Efficiency of fine scale and spatial regression in modelling associations between healthcare service spatial accessibility and their utilization

Revealing spatiotemporal inequalities, hotspots, and determinants in healthcare resource distribution: insights from hospital beds panel data in 2308 Chinese counties

BACKGROUND

Ensuring universal health coverage and equitable access to health services requires a comprehensive understanding of spatiotemporal heterogeneity in healthcare resources, especially in small areas. The absence of a structured spatiotemporal evaluation framework in existing studies inspired us to propose a conceptual framework encompassing three perspectives: spatiotemporal inequalities, hotspots, and determinants.

METHODS

To demonstrate our three-perspective conceptual framework, we employed three state-of-the-art methods and analyzed 10 years' worth of Chinese county-level hospital bed data. First, we depicted spatial inequalities of hospital beds within provinces and their temporal inequalities through the spatial Gini coefficient. Next, we identified different types of spatiotemporal hotspots and coldspots at the county level using the emerging hot spot analysis (Getis-Ord Gi* statistics). Finally, we explored the spatiotemporally heterogeneous impacts of socioeconomic and environmental factors on hospital beds using the Bayesian spatiotemporally varying coefficients (STVC) model and quantified factors' spatiotemporal explainable percentages with the spatiotemporal variance partitioning index (STVPI).

RESULTS

Spatial inequalities map revealed significant disparities in hospital beds, with gradual improvements observed in 21 provinces over time. Seven types of hot and cold spots among 24.78% counties highlighted the persistent presence of the regional Matthew effect in both high- and low-level hospital bed counties. Socioeconomic factors contributed 36.85% (95% credible intervals [CIs]: 31.84-42.50%) of county-level hospital beds, while environmental factors accounted for 59.12% (53.80-63.83%). Factors' space-scale variation explained 75.71% (68.94-81.55%), whereas time-scale variation contributed 20.25% (14.14-27.36%). Additionally, six factors (GDP, first industrial output, local general budget revenue, road, river, and slope) were identified as the spatiotemporal determinants, collectively explaining over 84% of the variations.

CONCLUSIONS

Three-perspective framework enables global policymakers and stakeholders to identify health services disparities at the micro-level, pinpoint regions needing targeted interventions, and create differentiated strategies aligned with their unique spatiotemporal determinants, significantly aiding in achieving sustainable healthcare development.

Non-human and human service efficiency of long-term care facilities in China

Introduction

Care services provided by long-term care facilities (LTCFs) are currently plagued by care resource shortages and insufficient utilization. The analysis on the temporal and spatial distribution of human resources and non-human resources in LTCFs, could provide a basis to optimize resource allocation and efficient use of limited resources.

Methods

This study used data envelopment analysis to comprehensively evaluate the efficiency of human and non-human resources in different time spans and regions. The spatial Markov chain and spatial correlation were also applied to explore the heterogeneity of and correlation between the service efficiency of LTCFs in different regions and then analyzes the influencing factors of efficiency using Tobit regression model.

Results

The quantitative changes in the service efficiency of LTCFs in various provinces showed a "W" shape in two periods, ranging from 0.8 to 1.6. The overall efficiency of LTCFs in different regions had a lower probability to achieve short-term cross-stage development. Non-human resource efficiency presented a "cluster" distribution mode, demonstrating a great probability to achieve cross-stage development, which might be due to the regional disparities of economic development and land resource. Tobit regression analysis results also showed that the comprehensive efficiency of LTCFs decreases by 0.210 for every square increase in construction space variation. However, human resource efficiency had a significant spatial polarization, making it difficult to develop area linkages. The reason for this might be the nursing staff have relatively stable regional characteristics, weakening the inter-provincial spatial connection. We also found that female workers, aged between 35 and 45 can positively affect the efficiency of LTCFs. Those staff stay focused and improve their skills, which might improve the efficiency of LTCFs. So improving technology and service quality changes by increasing female workers, aged between 35 and 45, and avoiding excessive construction space changes can enhance the growth of service quality and personnel stability of LTCFs.

Conclusion

There is an urgent trade-off among staff quality improvement, resource reduction, construction excessive and substantial regional variation in efficiency. Therefore, strengthening policy support to encourage inter-regional initiatives, particularly highlighting the development of human resources interaction and common development is urgent.

