Enhancing elderly care services in high-density aging communities: a dual-dimensional GIS-SPO framework for spatial and temporal optimization

Abstract

Amid rapid population ageing, integrating health and social care in high-density urban neighbourhoods remains a critical challenge. We propose a dual-dimensional “spatio-temporal efficiency–service perception” framework combining GIS with the Structure-Process-Outcome (SPO) model, and tested it in Sanqiao Sub-district, Wuhan, China. Barrier-free renovations increased 15-minute elderly care coverage from 71.5% to 86.2%. Regression analysis identified facility adequacy (β = 0.22) and staff empathy (β = 0.14) as key satisfaction drivers. However, non-spatial barriers persisted: counselling utilisation was only 47.2%, and care costs ≥ 22% of household income reduced uptake by 63%. The “renovation + micro-station” strategy achieved 95.8% policy compliance, 100% EHR interoperability, and cut service response time to < 10 min. The model offers a culturally adaptive, transferable blueprint for resource-constrained ageing cities, emphasising that spatial fixes must be coupled with financial and stigma-reduction interventions to achieve equitable care access.

Introduction

Global population ageing is accelerating at an unprecedented pace. By 2050, adults aged ≥ 60 will number 2.1 billion, with 68% concentrated in high-density Asian cities [1]. These settings confront two converging challenges: (i) fragmented distribution of medical and elder-care facilities that create “last-mile” gaps, and (ii) vertical mobility barriers that prevent 15% of older residents from accessing basic services within a 15-minute walk [2]. Both issues directly contravene Sustainable Development Goal 3 (SDG 3) and amplify chronic-disease failure rates by 7.2% for every 10% decline in accessibility [3].

High-profile models—Tokyo’s nursing-care complexes, the US PACE program, and the Netherlands’ Buurtzorg—have improved care quality but are cost-intensive (≥ US$8,500 per capita) and difficult to scale in land-scarce megacities [4, 5]. Theoretically, Western New Public Management (NPM) emphasises market competition, often fragmenting services, while Collaborative Governance Theory (CGT) promotes multi-stakeholder partnerships but remains under-tested in ultra-ageing contexts [6, 7].

A second schism exists between spatial-accessibility studies (distance decay) and socio-cultural inquiries into service perception. Emerging evidence shows that stigma, financial strain, and built-environment quality strongly mediate the spatial availability–utilization pathway [8]. Yet, no operational framework simultaneously integrates high-precision GIS analytics with a theory-driven assessment of satisfaction determinants, leaving a critical gap between “hardware” (infrastructure) and “software” (socio-cultural-economic dynamics) [9, 10].

We address this gap by embedding the Structure-Process-Outcome (SPO) quality paradigm within dynamic GIS. Implemented in Sanqiao Sub-district (Wuhan, China; 520 elders km⁻²), our convergent parallel mixed-methods design achieves two breakthroughs: (i) barrier-free renovations expand 15-minute service coverage by 14.7% points (71.5% → 86.2%), directly advancing SDG 3.8; (ii) multivariate regression identifies facility adequacy (β = 0.22, p = 0.002) and staff empathy (β = 0.14, p = 0.015) as core satisfaction drivers, validating SDG 3.c. The resulting “Sanqiao Integrated Care Model” attains 95.8% policy compliance, 100% EHR interoperability, and 34% higher cross-sector efficiency than NPM-driven systems, offering a transferable blueprint for resource-constrained, rapidly ageing cities.

Methodology

Overall research design and GIS-SPO integration

We employed a convergent parallel mixed-methods design (QUAN + QUAL) centred on the Sanqiao Community-embedded Elderly Care Station in Hongshan District, Wuhan, China. The station operates within a vertically integrated medical consortium (1 tertiary, 2 secondary, 3 community hospitals, 10 satellite clinics). Quantitative (GIS, SPO survey) and qualitative (semi-structured interviews) data were collected concurrently, analysed separately, and integrated during interpretation (Fig. 1). The dual-dimensional GIS-SPO framework operationalises spatial indicators within Structure-Process-Outcome dimensions (Table 1).

Fig. 1.

Research Flowchart of the Integrated GIS-SPO Framework

Table 1.

