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Health service capacity modelling
Peter Trye1, Nigel Murray, Ian Wolstencroft
1Royal Melbourne Hospital.
Summary
This study presents a quantitative model for estimating future hospital bed demand, using historical inpatient data and ten factors. The tool aids healthcare managers and stakeholders in clear, explicit decision-making for resource allocation.
Area of Science:
- Health Services Research
- Operations Research
- Healthcare Management
Background:
- Accurate forecasting of hospital bed demand is crucial for effective healthcare resource allocation.
- Existing methods may lack the detail to incorporate various influencing factors.
- Stakeholder involvement in planning requires transparent and data-driven approaches.
Purpose of the Study:
- To describe a quantitative modelling tool for estimating future hospital bed demand.
- To outline challenges and considerations in applying this predictive model.
- To provide a framework for involving diverse stakeholders in healthcare capacity planning.
Main Methods:
- Development of a quantitative mathematical model based on two years of inpatient data.
- Inclusion of seasonally adjusted data to account for temporal variations.
- Application of ten distinct factors to project bed-days and required beds five years into the future.
Main Results:
- The model successfully translated historical bed-day usage into future bed requirements.
- An example demonstrated that 7,924 bed-days in 1998-99 projected a need for 26 beds in 2004.
- The model's structure allows for the explicit consideration of multiple influencing factors.
Conclusions:
- The developed modelling tool offers a robust framework for hospital bed demand estimation.
- Its strength lies in delineating factors, facilitating informed decision-making by clinicians, managers, and purchasers.
- This approach enhances transparency and collaboration among healthcare stakeholders for strategic planning.
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