Distribution Of Health Care Resources Research Articles

Exploring sustainable health financing strategies in humanitarian settings: Challenges, innovations and efforts towards Achieving Universal Health Coverage

Sustainable health financing is critical in humanitarian settings to ensure that the most vulnerable populations have access to necessary healthcare services. In crises such as conflicts, natural disasters, or prolonged emergencies, healthcare systems are often destabilized, leading to significant challenges in providing adequate care. This review explores innovative financing mechanisms designed to support health services in these contexts, focusing on their potential to achieve Universal Health Coverage (UHC). Key challenges include limited funding, high out-of-pocket costs, and the uneven distribution of healthcare resources. In response, emerging models such as impact bonds, Islamic social finance, disaster risk insurance, and digital financial solutions offer new approaches to mobilizing resources and sustaining health interventions. These strategies are essential to bridging gaps in healthcare access, promoting equity, and strengthening the resilience of health systems. Policy recommendations highlight the importance of integrating emergency and routine health services, engaging communities, and enhancing coordination among stakeholders. Strengthening health financing mechanisms is vital for long-term improvements in health outcomes, especially in fragile settings. This research underscores the need for sustainable, inclusive policies that bolster health systems in the face of humanitarian crises.

Medical geographical zoning in part of Uzbekistan – A regional synthesis

This study delves into the nuanced realm of medical geography, focusing on the intricate interplay between geographical factors and public health outcomes in the Samarkand and Navoi regions of Uzbekistan. Over the decades, the field of medical geography has evolved, embracing a holistic perspective that integrates ecological, socioeconomic, and accessibility elements to elucidate the complex dynamics of disease distribution and healthcare provision. Utilizing a comprehensive methodology, this research employs a combination of GIS tools, statistical analysis, and expert input to delineate medical geographical zones within the study area. By synthesizing data from diverse sources including administrative records, environmental assessments, and demographic surveys, the study constructs a detailed picture of the region's health landscape. The analysis revealed five primary medical geographical zones and a sub-zone, each characterized by distinct natural features, economic activities, and health challenges. From the bustling urban centers of Samarkand and Navoi to the remote desert expanses of Uzguduk - Tomdi North, each zone presents unique opportunities and obstacles for healthcare delivery and environmental management. Key findings highlight the disproportionate distribution of healthcare resources, with densely populated areas in the southern part of the study area benefitting from greater accessibility to medical facilities compared to remote rural regions. Moreover, environmental factors such as air pollution, water contamination, and climatic variability emerge as significant determinants of public health, exacerbating respiratory ailments, cardiovascular diseases, and other health conditions. The study underscores the importance of spatial analysis and interdisciplinary collaboration in addressing complex health issues within diverse geographical landscapes. By mapping medical geographical zones and understanding their specific health concerns, policymakers and healthcare professionals can develop targeted interventions to improve healthcare access, mitigate environmental hazards, and promote community well-being. In conclusion, this research contributes valuable insights to the field of medical geography, shedding light on the multifaceted interactions between geography, environment, and health in the Samarkand and Navoi regions of Uzbekistan. Moving forward, further research and collaborative efforts are needed to address the underlying determinants of health disparities and foster sustainable development in the region.

An examination and analysis of the clustering of healthcare centers and their spatial accessibility in Tehran metropolis: Insights from Google POI data

Metropolises, as centers of diverse activities, encounter numerous challenges, including equitable access to healthcare services. This study examines the inequality in healthcare center accessibility in Tehran, a critical factor for sustainable urban development. Utilizing Google Point of Interest data, healthcare center clusters in Tehran were identified, and various clustering algorithms were tested. The Mean Shift Cluster algorithm was the most effective method. The study also mapped accessibility by analyzing the radius of neighborhoods around urban blocks. The findings reveal a significant imbalance in the distribution of healthcare centers in the city, with a concentration in the city center that does not align with population density—a key indicator of demand. Notably, District 7, despite being centrally located, relatively has a higher clusters' concentration of lower-quality healthcare centers. The findings reveal that four sub-districts situated in the peripheral regions of Tehran city, which collectively account for approximately 6.3% of the city's total area, exhibit significantly lower accessibility to the healthcare centers compared to other sub-districts. Overall, the areas with superior accessibility are predominantly found in the city center and extend towards the north, with accessibility decreasing as one moves towards the outskirts of the city. These results underscore the need for targeted urban planning to address the uneven distribution of healthcare resources and promote equitable access across Tehran.