Mapping of GIS indicators to SPO dimensions

SPO Dimension	SPO Construct (Measured by Survey/Interview)	Corresponding GIS Metric (Quantified Spatially)
Structure	Facility Adequacy	Kernel Density of Elderly Care Facilities
Structure	Resource Allocation	Service Blind Spot Identification
Process	Service Accessibility	Dynamic Network Analysis (Peak-hour impedance)
Process	Service Integration	Inter-floor Travel Time Difference
Outcome	Spatial Coverage Equity	15-Minute Walking Buffer Coverage
Outcome	--	-- (Satisfaction is primarily survey-based)

Data collection and processing

Spatial data

1. Data sources: facility coordinates extracted from Baidu Maps (WGS84); elderly population grids (100 m × 100 m) derived from the 7th National Census.

2. Network correction: OpenStreetMap pedestrian layers manually updated for age-friendly barriers (dead-end alleys, staircases); ArcGIS 10.8 Topology Checker ensured connectivity.

3. Accessibility modelling: time-geographic prisms simulated 15-minute walking coverage during peak hours (07:00–09:00; 15:00–17:00) at 4.0 ± 0.5 km h⁻¹, calibrated against the China Elderly Mobility White Paper.

Service and behavioral data

1. POI integration: service logs and coordinates collected for the ground-floor Health Management Centre (chronic-disease screening, EHR) and the first-floor Recreation-Rehabilitation Zone (psychological counselling, physiotherapy).

2. Wearable tracking: movement trajectories of 123 community-dwelling older adults were recorded for seven consecutive days using age-stratified random sampling (60–69 y: 38.2%; 70–79 y: 45.5%; ≥80 y: 16.3%). Sample size was powered by G*Power 3.1 (f² = 0.15, α = 0.05, power = 0.80). Exclusions (cognitive impairment or major surgery within three months) were applied for ethical and methodological reasons; this may systematically under-represent the most mobility-challenged subgroup (see § 2.2.3).

3. Qualitative supplement: thirty semi-structured interviews explored under-utilisation of counselling rooms (47.2%) and limited caregiving-burden relief (β = 0.031), with particular attention to cultural stigma and economic strain (≥ 22% household income).

Vertical coverage efficiency model

1. Inter-floor accessibility: a bespoke ArcGIS Pro 3.0 toolbox quantified between-floor service distances; stair/elevator impedance was set at α = 1.2 min per floor, empirically calibrated from 30 older adults (ICC = 0.91, Appendix S3).

2. Dynamic blind-spot identification: individual space-time prisms were used to compare 15-minute coverage gaps before and after renovation (Fig. 2).

Fig. 2.

15-Minute Walking Buffer Zone Coverage

Service satisfaction evaluation

1. SPO questionnaire: 20-item scale across five dimensions, developed via Delphi (15 experts) and AHP; Cronbach’s α = 0.872, KMO = 0.812, Bartlett χ² = 1,203.6, p < 0.001.

2. Qualitative analysis: NVivo 12 thematic coding (κ = 0.81) explored root causes of low counselling-room uptake and minimal caregiving-burden relief, focusing on mental-health taboos and catastrophic expenditure.

Statistical analysis

1. Multiple Linear Regression: Overall satisfaction was regressed on facility completeness (x₁), staff attitude (x₂), etc., with VIF < 5 ensuring no multicollinearity (SPSS 26.0).

2. Inference: bootstrap 1,000 repetitions for non-normal metrics; Wilson score CIs for proportions; α = 0.05 (two-tailed).

Ethics and compliance

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Geriatric Hospital of Wuhan University of Science and Technology. Written informed consent was obtained from all participants prior to data collection, including interviews and the use of anonymized wearable device data. All wearable data were anonymized in accordance with China’s Personal Information Protection Law and the European Union’s General Data Protection Regulation (GDPR).

Key findings

Spatial accessibility optimization

Dynamic GIS network analysis (Fig. 3) revealed that barrier-free renovations expanded 15-minute elderly care coverage in Sanqiao Community from 71.5% (2023) to 86.2% (2024) (+ 14.7 pp), reducing service blind spots to 13.8%,as shown in Fig. 3. Time-geographic modeling further identified 2.4 m-wide alleys and staircases as primary barriers, increasing peak-hour (7:00–9:00) walking impedance by 41%. Vertical integration reduced inter-floor service acquisition time disparity from 3.2 to 1.1 min (p < 0.01).

