Comparison of diagnosis-based risk adjustment methods for episode-based costs to apply in efficiency measurement

BACKGROUND: The recent rising health spending intrigued efficiency and cost-based performance measures. However, mortality risk adjustment methods are still under consideration in cost estimation, though methods specific to cost estimate have been developed. Therefore, we aimed to compare the performance of diagnosis-based risk adjustment methods based on the episode-based cost to utilize in efficiency measurement. METHODS: We used the Health Insurance Review and Assessment Service–National Patient Sample as the data source. A separate linear regression model was constructed within each Major Diagnostic Category (MDC). Individual models included explanatory (demographics, insurance type, institutional type, Adjacent Diagnosis Related Group [ADRG], diagnosis-based risk adjustment methods) and response variables (episode-based costs). The following risk adjustment methods were used: Refined Diagnosis Related Group (RDRG), Charlson Comorbidity Index (CCI), National Health Insurance Service Hierarchical Condition Categories (NHIS-HCC), and Department of Health and Human Service-HCC (HHS-HCC). The model accuracy was compared using R-squared (R(2)), mean absolute error, and predictive ratio. For external validity, we used the 2017 dataset. RESULTS: The model including RDRG improved the mean adjusted R(2) from 40.8% to 45.8% compared to the adjacent DRG. RDRG was inferior to both HCCs (RDRG adjusted R(2) 45.8%, NHIS-HCC adjusted R(2) 46.3%, HHS-HCC adjusted R(2) 45.9%) but superior to CCI (adjusted R(2) 42.7%). Model performance varied depending on the MDC groups. While both HCCs had the highest explanatory power in 12 MDCs, including MDC P (Newborns), RDRG showed the highest adjusted R(2) in 6 MDCs, such as MDC O (pregnancy, childbirth, and puerperium). The overall mean absolute errors were the lowest in the model with RDRG ($1,099). The predictive ratios showed similar patterns among the models regardless of the subgroups according to age, sex, insurance type, institutional type, and the upper and lower 10th percentiles of actual costs. External validity also showed a similar pattern in the model performance. CONCLUSIONS: Our research showed that either NHIS-HCC or HHS-HCC can be useful in adjusting comorbidities for episode-based costs in the process of efficiency measurement. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10282-4.