System design and data driven policy simulation for organ procurement networks using an OPO centre operations...

Area of Science:

• Health Services Research
• Operations Research
• Public Policy

Background:

• Healthcare organ procurement and transplantation networks operate as complex systems.
• Existing governance and incentives contribute to persistent regional inequities in organ allocation.
• Understanding organizational behavior is crucial for improving system performance.

Purpose of the Study:

• To develop a data-driven, simulation-based framework for evaluating and redesigning incentive mechanisms.
• To model transplant center responses under different governance regimes.
• To assess the impact of equity-weighted incentives on system performance.

Main Methods:

• Utilized SRTR-style center-level activity data.
• Constructed a Java-based policy-simulation environment.
• Formulated center utility based on transplant volumes, regional characteristics, and operating costs.
• Assessed system performance using aggregate welfare and distributional equity metrics.

Main Results:

• Simulation experiments revealed quantifiable equity-efficiency trade-offs.
• Identified parameter regions where incentive redesign improves regional equity with minimal performance loss.
• Demonstrated the impact of equity-weighted incentives on transplant center behavior.

Conclusions:

• The developed framework offers a transparent tool for regulators to test policy reforms.
• Integrating system design, behavioral modeling, and incentive analysis can optimize organ procurement networks.
• Policy interventions can mitigate regional inequities in organ transplantation.