen Liu; Anne E Sales; Nancy D Sharp; Paul Fishman; Kevin L Sloan; Jeff Todd-Stenberg; W Paul Nichol; Amy K Rosen; Susan Loveland Journal: Health Serv Res Date: 2003-10 Impact factor: 3.402