Dynamic hospital competition under rationing by waiting times

Area of Science:

• Health economics
• Operations research
• Game theory

Background:

• Healthcare systems face challenges with patient waiting times and hospital competition.
• Understanding the impact of policy interventions on hospital behavior and patient outcomes is crucial.

Purpose of the Study:

• To develop and analyze a dynamic model of hospital competition incorporating waiting times and patient choice.
• To evaluate the effectiveness of waiting time penalties versus patient choice policies on reducing hospital waiting times.

Main Methods:

• Developed a dynamic game-theoretic model of hospital competition.
• Incorporated factors: demand exceeding supply, patient hospital selection based on waiting times, and hospital penalties.
• Calibrated the model using data from the English National Health Service (NHS) for cataract surgery.

Main Results:

• Policies imposing penalties on hospitals for long waiting times effectively reduce these times.
• Policies promoting patient choice lead to an increase in hospital waiting times.
• The effectiveness of penalties is enhanced with linear structures; convex penalties reduce the negative impact of patient choice.

Conclusions:

• Waiting time penalties are a more effective strategy for reducing healthcare wait times than promoting patient choice.
• Policy design, specifically penalty structure (linear vs. convex), influences the outcomes of these interventions.
• Findings provide insights for optimizing healthcare resource allocation and patient access, exemplified by NHS cataract surgery data.