Distribution Of Health Care Resources Research Articles

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.

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.

Evaluation of healthcare-related factors influencing mental health of Taiwanese citizens among different age groups

The issue of mental health has gained heightened recognition as a significant public health concern due to its potential to significantly impact various aspects of individuals’ lives. Numerous factors may influence mental health, and this study seeks to investigate and compare potential healthcare-related factors that affect the mental health of Taiwanese individuals across different age groups. Data for this study were taken from the Taiwan Social Change Survey (TSCS), conducted in 2021. Descriptive statistics were calculated to compare the three age groups. Then, multiple regression models were constructed with mental health conditions as the dependent variable and demographics and other key healthcare-related components as independent variables, respectively. Results showed that, among the three age groups, the middle-aged adults had the highest BMI, and the older adults had significantly better mental health. As compared with the other age groups, the older adults had significantly better perceptions of fair distribution of healthcare resources, and their trust in the healthcare system was the highest. With regard to searching for online healthcare information, the frequency reported by the older adults was the lowest. The regression model showed that, religious belief, trust in the healthcare system and searching for online healthcare information were significantly associated with mental health of middle-aged adults. In the younger group, searching for online healthcare information was significantly negatively associated with mental health. The study’s findings provide insight into how to provide Taiwanese citizens of different age groups with proper and targeted mental health promotion activities.

Relationships between long-term exposure to major PM2.5 constituents and outpatient visits and hospitalizations in Guangdong, China

Ambient fine particulate matter (PM2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM2.5 constituents (WQS index) and outpatient visits (IR%, percentage increases in risk per unit WQS index increase:1.73, 95%CI: 1.72, 1.74) as well as hospitalizations (IR%:5.15, 95%CI: 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR%: 7.54, 95%CI: 7.33, 7.74 and IR%: 9.55, 95%CI: 8.36, 10.75, respectively) or decreased winter air temperatures (IR%: 1.88, 95%CI: 1.68, 2.08 and IR%: 4.87, 95%CI: 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM2.5 pollution.

Healthcare equity in focus: bridging gaps through a spatial analysis of healthcare facilities in Irbid, Jordan

In the Irbid Governorate, Jordan, equitable healthcare facility distribution is vital to ensuring healthcare accessibility and improving public health outcomes. This study investigated the spatial distribution, accessibility, and conformity of healthcare facilities to the Ministry of Health standards to identify areas requiring improvement. Using geographic information systems (GIS), three spatial analyses were conducted: nearest neighbor analysis, buffer analysis, and service area analysis. These analyses comprehensively assessed the healthcare landscape, revealing a random spatial distribution pattern of healthcare facilities; and indicating an absence of structured organization. The buffer analysis revealed concentrations in specific regions, while others were underserved. The Service Area Analysis revealed significant healthcare access challenges, especially in remote areas. The healthcare resource distribution of the Irbid governorate fell short of national and international standards, emphasizing the need for improvements. To address these disparities, policymakers and healthcare authorities should focus on equitably redistributing resources, tailoring allocation to local needs, improving remote area infrastructure, and refining government policies. Continuous monitoring and evaluation are imperative to ensure alignment with international standards and achieve healthcare equity. The insights from this case study provide valuable guidance for regions facing similar healthcare distribution challenges.

Does unequal economic development contribute to the inequitable distribution of healthcare resources? Evidence from China spanning 2001–2020

