Abstract
Introduction
Demographic change and unpredictable demand shocks — such as epidemics or mass migration — substantially affect the utilisation of healthcare services. The aim of this project was to develop a scenario-based modelling tool for long-term demand forecasting, integrating demographic projections with simulations of exogenous shocks.
Methods
The model quantifies demand using the average number of National Health Fund (NHF) reimbursement points per age/sex group. Population structure changes are projected over a 10-year horizon (2024–2034) across six scenarios, based on Eurostat forecasts. A dedicated demand shocks module enables the incorporation of exogenous events — such as migration waves or excess mortality — through targeted modifications of the population structure.
Results
The tool’s key strength lies in its crisis modelling capabilities. Migration waves are simulated by introducing cohorts with defined age-sex profiles, triggering automatic recalculation of demand across service types consistent with the Polish healthcare system structure. Epidemic scenarios allow for the application of excess mortality patterns, with calibration against historical data (e.g., COVID-19), and generate system load forecasts linked to interactive demand visualisations. Demographic dynamics are captured through scenarios covering population ageing, migration, and fertility trends. Demand can be disaggregated by medical specialty, including cardiology, oncology, and geriatrics. Outputs include structured reports, visualisations, and exports to standard analytical formats.
Conclusions
The tool supports strategic planning of healthcare resources by enabling rapid, evidence-informed assessment of demographic and crisis scenarios.
Key messages
• A modelling tool that helps planners forecast healthcare demand under demographic change and crisis scenarios — supporting smarter, more resilient resource allocation.
• By integrating demographic forecasts with exogenous shock simulations, the tool enables rapid, evidence-based assessment of future healthcare system pressures.