Evaluating diagnosis-based risk-adjustment methods in a population with spinal cord dysfunction

Abstract

Warner G, Hoenig H, Montez M, Wang F, Rosen A. Evaluating diagnosis-based risk-adjustment methods in a population with spinal cord dysfunction. Arch Phys Med Rehabil 2004;85:218–26. Objective To examine performance of models in predicting health care utilization for individuals with spinal cord dysfunction. Design Regression models compared 2 diagnosis-based risk-adjustment methods, the adjusted clinical groups (ACGs) and diagnostic cost groups (DCGs). To improve prediction, we added to our model: (1) spinal cord dysfunction-specific diagnostic information, (2) limitations in self-care function, and (3) both 1 and 2. Setting Models were replicated in 3 populations. Participants Samples from 3 populations: (1) 40% of veterans using Veterans Health Administration services in fiscal year 1997 (FY97) (N=1,046,803), (2) veteran sample with spinal cord dysfunction identified by codes from the International Statistical Classification of Diseases, 9th Revision, Clinical Modifications (N=7666), and (3) veteran sample identified in Veterans Affairs Spinal Cord Dysfunction Registry (N=5888). Interventions Not applicable. Main outcome measures Inpatient, outpatient, and total days of care in FY97. Results The DCG models ( R 2 range, .22–.38) performed better than ACG models ( R 2 range, .04–.34) for all outcomes. Spinal cord dysfunction-specific diagnostic information improved prediction more in the ACG model than in the DCG model ( R 2 range for ACG, .14–.34; R 2 range for DCG, .24–.38). Information on self-care function slightly improved performance ( R 2 range increased from 0 to .04). Conclusions The DCG risk-adjustment models predicted health care utilization better than ACG models. ACG model prediction was improved by adding information.