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Beyond Spatial Proximity: Optimizing Nursing Home Bed Allocation with a Proposed '4A' Model-Insights from Guangzhou,
He Jin1, Na Li1, Mengya Jia2
1School of Intelligent Transportation and Intelligent Construction Engineering, Huanghe Jiaotong University, Jiaozuo 454950, China.
Healthcare (Basel, Switzerland)
|July 28, 2026
Summary
Guangzhou
Area of Science:
- Gerontology and Public Health
- Health Services Research
- Urban Planning and Policy
Background:
- Guangzhou faces a severe elderly care gap due to rapid population aging.
- Existing nursing home allocation models are insufficient to meet demand.
- Optimizing resource distribution is crucial for elder care accessibility.
Purpose of the Study:
- To introduce and apply a novel '4A' model (accessibility, affordability, acceptability, availability) for nursing home bed allocation.
- To optimize the distribution of existing elderly care facilities in Guangzhou.
- To address the supply-demand imbalance in nursing home beds.
Main Methods:
- Applied the '4A' model to 2630 communities and 243 nursing homes in Guangzhou.
- Utilized linear programming to maximize bed allocation under various constraints.
- Assessed inequity using Gini coefficient, Theil index, and spatial analysis (Moran's I, hot spot analysis).
- Simulated four policy scenarios under different resource conditions.
Main Results:
- 28.6% of communities lacked nursing home access, with unmet demand clustering in urban and suburban areas.
- The '4A' model allocated 3813 more beds than a distance-based model.
- Policy simulations demonstrated that minimum service standards eliminated unserved areas, and targeted bed expansion significantly improved satisfaction and equity.
- Subsidies and quality upgrades were effective primarily with abundant bed supply.
Conclusions:
- The '4A' model provides a computable framework for optimizing nursing home bed allocation.
- It transforms qualitative access criteria into actionable recommendations for equitable elderly care.
- The study offers a phased policy roadmap for improving elderly care resource distribution in aging populations.
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