BackgroundThere is a dearth of research combining geographical big data on medical resource allocation and growth with various statistical data. Given the recent achievements of China in economic development and healthcare, this study takes China as an example to investigate the dynamic geographical distribution patterns of medical resources, utilizing data on healthcare resources from 290 cities in China, as well as economic and population-related data. The study aims to examine the correlation between economic growth and spatial distribution of medical resources, with the ultimate goal of providing evidence for promoting global health equity.MethodsThe data used in this study was sourced from the China City Statistical Yearbook from 2001 to 2020. Two indicators were employed to measure medical resources: the number of doctors per million population and the number of hospital and clinic beds per million population. We employed dynamic convergence model and fixed-effects model to examine the correlation between economic growth and the spatial distribution of medical resources. Ordinary least squares (OLS) were used to estimate the β values of the samples.ResultsThe average GDP for all city samples across all years was 36,019.31 ± 32,029.36, with an average of 2016.31 ± 1104.16 doctors per million people, and an average of 5986.2 ± 6801.67 hospital beds per million people. In the eastern cities, the average GDP for all city samples was 47,672.71 ± 37,850.77, with an average of 2264.58 ± 1288.89 doctors per million people, and an average of 3998.92 ± 1896.49 hospital beds per million people. Cities with initially low medical resources experienced faster growth (all β < 0, P < 0.001). The long-term convergence rate of the geographic distribution of medical resources in China was higher than the short-term convergence rate (|βi + 1| > |βi|, i = 1, 2, 3, …, 9, all β < 0, P < 0.001), and the convergence speed of doctor density exceeded that of bed density (bed: |βi| >doc: |βi|, i = 3, 4, 5, …, 10, P < 0.001). Economic growth significantly affected the convergence speed of medical resources, and this effect was nonlinear (doc: βi < 0, i = 1, 2, 3, …, 9, P < 0.05; bed: βi < 0, i = 1, 2, 3, …, 10, P < 0.01). The heterogeneity between provinces had a notable impact on the convergence of medical resources.ConclusionsThe experiences of China have provided significant insights for nations worldwide. Governments and institutions in all countries worldwide, should actively undertake measures to actively reduce health inequalities. This includes enhancing healthcare standards in impoverished regions, addressing issues of unequal distribution, and emphasizing the examination of social determinants of health within the domain of public health research.

Availability of resources for paediatric hearing care in a South African province.

Unavailability of healthcare resources can lead to poor patient outcomes. The latter is true for infants with hearing loss and require early hearing detection and intervention (EHDI). To determine the availability and distribution of resources for EHDI in state hospitals in the Eastern Cape (EC) province, South Africa. Sixteen state hospitals (nine district, four regional and three tertiary hospitals). Descriptive cross-sectional survey completed between July 2022 and October 2022. Thirteen hospitals had audiologists (n= 4) or speech therapists and audiologists (n= 9). Specific to equipment, 10 hospitals had a screening otoacoustic emissions or automated auditory brainstem response, 8 hospitals had diagnostic middle ear analysers and only 3 hospitals had diagnostic auditory brainstem response and/or auditory steady state response. Twelve hospitals did not have visual response audiometry (VRA) and 94% had no hearing aid verification systems. Budget allocations were uneven, with only 10 hospitals, i.e., 4 districts, all regional and 2 tertiary hospitals being allocated varying amounts. Subsequently, only 50% provided newborn hearing screening, 56% provided diagnostic evaluations and 14 hospitals fitted hearing aids. Results revealed a limited and uneven distribution of resources, which negatively impacted the provision of EHDI. Even distribution of healthcare resources and further research aimed at strengthening hearing health services is recommended as these could potentially improve equitable access to EHDI and the overall quality of healthcare provided.Contribution:This study highlights the need for even distribution of resources and strengthening of health systems, especially in the dawn of the National Health Insurance.

Overcoming barriers to prostate cancer care in the Philippines

Prostate cancer (PCa) is a health concern affecting millions of men globally, with a concerning rise in incidence in the Philippines, a country that faces a complex set of barriers to equitable access to quality PCa care. In this article, we describe the unique geographic, economic, socio-cultural, and political factors that influence access to screening, diagnosis, treatment, and supportive services in the country, and explore avenues for development. The country lacks a nationwide PCa registry to inform resource allocation and guide PCa cancer care programs and policy. Misconceptions, cultural barriers and negative attitudes about PCa among Filipino men adversely influence health-seeking behavior. Inadequate insurance coverage, and high out-of-pocket costs obstruct access to essential care. Geographic and political factors contribute to the uneven distribution of healthcare resources needed for comprehensive PCa care, including access to medical specialists, essential medicines, and surgical and radiotherapeutic equipment. Overcoming these challenges requires a collaborative effort encompassing robust data collection, awareness campaigns to reshape societal norms, policy and economic reforms, infrastructure improvements, and enhanced collaboration among healthcare professionals to provide evidence-based care. Addressing these issues holistically can pave the way to better outcomes and improved quality of life for Filipino men with this life-altering disease.

