Assessing ICD Data Quality and Its Impact on DRG Payments: Evidence from a Chinese Hospital

Abstract Background The International Statistical Classification of Diseases and Related Health Problems (ICD) codes play a critical role as fundamental data for hospital management and can significantly impact Diagnosis-Related Groups (DRGs). This study investigated the quality issues associated with ICD data and their impact on improper DRG payments. Methods Our study analyzed data from a Chinese hospital between 2016 and 2017 to evaluate the impact of ICD data quality on CN-DRG evaluation variables and payments. We assessed different stages of the ICD generation process and established a standardized process for evaluating ICD data quality and relevant indicators. The validation of the Data Quality Assessment (DQA) was confirmed through sampling data. Results This study of 85,522 inpatient charts found that gynecology had the highest and obstetrics had the lowest diagnosis agreement rates. Pediatrics had the highest agreement rates for MDC and DRG, while neonatal pediatrics had the lowest. The CMI of Coder- showed to be more reasonable than physician-, with increased DRG payments in obstetrics and gynecology. The DQA model revealed coding errors ranging from 40.32–65.18% for physician and 12.29–23.65% for coder. Payment discrepancies were observed, with physicians resulting in underpayment and coders displaying overpayment in some cases. Conclusion ICD data is crucial for effective healthcare management, and implementing standardized and automated processes to assess ICD data quality can improve data accuracy. This enhances the ability to make reasonable DRG payments and accurately reflects the quality of healthcare management.