Fig. 3.

The 15-Minute Blind Spot Coverage Change Map Before and After Barrier-Free Renovation

Determinants of elderly satisfaction

SPO-based regression (Fig. 4) identified facility completeness (β = 0.218, 95%CI 0.104–0.332) and staff attitude (β = 0.140, 95%CI 0.052–0.228) as core satisfaction drivers, explaining 42% variance (R²=0.420, p < 0.001). However, counseling room utilization remained suboptimal (47.2%), with minimal caregiving burden alleviation (β = 0.031, p = 0.214). Qualitative interviews (n = 30) uncovered systemic barriers:

Fig. 4.

Satisfaction Drivers Forest Plot

1. Cultural stigma: 78% associated “psychological consultation” with mental illness (χ²=15.6, p < 0.001);

2. Economic strain: Care costs ≥ 22% of monthly income reduced service uptake by 63% (OR = 0.37, 95%CI 0.18–0.75).

Policy implementation outcomes

The “renovation + micro-station” strategy achieved 95.8% policy compliance (115 new beds added in 2024). The tightly-knit medical consortium enabled:

1. Service response time reduction to < 10 min (58% improvement vs. 2023);

2. 100% electronic health record interoperability (Table 2);

3. Family physician sign-up rate increased from 68.4% to 89.1% (Δ + 20.7%).

Table 2.

Key performance indicators of Community-Embedded integrated elderly care services (2023–2024)

Key Indicators	2023 Baseline	2024 Outcomes	Change/Improvement Rate	p value
Electronic Health Record (EHR) Sharing Rate	85%	100%	15%	<0.001
Rehabilitation Equipment Utilization Rate	71.60%	93.40%	21.80%	<0.001
Family Physician Sign-up Rate	68.40%	89.10%	20.70%	<0.001
Service Response Time (Median)	24 min	10 min	−58%	<0.001
Counseling Room Utilization Rate	42.50%	47.20%	4.70%	0.002
New Medical-Elderly Care Beds Added	—	11,500 beds	95.80%	—
Chronic Disease Management Rate	63.80%	82.30%	18.50%	<0.001

Median (IQR); bootstrap 1 000 repetitions for non-normal distribution

Qualitative validation of interventions

Targeted measures in pilot communities demonstrated efficacy:

1. Mental health campaigns: Bi-monthly anti-stigma lectures raised counseling room utilization to 61.3% (Δ + 14.1%) within 6 months.

2. Caregiver subsidies: 300 RMB/month for households earning < 5,000 RMB/month increased service utilization by 29.5% (p = 0.008).

Discussion

Theoretical contributions

Rather than claiming a paradigmatic revolution, this study contributes to the evolving paradigm of elder-care research by explicitly linking geospatial efficiency metrics to multidimensional satisfaction dynamics. Our dual “spatio-temporal efficiency–service perception” framework empirically challenges spatial determinism: cultural and economic factors, not merely physical distance, shape service equity. By integrating GIS with SPO quality theory, we quantify stigma-driven avoidance and demonstrate that care costs ≥ 22% of household income reduce utilisation by 63%—a threshold aligned with Nature Aging calls for non-geographic exclusion mechanisms [11]. Thus, the model offers a transformative, operationally testable response to the long-standing “hardware versus software” divide in health-service research.

Collaborative governance in medical consortia: achievements and mediated challenges

The vertically integrated medical consortium provides field-based validation of Collaborative Governance Theory (CGT) in an ultra-ageing urban context. Specialist rotations from tertiary to community hospitals cut redundant equipment costs by 23% and reduced emergency response time by 58%, outcomes that exceed pure technical efficiency. Crucially, these rotations increased chronic-disease adherence by 18.5%, underscoring the relational-contract value of repeated face-to-face interactions stressed by CGT.

However, the pathway was not friction-free. Early negotiations revealed conflicts over specialist “brain drain” and blurred lines of clinical responsibility. These were mediated through a joint governance committee—comprising representatives from every tier—with authority to set cross-institutional protocols and allocate a performance-based incentive fund [12]. While resource-intensive initially, this deliberative mechanism forged the trust required for durable collaboration, illustrating that CGT success hinges on continuous stakeholder negotiation rather than on structural blueprints alone.

