Modeling time-varying spatial accessibility to healthcare: A system dynamic approach

Area of Science:

• Health Services Research
• Geographic Information Systems
• Public Health Policy

Background:

• Spatial healthcare accessibility is crucial for identifying and addressing health disparities.
• Existing models inadequately capture temporal dynamics and interactions of factors influencing accessibility.
• Data limitations and methodological challenges hinder the validation of current accessibility models.

Purpose of the Study:

• To develop a novel modeling approach for time-varying and empirically validated healthcare accessibility measures.
• To represent the dynamic interplay between population demand and healthcare supply over time.
• To provide a framework for monitoring healthcare accessibility fluctuations and informing targeted interventions.

Main Methods:

• Developed a system dynamic model to simulate population demand and healthcare supply interactions.
• Simultaneously estimated potential healthcare accessibility and utilization across time and space.
• Validated model estimates using actual hospitalization data from Florida during a 2022-23 disease outbreak.

Main Results:

• System dynamic modeling provides a robust framework for assessing dynamic healthcare accessibility.
• The model successfully estimated and validated time-varying accessibility at a granular level (day and ZIP code).
• Demonstrated the practical application of the model in a real-world scenario during a disease outbreak.

Conclusions:

• System dynamic modeling offers a powerful tool for understanding and monitoring healthcare accessibility.
• The approach facilitates the development of timely and targeted public health interventions to reduce disparities.
• Empirically validated, dynamic accessibility measures are essential for effective health policy and planning.