Use of Diagnosis-Based Risk Adjustment Models to Predict Individual Health Care Expenditure under the National Health Insurance System in Taiwan

Abstract

Diagnostic information has been extensively studied and employed in the prediction of risk adjusted capitation payments in some countries. Nevertheless, few studies have been dedicated to the development of diagnosis-based risk adjusters in Taiwan. The purposes of this study were to develop outpatient diagnosis-based risk adjusters for a model of Taiwan's National Health Insurance (NHI) system and to evaluate the predictability of the risk adjustment models generated utilizing these adjusters. Using a 2% random sample of 371,620 NHI enrollees, 5 risk adjustment models--i.e., demographic, inpatient diagnostic information outpatient diagnostic information, full diagnostic information, and prior utilization models--were evaluated with respect to predictive R2 and predictive ratios. While inpatient diagnosis-based risk adjusters were borrowed from previous research, outpatient diagnosis-based risk adjusters, referred to as Taiwan Ambulatory Spending Groups (TASGs), were developed based on 1996 claims data. The values of predictive R2 for the 5 risk adjustment models showed that the inclusion of outpatient diagnostic information considerably improved the predictability of the risk adjustment models for Taiwan's NHI system. Moreover, the predictive ratios revealed that the full diagnostic information model would reimburse different risk subgroups more fairly than the demographic, inpatient diagnostic information, and outpatient diagnostic information models and also outperform the prior utilization model with respect to disease risk groups. The risk adjustment model including the TASG risk adjusters can significantly improve predictability and can be employed to assess the NHI's current and proposed reform measures.