Incidence, prevalence, and pattern of medical service utilization of children's rare lung diseases in South Korea.

Children's rare lung diseases are a heterogeneous group of rare lung diseases with significant morbidity and mortality. There is very limited information on the incidence and prevalence of children's rare lung diseases in Asia. We investigated the nationwide incidence, prevalence, and pattern of medical service utilization of children's rare lung diseases in Korea. We studied patients who were diagnosed with rare lung diseases coded per International Statistical Classification of Diseases and Related Health Problems, 10th Edition and registered in the national rare diseases database of confirmed patients. Data was extracted from the Korean National Health Insurance Service Claims database over 2019-2021. Average incidence rate was 12.9 new cases per million children per year, and average prevalence rate was 60.2 cases per million children during the study period of 2019-2021. We found that more than 65% of new cases were diagnosed before 2 years of age. ChILD, primary ciliary dyskinesia, and cystic fibrosis were usually diagnosed after 6 years of age. Congenital airway and lung anomalies were often diagnosed before 2 years of age. Busan and Gyeongsangnam-do residents tended to visit hospitals near their place of residence, while residents of other areas tended to visit hospitals in Seoul regardless of their area of residence. We examined the epidemiology of rare lung diseases in children in South Korea. Our estimation of the incidence and prevalence could be used for sustainable health care and equitable distribution of health care resources.

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

BackgroundEnsuring 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.MethodsTo 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).ResultsSpatial 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.ConclusionsThree-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.

The 2023 Addiction Health Services Research Conference: Back in Person and Taking a Bite of the Big Apple.

The Addiction Health Services Research (AHSR) Conference has been held since 2002. This Conference brings together researchers, graduate students, policymakers, and treatment providers to focus improving the organization, distribution, and financing of healthcare resources for prevention/care of SUD. The AHSR 2023 Conference took place in New York City, October 18-20th, and was hosted by the Center for Health Economics of Treatment Interventions for Substance Use Disorder, HCV, and HIV (CHERISH; cherishresearch.org). Attended by more than 300 participants, the Conference comprised several themes relating to the latest research on addiction health services delivery, financing, and impact. The agenda also included pre-conference workshops, distinguished plenary speakers, a multitude of networking opportunities, and career support for early-stage and minority investigators. AHSR 2023 featured 3 plenary sessions, 120 oral presentations, and 143 poster presentations from academics throughout the world. Overall, AHSR 2023 provided numerous opportunities to advance the field of addiction health services research. The state-of-the-art techniques and insights gained by attending scholars will position them to be change-agents in the addiction field going forward.

Uncovering heterogeneous inequities induced by COVID-19 interventions: Evidence from three states in the U.S.

The debate surrounding the efficacy of the interventions stipulated at the peak of the COVID-19 pandemic is still raging. Specifically, there are mixed reactions to the success of the interventions. Even when the response strategies were deemed satisfactory, there were still lingering perceptions of inherent systemic failures due to the inequity of the seeming success. The objective of this paper is to reconcile these tensions by examining the heterogeneous impacts of stipulated interventions in the U.S. The examination employs the widely regarded simulation platform, COVASIM, to examine the equity implications of the prescribed interventions. A tailored Gini coefficient is used to evaluate the impact of the interventions with respect to the equitable distribution of healthcare resources that underscore the interventions. The findings indicate that there were inequities in the delivery of the interventions. Furthermore, the examination shows that the efficacy of the interventions has a different distribution across different subgroups and also by location such that the inequities were more profound across minority-populated locations. The disparities in the interventions across age, gender, and racial subgroups translated into the disproportionate count of cases and mortality. These findings provide guidance for future pandemic policies, highlighting that a one-size-fits-all approach is suboptimal. Tailored interventions for different population categories are necessary to achieve equitable success and minimize cases and fatalities.

