Adapting the Rx-Risk-V for mortality prediction in outpatient populations

We sought to operationalize, test, and validate an outpatient pharmacy-based case-mix adjuster.

Outpatients from the Department of Veterans Affairs (VA) prescribed a nonsteroidal anti-inflammatory drug (NSAID) or cyclooxygenase-2 selective drug during 2002 were identified. We updated and extended the Rx-Risk-V by adding 26 additional disease categories and mapping them to VA drug-class codes; derived empirical weights for each from a logistic model of 1-year mortality; adjusted for age, race and sex; and scored the weights into 1 measure of comorbidity. We compared the weighted score to the Deyo diagnosis-based comorbidity index and validated it in a national cohort of 260,321 outpatients with chronic heart failure (CHF).

One-year mortality among the 724,270-outpatient NSAID cohort was 1.6% (n = 11,766). Using a baseline model of age, race, and gender (c-index = 0.716), we found that the Deyo measure improved the prediction of mortality (c-index = 0.765), and the pharmacy comorbidity score further improved the prediction (c-index = 0.782), an increase of 25.8%. Using both, we found further improvement (c-index = 0.792). Among the CHF cohort, 9.7% (n = 25,251) died within 1 year. Performance of the baseline model controlling for age, race, and gender (c index = 0.620) improved with addition of the pharmacy comorbidity score (c index = 0.689), compared with the addition of the Deyo measure (c index = 0.651), an increase of 55.1%. Together, they slightly improved prediction in CHF patients (c index = 0.695).

The updated and extended Rx-Risk-V is useful for case-mix adjustment of mortality in an outpatient population.