Cost-effectiveness of fuzuloparib compared to routine surveillance, niraparib and olaparib for maintenance treatment of patients with germline BRCA1/2 mutation and platinum-sensitive recurrent ovarian carcinoma in China

Background: Maintenance therapy with the poly (ADP-ribose) polymerase inhibitors (PARPis) for platinum-sensitive recurrent ovarian carcinoma (OC) have proven to be effective compared with placebo. We aimed to evaluate the cost-effectiveness (CE) of maintenance fuzuloparib compared to routine surveillance (RS), niraparib and olaparib for platinum-sensitive recurrent OC from the Chinese healthcare systems. Method: A partitioned survival model with three-state (progression-free, progressed, death) was constructed utilizing TreeAge Pro 2011 software to evaluate the economic value of fuzuloparib, niraparib and olaparib maintenance treatment for platinum-sensitive recurrent OC based on the clinical data derived from FZOCUS-2, ENGOT-OV16/NOVA and ENGOT-Ov21/SOLO2. Transition probabilities were estimated from the reported survival probabilities in those trials. Cost and health preference data were derived from the literature. The quality-adjusted life-years (QALYs) and lifetime costs were measured for this analysis. A 5 years horizon and 5%/year discount rates were used. One-way analysis, and probabilistic sensitivity analysis (PSA) were performed to explore the model uncertainties. Results: Total cost of fuzuloparib, niraparib and olaparib were $31628.10, $48183.48 and $54605.54, whereas they had an incremental cost-utility ratio of $31992.69, $32216.08 and $23359.26 per additional progression-free survival (PFS) QALYs gained compared with RS, relatively. Model showed that maintenance fuzuloparib achieved at least an 85.5% probability of CE at the threshold of $37654.50/QALY. One-way sensitivity analysis revealed that the results were sensitive to the PFS and the price of medicines. Conclusion: Fuzuloparib was less cost-effective for patients with germline BRCA1/2 mutation and platinum-sensitive recurrent OC compared to olaparib, but was superior to niraparib from the Chinese healthcare systems perspective.

Cost-effectiveness of nivolumab plus ipilimumab versus chemotherapy as first-line therapy in advanced non-small cell lung cancer

OBJECTIVES

First-line treatment with nivolumab plus ipilimumab has been shown to improve overall survival (OS) and progression-free survival (PFS) for patients with advanced non-small cell lung cancer (NSCLC). The current study evaluated the cost-effectiveness of nivolumab plus ipilimumab versus chemotherapy in advanced NSCLC from the perspective of Chinese healthcare system.

METHODS

A three state-transition Markov model was employed to evaluate the cost and effectiveness of nivolumab plus ipilimumab versus chemotherapy in the first-line treatment of advanced NSCLC. Key clinical data in the model were derived from Part 1 of the phase 3 CheckMate 227 trial (NCT02477826). Costs and utilities were obtained from published literatures. The main endpoints of the model were costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses were performed to assess the model uncertainty.

RESULTS

Nivolumab plus ipilimumab was associated with an increase in overall cost of $95,867.82 and improved effectiveness of 0.98 QALYs compared with chemotherapy, yielding an ICER of $97,676.24 per QALY. In one-way sensitivity analysis, the variables that had the greatest influence on the ICER were hazard ratio for OS and body weight. In probabilistic analysis, nivolumab plus ipilimumab had a 0% probability of being cost-effective at a willingness-to-pay (WTP) threshold of $37,663.26/QALY in China. However, the combination therapy would become cost-effective when the cost of nivolumab and ipilimumab were discounted by 65%.

CONCLUSION

First-line nivolumab plus ipilimumab treatment for advanced NSCLC was found to be not cost-effective compared with chemotherapy at a WTP threshold of $37,663.26/QALY in China.

Cost-effectiveness analysis of nivolumab plus ipilimumab versus chemotherapy as the first-line treatment for unresectable malignant pleural mesothelioma

Introduction:

This study evaluated the cost-effectiveness of nivolumab plus ipilimumab (NI) versus pemetrexed plus cisplatin/carboplatin (C) as the first-line treatment for unresectable malignant pleural mesothelioma (MPM) from the perspective of US payers.

Methods:

A 10-year partitioned survival model was constructed using survival and safety data from the CheckMate 743 clinical trial. The output metrics of the model included the patient’s lifetime quality-adjusted life years (QALYs), lifetime costs, and incremental cost-effectiveness ratio (ICER). Only direct medical costs were considered. One-way and probabilistic sensitivity analyses were conducted to assess the robustness of the results.

Results:

Among all randomized patients, group NI had an ICER of $475,677/QALY relative to group C. Among patients with epithelioid histology, group NI had an ICER of $760,955/QALY. Among patients with non-epithelioid histology, group NI had an ICER of $418,348/QALY. The ICERs of all three populations exceeded the willingness-to-pay threshold ($150,000). The results of one-way sensitivity analysis revealed that the cost of nivolumab had a great influence on the results. The results of probabilistic sensitivity analysis demonstrated that the possibility of NI being more economical in all randomized patients and in patients with non-epidemiology histology was 0. In patients with epithelioid histology, the probability that NI had an economic advantage was 0.6%.