Unraveling the drivers of inequality in primary health-care resource distribution: Evidence from Guangzhou, China

BackgroundPrimary health-care (PHC) resource plays a critical role in addressing challenges related to healthcare accessibility and costs, as well as implementing a graded diagnosis and treatment system. This study aims to analyze the extent and components of inequality in PHC resource allocation in Guangzhou. MethodsBy utilizing data from the Annual Report on Healthcare Institutions for community and township health centers in Guangzhou from 2012 to 2020, this paper analyses the distribution of human, material and financial resources. It examines inequities in health resource allocation using the Gini coefficient. Additionally, it investigates the internal structure of overall inequality through the two-stage nested Theil decomposition method and explores the influencing mechanisms of inequality using the concentration index decomposition method. ResultsThe findings indicate that between 2012 and 2020, except for beds in 2018 and 2019, the Gini coefficients for resource allocation relative to population size remained below 0.3. Moreover, the Gini coefficient for geographical area ranged from 0.1228 to 0.3481. The two-stage nested Theil decomposition results reveal that within-district disparity contributes the most to the overall inequality, exceeding 46 %. The Concentration indexes show negative values, and the decomposition analysis highlights the significant contribution of the number of individuals served (over 72 %) to the inequality in health resource allocation. ConclusionAt the administrative district level, the allocation of PHC resources in Guangzhou demonstrates overall equity, with within-district inequality identified as the primary contributor to the overall inequality. The distribution of PHC resources in Guangzhou follows a pro-poor pattern. The key factors influencing equity enhancement in PHC resource allocation in Guangzhou include the number of individuals served, the presence of township health centers among institution types, the number of hospital admissions per capita, and the proportion of children aged 0–3.

Dynamic recommender system for chronic disease-focused online health community

Unequal distribution of healthcare resources poses a significant challenge in numerous regions and countries worldwide. Online Health Communities (OHCs) serve as pivotal platforms for patients to share treatment experiences and seek emotional support from peers facing similar health challenges. The facilitation of efficient user navigation to relevant sub-communities and topics within OHCs emerges as a critical need. Addressing these complexities, a recommendation system specifically designed for OHCs is proposed to tackle unique challenges such as simultaneous prediction of sub-communities and topics with varying levels of information, capturing the influence of evolving health stages on patient interactions, and ensuring coherent recommendations. To meet these challenges, OHCs are conceptualized as dynamic tripartite graphs that model three primary entities—patients, sub-communities, and topics—alongside their temporal interactions. Novel techniques including dynamic tripartite subgraph convolution and dynamic tripartite collaborative filtering are introduced to effectively capture the impact of changing health stages. Additionally, a multi-type entity prediction method is developed to forecast sub-communities and topics, incorporating robust constraints to ensure the validity of predictions. The study conducts extensive experiments using real-world datasets from two online chronic disease communities, including the Breast OHC dataset and the Bladder OHC dataset, encompassing 5,346,591 and 16,427 patient interactions, respectively. Results demonstrate significant advancements over state-of-the-art methods, achieving maximum improvements of 11% and 15% in Mean Reciprocal Rank and Recall metrics, respectively. Sensitivity analyses of online and batch-based algorithms provide insights into the trade-offs between efficiency and accuracy, supported by an illustrative application example highlighting the system’s superiority over existing approaches.

Bayesian Modeling and Estimation of Spatial Risk for Hospitalization and Mortality from Ischemic Heart Disease in Paraná, Brazil.

Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in the state of Paraná (Brazil), using spatial analysis to identify areas with higher risk based on socioeconomic, demographic and health variables. This is an ecological study based on secondary and retrospective IHD hospitalization and mortality data obtained from the Brazilian Hospitalization and Mortality Information Systems during the 2010-2021 period. Data were analyzed for 399 municipalities and 22 health regions in the state of Paraná. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software. A total of 333,229 hospitalizations and 73,221 deaths occurred in the analyzed period, and elevated RR of hospitalization (RR = 27.412, CI 21.801; 34.466) and mortality (RR = 15.673, CI 2.148; 114.319) from IHD occurred in small-sized municipalities. In addition, medium-sized municipalities also presented elevated RR of hospitalization (RR = 6.533, CI 1.748; 2.006) and mortality (RR = 6.092, CI 1.451; 2.163) from IHD. Hospitalization and mortality rates were higher in white men aged 40-59 years. A negative association was found between Municipal Performance Index (IPDM) and IHD hospitalization and mortality. Areas with increased risk of hospitalization and mortality from IHD were found in small and medium-sized municipalities in the state of Paraná, Brazil. These results suggest a deficit in health care attention for IHD cases in these areas, potentially due to a low distribution of health care resources.

Advances in the selection and timing of postoperative radioiodine treatment in patients with differentiated thyroid carcinoma.

Differentiated thyroid cancer (DTC) is the most common endocrine malignancy. Patients who receive systematic care typically have a better prognosis. RAI treatment plays a key role in eradicating any remaining thyroid lesions in DTC patients, hence decreasing the risk of distant metastases and cancer recurrence. As research continues to advance, RAI treatment is becoming more and more individualized. Because of the excellent prognosis for DTC patients, there is a relatively broad window for RAI treatment, making it easy to overlook when to receive RAI treatment. However, research on this issue can help patients with varying recurrence risk stratification make better decisions about when to begin RAI treatment following surgery, and physicians can schedule patients based on the severity of their disease. This will improve patient prognosis and lessen needless anxiety in addition to helping solve the problems of unjust healthcare resource distribution. In this review, we will mainly discuss the target population of RAI treatment as well as studies that examine the impact of RAI treatment timingon patient outcomes. In an effort to discourage DTC patients and physicians from selecting RAI therapy at random, we also review the possible negative effects of this treatment.

Equality of healthcare resource allocation between impoverished counties and non-impoverished counties in Northwest China: a longitudinal study

BackgroundThe Health and Medical Assistance Program for Poverty Alleviation is part of China’s targeted poverty elimination strategy, which aims to protect poor people’s right to health and prevent them from becoming trapped in or returning to poverty because of illness. Many tasks have been defined in this program, including raising the medical insurance level, providing a triage system, improving medical and health services, and enhancing people’s health. One pivotal aspect of this initiative involves equitable health resource allocation, a key measure aimed at bolstering medical and health services. This study aimed to analyze and compare health resource allocations in different counties in Northwest China after the implementation of the program.MethodsThe Gini coefficient quantifies the level of distributional equality, the Theil index assesses the sources of inequality, and the Health Resource Agglomeration Degree gauges the accessibility of health resources.Results1) The health resource allocation distributed based on population(Gini Coefficient < 0.45) was more equitable than that distributed based on area(Gini Coefficient > 0.35) among counties in Northwest China. 2) The contribution rate within non-impoverished counties is higher than that of impoverished counties, which means the inequality within non-impoverished counties. 3) The allocation of beds in medical institutions by area in non-impoverished counties was better than that in impoverished counties, and accessibility to health services for residents in non-impoverished counties was better than that in impoverished counties.ConclusionThe analysis of health resource allocation among the five provinces in Northwest China revealed significant differences in equality among the five provinces in Northwest China, and the differences were mainly derived from the non-impoverished counties. Although the equality is gradually improving, the number of health resources in impoverished counties remain lower than that in non-impoverished counties.Subsequently, it is essential to ensure equitable distribution of healthcare resources while also taking into account their utilization and quality.

