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Risk adjustment, which reflects the baseline characteristics and risk factors of a patient, plays a crucial role in ensuring fair hospital performance assessment.This study aimed to examine risk adjustment methods in the National Quality Assessment Program (NQAP) of the Health Insurance Review & Assessment Service (HIRA) and provide recommendations.The goal of the NQAP is to enhance the quality of healthcare services and improve patient safety.The outcome indicators measured in the NQAP were extracted from the Quality Assessment Information Bank System operated by the HIRA.A literature review was conducted to identify the data sources, statistical methods, and risk factors of the risk-adjustment models for these outcome indicators.As of 2024, among the 36 assessment items in the NQAP, 11 have applied risk adjustment models to calculate outcome indicators.A total of 23 outcome indicators were adjusted for patient severity, most of which were indicators of mortality or readmission.Logistic and linear regression models were applied to develop risk adjustment models, and the final models were established through model validation.The risk adjustment models included demographic factors, clinical factors, and medical history or comorbidities.Comprehensive data collection incorporating clinical evidence and data quality management is essential for risk adjustment.Moreover, regularly updating models based on the latest data is crucial to ensure the accuracy and reliability of the assessment results.
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Kyoung Hoon Kim (2025) studied this question.
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