Conclusions:

From the perspective of US payers, in patients with unresectable MPM, NI has no economic advantage over C.

Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities accessibility of schools, hospitals, green space, and public transit stations with four kinds of accessibility models such as the nearest distance, real time travel cost, kernel density, and two step floating catchment area (2SFCA), and explores the multiscale effect of public services accessibility on house prices with multiscale geographically weighted regression model. The results show that the differentiated scale effect not only exists among different public facility accessibilities, but also exists in different accessibility models of the same sort of facility. The article also suggests that different facilities should adopt its appropriate accessibility model. This study provides insights into spatial heterogeneity of urban public service facilities accessibility, which will benefit decision making in equal accessibility planning and policy formulation for the layout of urban service facilities.

Local Characteristics Related to SARS-CoV-2 Transmissions in the Seoul Metropolitan Area, South Korea

The Seoul metropolitan area is one of the most populated metropolitan areas in the world; hence, Seoul's COVID-19 cases are highly concentrated. This study identified local demographic and socio-economic characteristics that affected SARS-CoV-2 transmission to provide locally targeted intervention policies. For the effective control of outbreaks, locally targeted intervention policies are required since the SARS-CoV-2 transmission process is heterogeneous over space. To identify the local COVID-19 characteristics, this study applied the geographically weighted lasso (GWL). GWL provides local regression coefficients, which were used to account for the spatial heterogeneity of SARS-CoV-2 outbreaks. In particular, the GWL pinpoints statistically significant regions with specific local characteristics. The applied explanatory variables involving demographic and socio-economic characteristics that were associated with higher SARS-CoV-2 transmission in the Seoul metropolitan area were as follows: young adults (19~34 years), older population, Christian population, foreign-born population, low-income households, and subway commuters. The COVID-19 case data were classified into three periods: the first period (from January 2020 to July 2021), the second period (from August to November 2020), and the third period (from December 2020 to February 2021), and the GWL was fitted for the entire period (from January 2020 to February 2021). The result showed that young adults, the Christian population, and subway commuters were the most significant local characteristics that influenced SARS-CoV-2 transmissions in the Seoul metropolitan area.

Measuring hospital spatial accessibility using the enhanced two-step floating catchment area method to assess the impact of spatial accessibility to hospital and non-hospital care on the length of hospital stay

Background

Optimal healthcare access improves the health status and decreases health inequalities. Many studies demonstrated the importance of spatial access to healthcare facilities in health outcomes, particularly using the enhanced two-step floating catchment area (E2SFCA) method. The study objectives were to build a hospital facility access indicator at a fine geographic scale, and then to assess the impact of spatial accessibility to inpatient hospital and non-hospital care services on the length of hospital stay (LOS).

Methods

Data concerning older adults (≥75 years) living in the Nord administrative region of France were used. Hospital spatial accessibility was computed with the E2SFCA method, and the LOS score was calculated from the French national hospital activity and patient discharge database. The relationship between LOS and spatial accessibility to inpatient hospital care and to three non-hospital care types (general practitioners, physiotherapists, and home-visiting nurses) was analyzed with linear regression models.

Results

The mean number (standard deviation) of beds per 10,000 inhabitants was 19.0 (10.69) in Medical, Surgical and Obstetrics (MCO) facilities and 5.58 (2.19) in Postoperative and Rehabilitation Care (SSR) facilities, highlighting important variations within the region. Accessibility to hospital services was higher in large urban areas, despite the dense population and higher demand. In 2014, the mean LOS scores were 0.26 for MCO and 0.85 for SSR, but their geographical repartition was non-homogeneous. The linear regression analysis revealed a strong negative and significant association between LOS and non-hospital care accessibility.

Conclusions

This is the first study to measure spatial accessibility to inpatient hospital care in France using the E2SFCA method, and to investigate the relationship between healthcare utilization (LOS score) and spatial accessibility to inpatient hospital care facilities and three types of non-hospital care services. Our findings might help to make decisions about deploying additional beds and to identify the best locations for non-hospital care services. They might also contribute to improve access, and to ensure the best coordination and sustainability of inpatient and outpatient services, in order to better cover the population’s healthcare needs. International studies using multiple consensual indicators of healthcare outcomes and accessibility and sophisticated modeling methods are needed.