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StratBAM: A Discrete-Event Simulation Model to Support Strategic Hospital Bed Capacity Decisions
Priyantha Devapriya1, Christopher T B Strömblad, Matthew D Bailey
1Geisinger Health System, Danville, PA, USA.
Journal of Medical Systems
|August 28, 2015
Summary
A new simulation model, StratBAM, accurately assesses healthcare capacity and patient flow. It aids in planning bed capacity, budgeting, and evaluating process improvements for better patient safety outcomes.
Area of Science:
- Industrial and Systems Engineering
- Health Services Research
Background:
- Accurate assessment of healthcare system capacity is crucial for quality and patient safety.
- There is a need to apply industrial and systems engineering principles to healthcare.
Purpose of the Study:
- To develop a decision support tool for planning and budgeting healthcare bed capacity.
- To evaluate potential process improvement efforts using simulation.
Main Methods:
- Developed the Strategic Bed Analysis Model (StratBAM), a discrete-event simulation model.
- Utilized patient flow data and electronic health records from Geisinger Health System (GHS).
- Incorporated inputs such as patient arrival/discharge data, length of care, patient paths, and projected volumes.
Main Results:
- StratBAM accurately models real-world healthcare data, validated against GHS operational data.
- Key outputs include admission wait times and occupancy rates.
- Successfully evaluated the system impact of forecasted patient volumes and length of stay on wait times, occupancy, and cost.
Conclusions:
- StratBAM is a generalizable and scalable tool for healthcare capacity planning and process improvement.
- The model supports informed decision-making for optimizing healthcare resource allocation.
- Enhances healthcare quality and patient safety through better capacity management.
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