Uncovering the state of knowledge about healthcare gentrification: a scoping review protocol

IntroductionHealthcare gentrification is the process in which the distribution of healthcare resources within a neighbourhood affects residents' access to healthcare services. To understand the complexity of healthcare access and to...

Machine Learning for Evaluating Hospital Mobility: An Italian Case Study

This study delves into hospital mobility within the Italian regions of Apulia and Emilia-Romagna, interpreting it as an indicator of perceived service quality. Utilizing logistic regression alongside other machine learning techniques, we analyze the impact of structural, operational, and clinical variables on patient perceptions of quality, thus influencing their healthcare choices. The analysis of mobility trends has uncovered significant regional differences, emphasizing how the regional context shapes perceived service quality. To further enhance the analysis, SHAP (SHapley Additive exPlanations) values have been integrated into the logistic regression model. These values quantify the specific contributions of each variable to the perceived quality of service, significantly improving the interpretability and fairness of evaluations. A methodological innovation of this study is the use of these SHAP impact scores as weights in the data envelopment analysis (DEA), facilitating a comparative efficiency analysis of healthcare facilities that is both weighted and normative. The combination of logistic regression and SHAP-weighted DEA provides a deeper understanding of perceived quality dynamics and offers essential insights for optimizing the distribution of healthcare resources. This approach underscores the importance of data-driven strategies to develop more equitable, efficient, and patient-centered healthcare systems. This research significantly contributes to the understanding of perceived quality dynamics within the healthcare context and promotes further investigations to enhance service accessibility and quality, leveraging machine learning as a tool to increase the efficiency of healthcare services across diverse regional settings. These findings are pivotal for policymakers and healthcare system managers aiming to reduce regional disparities and promote a more responsive and personalized healthcare service.

The Impact of a City’s Healthcare Resources on Immigrants’ Employment Quality

This study investigates the impact of city healthcare resources on immigrants’ employment quality. It has implications for promoting equity in the distribution of healthcare resources, which is critical for immigrants’ survival and settlement. Moreover, the relationship between healthcare resources and employment quality is equally relevant to developing-country urbanization. Using data from the China Migrants Dynamic Survey (CMDS) from 2016 to 2018, we demonstrate the effect of healthcare resources on employment quality. Cities’ healthcare resources are significantly correlated with immigrants’ quality of employment. The more healthcare resources are available, the higher the income from work, the shorter the working hours, and the more stable the employment of immigrants. The quality-enhancing effect of healthcare resources on employment quality is substantial among immigrants with health training and medical files. Urban medical insurance has important differentiating implications for immigrants’ access to healthcare resources. Healthcare resources enhance the employment quality of immigrants by improving their health status and integration into local society. Promoting equalizing healthcare resources and adjusting the differences between urban and rural medical insurance systems increase immigrant employment quality.

Temporal Analysis of the Incidence, Mortality and Disability-Adjusted Life Years of Benign Gallbladder and Biliary Diseases in High-Income Nations, 1990-2019.

The aim of this observational study was to analyze trends in the incidence, mortality, and disability-adjusted life years (DALYs) of benign gallbladder and biliary diseases across high-income countries between 1990 and 2019. Benign gallbladder and biliary diseases place a substantial burden on healthcare systems in high-income countries. Accurate characterization of the disease burden may help optimize healthcare policy and resource distribution. Age-standardized incidence rates (ASIRs), age-standardized mortality rates (ASMRs), and DALYs data for gallbladder and biliary diseases in males and females were extracted from the 2019 Global Burden of Disease (GBD) study. A mortality-incidence index (MII) was also calculated. Joinpoint regression analysis was performed. The median ASIRs across the European Union 15+ countries in 2019 were 758/100,000 for females and 282/100,000 for males. Between 1990 and 2019 the median percentage change in ASIR was +2.49% for females and +1.07% for males. The median ASMRs in 2019 were 1.22/100,000 for females and 1.49/100,000 for males with a median percentage change over the observation period of -21.93% and -23.01%, respectively. In 2019, the median DALYs was 65/100,000 for females and 37/100,000 among males, with comparable percentage decreases over the observation period of -21.27% and -19.23%, respectively. International variation in lifestyle factors, diagnostic and management strategies likely account for national and sex disparities. This study highlights the importance of ongoing clinical efforts to optimize treatment pathways for gallbladder and biliary diseases, particularly in the provision of emergency surgical services and efforts to address population risk factors.

