Assessing ICD Data Quality and Its Impact on DRG Payments: Evidence from a Women and Children Special Hospital in China.

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 from 2016-2017 to evaluate the impact of ICD data quality on Chinese Diagnosis-related Group (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 Case Mix Index (CMI) of Coder-coded data showed to be more reasonable than physician-coded data, with increased DRG payments in obstetrics and gynecology. The DQA model revealed coding errors ranging from 40.3 percent to 65.1 percent for physician and 12.2 percent to 23.6 percent 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.