Warner Grace, Hoenig Helen, Montez Maria, Wang Fei, Rosen Amy
Center for Health Quality, Outcomes, and Economic Research, VAMC, Bedford, MA, USA.
Arch Phys Med Rehabil. 2004 Feb;85(2):218-26. doi: 10.1016/s0003-9993(03)00768-8.
To examine performance of models in predicting health care utilization for individuals with spinal cord dysfunction.
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.
Models were replicated in 3 populations.
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).
Not applicable.
Inpatient, outpatient, and total days of care in FY97.
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).
The DCG risk-adjustment models predicted health care utilization better than ACG models. ACG model prediction was improved by adding information.
