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Analytical Techniques for Supporting Hospital Case Mix Planning Encompassing Forced Adjustments, Comparisons, and
Robert L Burdett1, Paul Corry1, David Cook2
1School of Mathematical Sciences, Queensland University of Technology, 2 George Street, P.O. Box 2434, Brisbane, QLD 4000, Australia.
This study introduces novel analytical techniques and a decision support tool for hospital capacity assessment and case mix planning (CMP). These methods enhance situational awareness and bridge the gap between theory and practice in healthcare resource management.
Area of Science:
- Healthcare Management
- Operations Research
- Health Services Research
Background:
- Existing methods for hospital capacity assessment and case mix planning (CMP) lack comprehensive analytical techniques.
- There is a need for quantitative tools to support strategic decision-making in hospital resource allocation.
Purpose of the Study:
- To present novel analytical techniques for hospital capacity assessment.
- To introduce a decision support tool for effective case mix planning (CMP).
- To enhance situational awareness regarding hospital resource availability and its impact on patient mix.
Main Methods:
- Development of an optimization model to assess the impact of case mix adjustments on hospital resources.
- Application of multi-objective decision-making techniques to evaluate and compare different case mix scenarios.
- Integration of analytical techniques into a user-friendly Excel Visual Basic for Applications (VBA) personal decision support tool (PDST).
Main Results:
- The PDST provides quantitative assessments of hospital capacity and the effects of case mix modifications.
- The tool reports metrics detailing differences and the impact on various patient types.
- Demonstrated seamless integration of complex analytical models into a practical software application.
Conclusions:
- The developed techniques offer a practical bridge between theoretical optimization models and real-world hospital management.
- The decision support tool enhances understanding of hospital capacity dynamics and informs strategic planning.
- The findings contribute to improved situational awareness for hospital administrators and planners.
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