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A computational application for multi-skill nurse staffing in hospital units
Ana Respicio1,2, Margarida Moz3, Margarida Vaz Pato3
1CMAF-CIO, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal. alrespicio@fc.ul.pt.
BMC Medical Informatics and Decision Making
|June 30, 2018
Summary
This study introduces a new method for optimizing hospital nurse staffing by considering patient severity, skill mix, and shift work. The developed tool helps managers improve staff distribution and reduce costs.
Area of Science:
- Healthcare Management
- Operations Research
- Nursing Administration
Background:
- Current nurse staffing models primarily focus on patient illness severity, neglecting multi-skill and multi-shift considerations.
- A gap exists in strategic decision-making for nurse staffing that incorporates work organization across shifts and demand variability.
Purpose of the Study:
- To develop a novel mathematical model and tool for determining optimal nurse staffing levels per skill category and shift.
- To minimize salary costs while ensuring compliance with legislation and guidelines.
- To support strategic decision-making in hospital workforce dimensioning.
Main Methods:
- Development of a mathematical model for nurse staffing optimization.
- Creation of a spreadsheet-based tool for scenario simulation and demand fluctuation analysis.
- Application of the model using real data from a Brazilian hospital unit.
Main Results:
- The model validated the overall current staff level in the studied unit.
- Analysis revealed opportunities for improving staff distribution across different skill categories.
- The tool supports decision-making by simulating various demand scenarios.
Conclusions:
- The method enables determination of shift- and skill-specific staffing based on patient acuity.
- A user-friendly spreadsheet tool facilitates optimization and scenario evaluation for hospital managers.
- The model is adaptable to other hospitals, incorporating local regulations and legislation.
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