Trajectory of medical expenditure and regional disparities in hypertensive patients in South Korea.

The aim of this study is to understand how different regions influence the management and financial burden of hypertension, and to identify regional disparities in hypertension management and medical expenditure. The study utilized data from the Korean Health Panel Survey conducted between 2014 and 2018, focusing on individuals with hypertension. Medical expenditures were classified into three trajectory groups: "Persistent Low," "Expenditure Increasing," and "Persistent High" over a five-year period using trajectory analysis. Inverse Probability Weighting (IPW) analysis was then employed to identify the association between regions and medical expenditure trajectories. The results indicate that individuals residing in metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural areas were more likely to belong to the "Expenditure Increasing" group compared to the "Persistent Low Expenditure" group (OR = 1.07; 95% CI; p < 0.001), as opposed to those in the capital city (Seoul) (OR = 1.07; 95% CI; p < 0.001). Additionally, residents of rural areas were more likely to be in the "High Expenditure" group compared to the "Persistent Low Expenditure" group than those residing in the capital city (OR = 1.05; 95% CI; p = 0.001). These findings suggest that individuals in rural areas may be receiving relatively inadequate management for hypertension, leading to higher medical expenditures compared to those in the capital region. These disparities signify health inequality and highlight the need for policy efforts to address regional imbalances in social structures and healthcare resource distribution to ensure equitable chronic disease management across different regions.

Trends in Regional Disparities in Cardiovascular Surgery and Mortality in Korea: A National Cross-sectional Study.

Regional disparities in cardiovascular care in Korea have led to uneven patient outcomes. Despite the growing need for and access to procedures, few studies have linked regional service availability to mortality rates. This study analyzed regional variation in the utilization of major cardiovascular procedures and their associations with short-term mortality to provide better evidence regarding the relationship between healthcare resource distribution and patient survival. A cross-sectional study was conducted using nationwide claims data for patients who underwent coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), stent insertion, or aortic aneurysm resection in 2022. Regional variation was assessed by the relevance index (RI). The associations between the regional RI and 30-day mortality were analyzed. The RI was lowest for aortic aneurysm resection (mean, 26.2; standard deviation, 26.1), indicating the most uneven regional distribution among the surgical procedures. Patients undergoing this procedure in regions with higher RIs showed significantly lower 30-day mortality (adjusted odds ratio [aOR], 0.73; 95% confidence interval, 0.55 to 0.96; p=0.026) versus those with lower RIs. This suggests that cardiovascular surgery regional availability, as measured by RI, has an impact on mortality rates for certain complex surgical procedures. The RI was not associated with significant mortality differences for more widely available procedures like CABG (aOR, 0.96), PCI (aOR, 1.00), or stent insertion (aOR, 0.91). Significant regional variation and underutilization of cardiovascular surgery were found, with reduced access linked to worse mortality for complex procedures. Disparities should be addressed through collaboration among hospitals and policy efforts to improve outcomes.

