Statistical Insight into China's Indigenous Diagnosis-Related-Group System Evolution

Area of Science:

• Health Economics
• Healthcare Management
• Public Health Policy

Background:

• Diagnosis-Related Groups (DRG) are widely used globally to control healthcare costs and enhance hospital efficiency.
• China has developed its own DRG-based payment systems: Single Disease Payment (SDP), DRGs, and the Big Data Diagnosis-Intervention Packet (DIP).

Purpose of the Study:

• To evaluate the effectiveness of China's indigenized DRG payment systems, specifically SDP and DRGs, using cholecystitis as a case study.
• To analyze the evolution and application of DRG systems in China.
• To introduce and preliminarily assess the Big Data Diagnosis-Intervention Packet (DIP).

Main Methods:

• Utilized primary data from Qilu Hospital (2019-2021) and secondary data from published literature (2004-2016).
• Included studies comparing pre- and post-implementation of SDP/DRG.
• Analyzed hospitalization costs, length of stay, and patient age as key factors.

Main Results:

• 92.9% of analyzed studies reported significant reductions in hospitalization costs after SDP implementation.
• Length of stay and patient age were identified as major factors influencing SDP effectiveness.
• 60% of reviewed studies indicated DRG efficiency across different regions, though broader validation is needed.
• SDP demonstrated cost-saving potential but faces implementation limitations; DRGs offer wider applicability but require further validation; DIP is a novel system needing more data.

Conclusions:

• Single Disease Payment (SDP) effectively reduces hospitalization costs but has limited implementation scope.
• Diagnosis-Related Groups (DRGs) show potential for broader application in healthcare cost control, but their effectiveness requires further validation.
• The Big Data Diagnosis-Intervention Packet (DIP) is an emerging system in China, necessitating additional data for a comprehensive efficiency assessment.