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A Game Model for Medical Service Pricing Based on the Diagnosis Related Groups
Jinli Duan1, Zhibin Lin2, Feng Jiao3
1College of Modern Management, Yango University, Fuzhou, China.
Insights
This study uses a game pricing model to prevent adverse selection in China's Diagnosis-Related Groups (DRGs) system. It ensures fair compensation for medical institutions and improves overall social welfare by considering patient preferences and demand elasticity.
Area of Science:
- Health Economics
- Healthcare Management
- Game Theory
Background:
- China's Diagnosis-Related Groups (DRGs) pricing system faces challenges including patient selection and inadequate compensation for complex cases.
- These issues stem from the current price-setting mechanisms within the DRGs framework.
Purpose of the Study:
- To develop a scientific and reasonable pricing strategy for DRGs using a game pricing model.
- The objective is to prevent adverse selection problems in the operation of the DRGs system.
Main Methods:
- A three-stage bargaining game model was proposed, involving an alliance of government and patients.
- The model incorporates Stackelberg and Rubinstein bargaining games to determine optimal pricing and service quality.
- Equilibrium solutions were derived considering the alliance as price maker/taker and medical institutions as price taker/leader.
Main Results:
- Increased price elasticity of demand leads to higher cost compensation ratios and equilibrium prices for medical institutions.
- Equilibrium pricing is influenced by patient quality preference coefficients and risk aversion.
- Patient risk aversion impacts government compensation and overall social welfare.
Conclusions:
- DRGs pricing that considers demand elasticity and patient quality preferences can mitigate adverse selection.
- Future research will extend the model to include inter-institutional competition within DRGs.
- Differential compensation for different hospital types is suggested to promote hierarchical diagnosis and treatment.
Abstract:
Background: Currently there are various issues that exist in the medical institutions in China as a result of the price-setting in DRGs, which include the fact that medical institutions tend to choose patients and that the payment standard for complex cases cannot reasonably compensate the cost. Objective: The main objective is to prevent adverse selection problems in the operations of a diagnosis-related groups (DRGs) system with the game pricing model for scientific and reasonable pricing. Methods: The study proposes an improved bargaining game model over three stages, with the government and patients forming an alliance. The first stage assumes the alliance is the price maker in the Stackelberg game to maximize social welfare. Medical institutions are a price taker and decide the level of quality of medical service to maximize their revenue. A Stackelberg equilibrium solution is obtained. The second stage assumes medical institutions dominate the Stackelberg game and set an optimal service quality for maximizing their revenues. The alliance as the price taker decides the price to maximize the social welfare. Another Stackelberg equilibrium solution is achieved. The final stage establishes a Rubinstein bargaining game model to combine the Stackelberg equilibrium solutions in the first and second stage. A new equilibrium between the alliance and medical institutions is established. Results: The results show that if the price elasticity of demand increases, the ratio of cost compensation on medical institutions will increase, and the equilibrium price will increase. The equilibrium price is associated with the coefficient of patients' quality preference. The absolute risk aversion coefficient of patients affects government compensation and total social welfare. Conclusion: In a DRGs system, considering the demand elasticity and the quality preference of patients, medical service pricing can prevent an adverse selection problem. In the future, we plan to generalize these models to DRGs pricing systems with the effects of competition of medical institutions. In addition, we suggest considering the differential compensation for general hospitals and community hospitals in a DRGs system, in order to promote the goal of hierarchical diagnosis and treatment.
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