Predictive Model for Medical Assistance

Medical tourism has emerged as a prominent global healthcare phenomenon, driven by various factors such as cost differentials, quality of care, and accessibility. The first aspect of medical tourism is the transnational use of healthcare services, which is frequently driven by financial savings and shortened wait times. Patients from high-income nations frequently go to less expensive locations for elective surgery, while people from low-income nations may look overseas for cutting-edge medical care due to a lack of local healthcare infrastructure. Patients who choose medical tourism locations do so because of the high quality of the care they receive. Patients are enticed to particular locations by accredited healthcare facilities and highly trained medical personnel. However, maintaining uniform quality across many healthcare systems is still difficult. The economic impact on the countries of origin and destination makes up the third aspect of medical tourism. Through higher healthcare sector income, tourism-related activities, and job creation, medical tourism can promote economic growth in destination nations. On the other hand, source nations could experience issues with the distribution of healthcare resources and the "brain drain" of medical specialists. The relevance of ethical considerations in medical travel cannot be overstated. To preserve the credibility of medical tourism, issues relating to informed consent, patient safety, and the equal distribution of healthcare resources must be properly addressed. The COVID-19 pandemic's effects on international travel and healthcare systems are just a few of the aspects that are taken into account in this abstract while discussing the future of medical tourism. It emphasises the necessity of international cooperation to create uniform policies, rules, and moral frameworks that guarantee the safety of patients taking part in medical tourism.

Impact of Healthcare Infrastructure on Maternal Mortality in Nigeria

This study investigates the impact of healthcare infrastructure on maternal mortality in Nigeria, focusing on the quality of care, availability of healthcare facilities, and institutional capacity. We employed a cross-sectional survey design, guided by Donabedian's Quality of Care Framework, and targeted 380 healthcare facilities in Lagos, Kano, and Enugu. Data was collected using structured questionnaires and analyzed using multiple regression analysis. The findings reveal that quality of care (β = .643, p &lt; .001) and availability of healthcare facilities (β = .362, p &lt; .001) significantly influence maternal mortality rates, while institutional capacity (β = .003, p = .882) does not have a significant impact. High-quality care and accessible healthcare facilities are crucial in reducing maternal deaths. Recommendations include continuous professional development for healthcare providers, equitable distribution of healthcare resources, and investments in healthcare infrastructure and governance. This research provides valuable insights for policymakers and healthcare stakeholders aiming to improve maternal health outcomes in Nigeria.

Spatial and social inequality of hierarchical healthcare accessibility in urban system: A case study in Shanghai, China

Urbanization is intensifying in cities, accompanied by burgeoning inequalities, notably in the healthcare sector. Limited research offers a granular examination of healthcare resource accessibility across diverse population groups. In this study, we employ census data from all 6164 communities in Shanghai to investigate the relationship between multi-scalar spatial dimensions and the socio-economic (dis)advantage of populations concerning healthcare resource accessibility. Distinct from previous studies, this research quantifies social inequality by considering the demographics of community residents and their interactions with healthcare facilities. We elucidate the stratified spatial distribution of healthcare accessibility across various spatial scales in Shanghai, leveraging Web Application Programming Interface (API) technology and examine the pervasive social inequalities across sub-district, district, and the central urban-suburban divide, focusing on specific population subgroups including gender, age, education level, wealth, household registration, ethnicity, occupation, and housing living facilities. Findings reveal that disparities in healthcare accessibility correlate with the quality of healthcare facilities, the socio-spatial attributes of localities, and the socio-economic and demographic profiles of the populations. The insights from this research will aid policymakers in enhancing the distribution and provision of healthcare resources, thereby promoting spatial and social equity in public healthcare system planning and implementation.

Spatial distribution and influencing factors of CDC health resources in China: a study based on panel data from 2016-2021.

