Designing Governance Boundaries for Hospital Bed Management: Balancing Centralized Pooling and Local Protection.

Area of Science:

• Healthcare Management
• Operations Research
• Health Systems Engineering

Background:

• Hospital-wide bed pooling is a common strategy in bed management reform to optimize scarce inpatient capacity.
• However, the effectiveness of pooled beds depends on coordination, judgment, and timely execution during cross-ward reassignments, especially under pressure.
• This study frames hospital bed governance as a balance between local ward protection and centralized pooling.

Purpose of the Study:

• To develop and analyze an alpha-based governance framework for hospital bed pooling.
• To examine the trade-offs between centralized pooling and local capacity protection under varying conditions.
• To identify optimal boundaries for hospital bed governance considering coordination friction and operational usability.

Main Methods:

• Development of an alpha-based governance framework modeling decentralization, bounded centralization, and full centralization.
• Introduction of parameters for coordination friction, pooled-allocation imperfection, and local capacity value.
• Scenario-based computational experiments to simulate performance across different operating conditions and multi-ward scenarios.

Main Results:

• In a frictionless model, full centralization offers the broadest allocation set and weakly dominates.
• When pooled allocation is effective, full centralization is not significantly outperformed.
• Coordination friction alone does not necessitate abandoning full centralization, but reduced reassignment reliability under pressure favors interior governance boundaries that preserve local capacity.

Conclusions:

• Centralized pooling remains a viable strategy for hospital bed management.
• Effective bed reform requires evaluating not only the extent of pooling but also the practical usability of pooled beds during high-demand periods.
• Balancing centralized pooling with sufficient local capacity protection may be crucial for optimizing hospital operations under stress.