The need for integrated clinical and administrative data models for risk adjustment in assessment of the cost transplant care.

Abstract

Value-based purchasing requires accurate techniques to appropriately measure both outcomes and cost with robust adjustment for differences in severity of illness. Traditional methods to adjust cost estimates have exclusively used administrative data derived from billing claims to identify comorbidity and complications. Transplantation uniquely has accurate national clinical registry data that can be used to supplement administrative data. Administrative claims from the Vizient, Inc, Clinical Data Base (CDB) were linked with clinical records from the Scientific Registry for Transplant Recipients for 76 liver and 109 kidney transplant programs. Using either or both datasets, we fitted a regression model to the total direct cost of care for 16,649 kidney and 6058 liver transplants. The proportion of variation explained by these risk-adjustment models increased significantly when combined administrative and clinical data were used for kidney (administrative only R2 =.069, clinical only R2 =.047, combined R2 =.14, p<.0001) and liver (administrative only R2 =.28, clinical only R2 =.25, combined R2 =.33, p<.0001). Incorporating accurate clinical data into risk-adjustment methodologies can improve risk adjustment methodologies; however, as majority of variation in cost remains unexplained by these risk-adjustment models further work is needed to accuracy assess transplant value.