Measuring the development of Chinese centers for disease control and prevention only by analyzing human resources for health seems incomplete. Moreover, previous studies have focused more on the quantitative changes in healthcare resources and ignored its determinants. Therefore, this study aimed to analyze the allocation of healthcare resources in Chinese centers for disease control and prevention from the perspective of population and spatial distribution, and to further explore the characteristics and influencing factors of the spatial distribution of healthcare resources. Disease control personnel density, disease control and prevention centers density, and health expenditures density were used to represent human, physical, and financial resources for health, respectively. First, health resources were analyzed descriptively. Then, spatial autocorrelation was used to analyze the spatial distribution characteristics of healthcare resources. Finally, we used spatial econometric modeling to explore the influencing factors of healthcare resources. The global Moran index for disease control and prevention centers density decreased from 1.3164 to 0.2662 (p < 0.01), while the global Moran index for disease control personnel density increased from 0.4782 to 0.5067 (p < 0.01), while the global Moran index for health expenditures density was statistically significant only in 2016 (p < 0.1). All three types of healthcare resources showed spatial aggregation. Population density and urbanization have a negative impact on the disease control and prevention centers density. There are direct and indirect effects of disease control personnel density and health expenditures density. Population density and urbanization had significant negative effects on local disease control personnel density. Urbanization has an indirect effect on health expenditures density. There were obvious differences in the spatial distribution of healthcare resources in Chinese centers for disease control and prevention. Social, economic and policy factors can affect healthcare resources. The government should consider the rational allocation of healthcare resources at the macro level.

Mapping of Health Resources in Lower Manya Krobo Municipality in the Eastern Region of Ghana.

Spatial disparities impact population health and are linked to social and health disparities. Understanding the scope, nature, and trends of regional inequalities can help create policies, strategies, and interventions that affect the morbidity and mortality of various disease control. The variations in the distribution of health facilities have resulted in differences in health outcomes within Ghana's administrative districts, of which the Lower Manya Krobo Municipality (LMKM) is no exception. The primary objective of this study was to examine the distribution of healthcare resources in the LMKM in the Eastern Region of Ghana. A single case study approach involving all health resources, facilities, and supporting service centers in the LMKM was adopted. All functional health facilities in the municipality during the study were included. The study partly used records of generated coordinates using the global positioning system of other resources and services. The Municipality had 16 health facilities and 29 supporting centers. There were 285 clinical health workers in the municipality. Odumase and Akuse had higher percentages of clinical health personnel. The municipality's population per single health worker ratio was 13,201:1. Agomanya had the highest number of facilities and support centers. The population per health facility ratio was 15,086 per facility. The study demonstrated disparities in the distribution of health facilities across the municipality. There is a need to ensure that all health resources are allocated to the population size and the health needs of the LMKM.

Factors affecting the place of death in patients with liver cancer in China, 2013–2020: A population-based study

BackgroundDespite the country's substantial liver cancer burden, there is limited research on the factors influencing the place of death (POD) of patients with liver cancer in China. This study aimed to delineate POD distribution among patients with liver cancer, identify the factors associated with hospital deaths, and offer valuable insights for the government to develop healthcare policies. MethodsData from 2013 to 2020 were obtained from the National Mortality Surveillance System (NMSS) of China. This analysis focused on the distribution of POD among individuals who succumbed to liver cancer. Variations in characteristic distributions across different categories were evaluated using a chi-squared test. We also applied a multilevel logistic regression analysis to identify the factors associated with hospital liver cancer deaths. The proportional change in variance was computed to evaluate the contributions of different factors in the model. ResultsFrom 2013 to 2020, the NMSS reported a total of 608,789 liver cancer-related deaths, of which 440,079 (72.29%) died at home, and 158,291 (26.00%) died in the hospital. Home remained the preferred POD among patients with liver cancer. The results demonstrated that female patients, aged between 0 and 14 years, of Han ethnicity, living in urban areas, unmarried, highly educated, and either employed in a professional, staff, or civil servant capacity, or retired patients tended to end their lives in the hospital. ConclusionsIn China, home continues to be the predominant POD for patients with liver cancer, with demographic and socioeconomic factors significantly influencing whether a hospital is their POD. Enhancing healthcare policymakers' understanding of the factors influencing the place of death for patients with liver cancer may assist in creating a more equitable distribution of healthcare resources and providing a variety of choices for minorities with distinct preferences for end-of-life care.