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Multifactorial Correlation Analysis of Nursing Unit Staffing Based on Gray Relation Analysis: A Cross-Sectional Study
Xinyue Pang1, Xinmei Cao1, Zhi Chen2
1The First School of Medicine, School of Information and Engineering, Wenzhou Medical Medical University, Wenzhou, 325035, Zhejiang, China.
Journal of Nursing Management
|March 5, 2026
Summary
This study used gray relation analysis to identify key factors influencing nurse staffing. Physical/financial inputs and nursing quality/safety outputs are crucial for effective nurse staffing models.
Area of Science:
- Nursing Management
- Healthcare Operations Research
- Health Services Research
Background:
- Nurse staffing rationalization is complex, with unclear correlations between influencing factors and staffing levels.
- Previous research has not fully clarified the multifaceted influences on nursing human resource allocation.
Purpose of the Study:
- To analyze associations between human, material, financial inputs, nursing services, and quality with nursing human resource allocation.
- To clarify nursing unit staffing priorities using gray relation analysis from time series and nursing unit perspectives.
Main Methods:
- Identified 7 primary and 26 secondary indicators influencing nursing unit staffing.
- Retrospectively collected data from 55 nursing units for 2023.
- Applied gray relation analysis to rank correlations between influencing factors and staffing.
Main Results:
- Gray relation analysis showed high correlation coefficients for primary indicators (0.72-1.00) and secondary indicators (0.59-1.00).
- Physical/financial inputs and nursing quality/safety outputs ranked highest among primary categories.
- Key secondary indicators included open beds, nurses on duty, nurse-patient ratio, work hours, quality assessment, bed utilization, patient satisfaction, and DRGs.
Conclusions:
- Gray relation analysis effectively identifies key inputs and outputs for nursing unit staffing.
- Management should prioritize physical/financial inputs and nursing quality/safety outputs.
- The analytical perspective (time-series vs. unit comparison) is crucial as factor relationships vary significantly.
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