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Drivers and effects of DRG coding abuse based on hot cheese model: a qualitative study
Shuo Liu1, Chang-Chang Chen2, Li Zhao1
1First Affiliated Hospital of Air Force Medical University, Xi'an, China.
Frontiers in Public Health
|June 29, 2026
Summary
Healthcare providers
Area of Science:
- Health Economics
- Healthcare Management
- Medical Coding
Background:
- China's national Healthcare Security Diagnosis-Related Groups (CHS-DRG) reform, initiated 6 years ago, faces diminishing returns in controlling medical insurance expenditures.
- Healthcare provider gaming behaviors are a primary reason for the reduced effectiveness of the CHS-DRG reform.
- Understanding DRG coding abuse is crucial for optimizing healthcare insurance fund management.
Purpose of the Study:
- To investigate the internal drivers and effects of DRG downcoding, upcoding, and ambiguous cases within the CHS-DRG framework.
- To propose targeted intervention strategies by analyzing the interrelationships of DRG coding behaviors.
- To apply the hot cheese model for a comprehensive analysis of DRG coding abuse.
Main Methods:
- Qualitative analysis using semi-structured interviews with 22 hospital participants in Shaanxi Province, China.
- Application of the hot cheese model to systematically examine DRG coding abuse.
- Analysis of manifestations, subjective/objective driving factors, and internal/external effects of coding abuse.
Main Results:
- Identified subjective and objective drivers contributing to DRG coding abuse.
- Established a hot cheese model with three defensive layers: hospital organization environment, initial medical record documentation, and review processes.
- Revealed the multifaceted effects of DRG coding abuse on healthcare insurance funds.
Conclusions:
- Differentiate between subjective and objective drivers of DRG upcoding for effective intervention.
- Acknowledge the significant impact of DRG downcoding and ambiguous cases.
- Recommend future research on natural language processing for intelligent early warning systems in medical record pre-coding.
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