Policy implementation beyond Spatial metrics

While the 14.7%-point expansion in 15-minute coverage validates spatial investment, our findings expose the limits of infrastructure-centric policy. A fully accessible counselling room achieved only 47.2% utilisation, driven by stigma (78% avoidance) and catastrophic expenditure (≥ 22% household income). We therefore propose a three-phase, culturally adaptive roadmap that moves budgets from “bricks” to “behaviour”:

1. Pilot Optimisation: reallocate 30% of ageing-in-place funds to stigma-reduction campaigns in digitally mature districts; our pilot achieved a 29.5% uptake increase with an ROI of 1:2.3 within six months.

2. Regional Scaling: introduce 15% salary premiums for high-stigma areas alongside means-tested subsidies once care-to-income ratios exceed 20%.

3. Systemic Integration: embed collaborative-governance clauses in urban health statutes, mandating cross-tier performance agreements and shared savings pools.

By sequencing spatial, financial and cultural levers, the roadmap operationalises The Lancet Healthy Longevity call for culturally adaptive health investments while minimising fiscal risk for municipal governments.

Limitations and cultural boundaries

Generalisability is bounded by three context-specific factors. First, EHR interoperability reached 100% in Hubei but falls to 35% in lower-middle-income settings such as Indonesia, highlighting digital-infrastructure disparities. Second, family-mediated stigma reduction backfired in individualistic cultures where 62% of US seniors opposed relative-involved counselling, underscoring the risk of “techno-cultural mismatch”. Third, wearable tracking missed 43% of trips among the oldest-old (≥ 85 years), limiting mobility insights for the most frail subgroup. These constraints echo Nature Aging warnings that successful ageing innovations must be locally adapted rather than directly transplanted.

Culturally adaptive futures

Scaling the Sanqiao Integrated Care Model requires context-sensitive adaptations. In Confucian settings, family-mediation workshops that train relatives as care coordinators increased uptake by 22% in our unpublished pilot. Individualistic cultures benefit from anonymous AI chatbots (e.g., “Mental Health Navigator”) which achieved 68% engagement in early trials, bypassing stigma through privacy. Resource-limited regions can deploy SMS-based symptom checkers that improved depression screening from 31% to 57% in rural India, offering low-cost, high-reach solutions.

A global ageing-care innovation index—combining spatial accessibility, stigma levels and digital readiness—should be developed to guide local prioritisation and prevent “one-size-fits-all” transfers. By embedding these culturally calibrated tools within the three-phase roadmap (§ 4.3), policymakers can accelerate equitable ageing-in-place while avoiding the pitfalls of technological or cultural imperialism.

Conclusion

This study moves beyond spatial determinism by validating a GIS-SPO dual-dimensional framework that simultaneously optimises infrastructure and addresses cultural-economic exclusion. While the 14.7%-point expansion in 15-minute coverage demonstrates the power of spatial planning, the under-utilisation of fully accessible counselling rooms (47.2%) powerfully illustrates that stigma and financial strain can nullify even the best “hardware” investments.

Our three-phase implementation roadmap—pilot optimisation, regional scaling, and systemic integration—provides policy-makers with a transferable blueprint that re-allocates budgets from bricks to behaviour, from stigma to subsidies, and from isolated facilities to collaborative governance. By embedding culturally calibrated tools within this sequence, the Sanqiao Integrated Care Model offers a replicable pathway towards universal health equity for rapidly ageing, resource-constrained cities worldwide.

Future research should focus on: (i) developing non-intrusive mobility tracking for the oldest-old and cognitively impaired; (ii) institutional levers for high-level EHR interoperability across heterogeneous health systems; and (iii) cross-national trials to refine the global ageing-care innovation index proposed herein.

Author contributions

Yan Wu: writing-original draft. Wei Tan: conceptualization and proof reading. Wenlong Yi: polishing the text of the manuscript. Yujuan Chen: writing-review & editing. All authors agreed on the final version.

Funding

Not applicable.

Data availability

The datasets generated and analyzed during this study are available from the corresponding author upon reasonable request. De-identified data will be shared under a Data Transfer Agreement to ensure compliance with ethical standards.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Geriatric Hospital of Wuhan University of Science and Technology, and written informed consent was secured from all participants. All wearable data were anonymized in accordance with China’s Personal Information Protection Law and the European Union’s General Data Protection Regulation (GDPR).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.