The effect of public hospital closure on the death of long-term inpatients in Korea.

This study aimed to examine the changes in health outcomes and the patterns of medical institution utilization among patients with long-term stays in public hospitals following the closure of a public medical center. It also sought to present a proposal regarding the role of public hospitals in countries with healthcare systems predominantly driven by private entities, such as Korea. To assess the impact of a public healthcare institution closure on health outcomes in a specific region, we utilized nationally representative health insurance claims data. A retrospective cohort study was conducted for this analysis. An analysis of the medical utilization patterns of patients after the closure of Jinju Medical Center showed that 67.4% of the total medical usage was redirected to long-term care hospitals. This figure is notably high in comparison to the 20% utilization rate of nursing hospitals observed among patients from other medical facilities. These results indicate that former patients of Jinju Medical Center may have experienced limitations in accessing necessary medical services beyond nursing care. After accounting for relevant mortality factors, the analysis showed that the mortality rate in closed public hospitals was 2.47 (95% confidence interval, 0.85 to 0.96) times higher than in private hospitals. The closure of public medical institutions has resulted in unmet healthcare needs, and an observed association was observed with increased mortality rates. It is essential to define the role and objectives of public medical institutions, taking into account the distribution of healthcare resources and the conditions of the population.

Demystifying hospital size distribution: A geographical approach

Hospital size distribution, i.e., the uneven allocation of healthcare resources between hospitals of different size classes, significantly impacts healthcare equality and efficiency and challenges healthcare governance. Yet, its variation is inadequately explained by two prevalent approaches to size distribution – the statistical approach merely works on statistical patterns, while the economic approach has difficulties in calculating hospital cost-returns. This study provides an alternative – a geographical approach – to demystify hospital size distribution. Incorporating the distinctiveness of healthcare into George Stigler's (1958) classic survivor analysis of firm size distribution, we conceptualize hospital size distribution as the result of hospitals' interactions with their socio-economic-technical environment in a defined area, and thus its pattern and variation could be understood through its coevolution with geographical contexts. We substantiate this idea with a study on China's provincial hospital size distributions between 2002 and 2019. During this period, hospitals with 0–99 beds maintained a stable proportion, while the size class of 800+ beds grew significantly, in contrast to the reduction in the size class of 100–799 beds. Cluster analysis identifies four clusters of provinces dominated by different hospital size classes after healthcare delivery reform in 2012. Cross-sectional time-series regression models find evolving impacts from market power, government intervention, and advancement of medical technology. We also offer a novel approach to understanding healthcare resource distribution by examining the structure rather than merely the number of healthcare resources.

Inequality in the distribution of resources in the health sector before and after the Health Transformation Plan in Qazvin, Iran

