Risk Adjustment Tools for Learning Health Systems: A Comparison of Dx CG and CMS ‐ HCC V21

Abstract

OBJECTIVE: To compare risk scores computed by DxCG (Verisk) and Centers for Medicare and Medicaid Services (CMS) V21. RESEARCH DESIGN: Analysis of administrative data from the Department of Veterans Affairs (VA) for fiscal years 2010 and 2011. STUDY DESIGN: We regressed total annual VA costs on predicted risk scores. Model fit was judged by R-squared, root mean squared error, mean absolute error, and Hosmer-Lemeshow goodness-of-fit tests. Recalibrated models were tested using split samples with pharmacy data. DATA COLLECTION: We created six analytical files: a random sample (n = 2 million), high cost users (n = 261,487), users over age 75 (n = 644,524), mental health and substance use users (n = 830,832), multimorbid users (n = 817,951), and low-risk users (n = 78,032). PRINCIPAL FINDINGS: The DxCG Medicaid with pharmacy risk score yielded substantial gains in fit over the V21 model. Recalibrating the V21 model using VA pharmacy data-generated risk scores with similar fit statistics to the DxCG risk scores. CONCLUSIONS: Although the CMS V21 and DxCG prospective risk scores were similar, the DxCG model with pharmacy data offered improved fit over V21. However, health care systems, such as the VA, can recalibrate the V21 model with additional variables to develop a tailored risk score that compares favorably to the DxCG models.

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