Estimating need and demand for prehospital care.

Area of Science:

• Health Services Research
• Operations Research
• Public Health

Background:

• Accurate estimation of emergency transportation services (ETS) demand and need is crucial for effective healthcare planning and resource allocation.
• Traditional reliance on historical data for planning can be limiting; alternative modeling approaches are needed.
• Understanding factors influencing ETS demand is essential for optimizing service delivery.

Purpose of the Study:

• To develop and validate models for estimating the demand for emergency transportation services.
• To create a subsequent model for estimating the unmet need for these services.
• To investigate the influence of emergency transportation service provider characteristics on demand.

Main Methods:

• Developed a demand model using population, employment, and socioeconomic status indicators from census data.
• Calibrated the demand model with 1979 data from 82 ambulance services in Southwestern Pennsylvania.
• Tested the model's predictive accuracy using data from an additional 55 civil divisions.

Main Results:

• The demand model provided reliable estimates of ETS demand across operational and clinical categories.
• The model demonstrated good predictive accuracy when tested on new data.
• Provider characteristics were found to be insignificant for demand forecasting when sociodemographic factors were controlled.

Conclusions:

• The developed models offer a robust method for estimating ETS demand and unmet need, complementing or replacing historical data.
• Sociodemographic factors are primary drivers of ETS demand, outweighing provider-specific characteristics in forecasting.
• These models support evidence-based planning for emergency transportation services.