The performance of administrative and self-reported measures for risk adjustment of veterans affairs expenditures

Health Services Research, June, 2005 by Matthew L. Maciejewski, Chuan-Fen Liu, Ann Derleth, Mary McDonell, Steve Anderson, Stephan D. Fihn

In all instances, measures based on administrative data performed better than measures based on serf-reported health, while age and gender explained the least variation (Table 3). Adjusted [R.sup.2] values were generally higher for the outpatient models and lowest for the inpatient models. In predicting total expenditures, the model incorporating PCS/MCS was the self-report model that exhibited the highest adjusted [R.sup.2] (1.8 percent), while of the models derived from diagnostic information, DCGs had the highest adjusted [R.sup.2] (7.2 percent). The pharmacy-based measure (RxRisk) had an adjusted [R.sup.2] of 4.7 percent and prior total expenditures had an adjusted [R.sup.2] of 4.8 percent. In predicting inpatient expenditures, the PCS/MCS model explained only 1.0 percent, the SIC 0.9 percent, and DCG 3.4 percent. The Charlson score was marginally more accurate ([R.sup.2] = 2.4 percent) than models based on CDPS, ACG, RxRisk, and prior inpatient expenditures.

The performance of outpatient cost models incorporating administrative data generally outperformed those based on self-report, while the DCG model was the best conventional risk adjuster ([R.sup.2] = 20.6 percent) followed closely by the ACG model ([R.sup.2] = 18.0 percent). Prior year outpatient expenditures, however, were more predictive than any other model ([R.sup.2] = 41.9 percent).

Based on the correlation matrix and the variance explained by single-measure models in Table 3, four sets of measures were combined into multimeasure models because the correlations between measures ranged widely, measures had different data sources, and each model had at least one variable that predicted expenditure variation well. The four models were: (1) DCG and prior expenditure, (2) DCG and RxRisk, (3) DCG, RxRisk, and prior expenditure, and (4) DCG, RxRisk, prior expenditure, and PCS/MCS from the SF-36. These models are compared with the eight single-measure models to determine if combined models had greater predictive power. The combined models had marginally higher adjusted [R.sup.2]s than the single-measure total and inpatient expenditure models discussed above, with the greatest prediction coming from the model that incorporated DCG, DCG, RxRisk, prior expenditure, and SF-36 measures. This model was also the most predictive of outpatient expenditures.

When total costs were segmented by quintiles, all models significantly over-estimated expenditures in the lowest quintile and under-estimated those in the highest quintile, although this was less apparent for models incorporating total costs, ACGs and DCGs that exhibited the highest adjusted [R.sup.2] values (Table 4). The combined models improved on the single measure models by further reducing over-prediction in the two lowest quintiles and modestly improving under-prediction in the highest expenditure quintile. The adjusted [R.sup.2] was identical (7.74 percent) for the combined model of DCG and prior expenditure and that of DCG and RxRisk, but the predictive ratio for the highest quintile was most improved in the combined model of DCG and RxRisk. The predictive ratios for the remaining quintiles were similar between the two models.