BackgroundThe equitable distribution of healthcare resources represents a paramount objective in the realm of global health systems. Thus, the present study sought to assess the fairness in the allocation of health resources at Qazvin University of Medical Sciences (QUMS), both prior to and subsequent to the implementation of the Health Transformation Plan (HTP) using the Gini coefficient and the Hirschman–Herfindahl index (HHI).MethodsThis descriptive-analytical study aimed to investigate the distribution of healthcare resources among general practitioners (GPs), specialists, and subspecialists employed at QUMS between 2011 and 2017. Demographic data pertaining to the cities were obtained from the statistical yearbooks of the Statistical Center of Iran, while information regarding the healthcare workforce was extracted from QUMS records. The analysis utilized two key measures, namely the Gini coefficient and the HHI, to assess the fairness of resource distribution. Data analysis was performed using Microsoft Excel 2016 and the Stata statistical software.ResultsThe highest number of GPs, specialists, and subspecialists was observed in 2014, 2017, and 2017, respectively, while the lowest number was recorded in 2016, 2011, and 2015, respectively. From 2011 to 2017, the Gini coefficient for GPs ranged between 0.61 and 0.63. Among specialists, the lowest Gini coefficient value was observed in 2015 (0.57), while the highest was recorded in 2017 (0.60). The Gini coefficient for subspecialists remained constant at 0.52 from 2011 to 2017. The HHI revealed a high concentration of GPs in the cities of Qazvin province. Although the disparity gradually decreased in the specialties of eye, ear, nose, and throat, and pediatrics, the concentration still persists in Qazvin. In general surgery, the index value is low, indicating some level of inequality. In anesthesia and neurology, the index value decreased after the HTP and reached 5700; however, achieving equality (below 1000) still requires further efforts. No significant change in the index was observed after the HTP in specialties such as neurosurgery, rehabilitation, and nuclear medicine. Subspecialists also exhibited a concentration in the city of Qazvin.ConclusionBased on the analysis of the Gini and HHI, it is evident that the distribution of GPs has not undergone significant changes following the implementation of the HTP. The Gini coefficient, which ranges from 0.4 to 0.6, indicates a high to complete level of inequality in the distribution of specialists and subspecialists. Moreover, the HHI exceeds 1000, reflecting a concentration of resources in specific areas. As a result, the HTP has not yet achieved its goal of ensuring a fair distribution of human resources. To address this issue, it is recommended to redesign distribution policies, including the allocation of physical health resources, such as specialized hospitals, beds, and medical equipment. Additionally, increasing student admissions in specialized and subspecialized fields and implementing tariff incentives can contribute to a more equitable distribution of resources. By aligning distribution policies with the principle of fairness, the healthcare system can better address the issue of resource distribution.

HBsAg Status, Molecular Detection and Therapy Evaluation of Hepatitis B Patient

The management of chronic hepatitis B involves various therapeutic approaches, including nucleotide analogs (NUCs) and pegylated-interferon alpha (peg-IFN), either in isolation or in combination. Reverse transcriptase enzyme is competitively inhibited by NUCs, which effectively suppresses HBV replication and lowers viral load. Concerning their cost-effectiveness, high response rates, low side effects, and oral administration, NUCs are recommended. Prolonged use, particularly of NUCs with a low genetic barrier or as monotherapy, can, however, lead to resistance, long-term safety issues, and the need for ongoing treatment. Physicians and other healthcare professionals are extremely concerned about the emergence of resistance and possible safety concerns related to the long-term use of NUCs. Moreover, the requirement for continuous therapy presents notable obstacles concerning patient adherence, distribution of healthcare resources, and overall economic viability. To clarify these problems and direct the creation of more potent and long-lasting treatment plans for chronic hepatitis B, urgent research is required. Hepatitis B surface antigen (HBsAg) detection is frequently accomplished via the use of the Chemiluminescent Microparticle Immunoassay (CMIA), which is a crucial early serologic marker for screening and diagnosis. Polymerase chain reaction (PCR) molecular testing is employed to confirm the presence of HBsAg. Polymerase Chain Reaction (PCR) was the technique we utilized to verify the outcomes. Twenty-eight of the HBsAg-positive patients at W.Z. Johannes Kupang Hospital had positive PCR results, highlighting the significance of molecular confirmation. The results of this study emphasize the value of precise HBsAg testing and the supplementary function of molecular confirmation in the treatment of patients with chronic hepatitis B. Furthermore, it clarifies the current therapeutic approaches applied to this patient population, highlighting the necessity of customized therapeutic approaches based on each patient's unique profile and potential complications.

Ethical Considerations in AI-assisted Decision- Making for End-Of-Life Care in Healthcare.

This paper delves into the ethical implications of deploying artificial intelligence (AI) in decision-making processes related to end-of-life care within healthcare settings. As AI continues to advance, its integration in healthcare introduces both opportunities and challenges, particularly in navigating the sensitive realm of end-of-life care. The paper explores this intersection, seeking to contribute valuable insights to the ongoing discourse on responsible AI implementation in the healthcare sector. Central to ethical considerations in end-of-life care is the principle of autonomy, emphasizing the importance of respecting patients' ability to make informed decisions about their care preferences. The paper argues for the need to design AI systems that augment rather than diminish patient autonomy, ensuring that individuals facing end-of-life decisions remain active participants in the process. Furthermore, the principles of beneficence and non-maleficence are highlighted, emphasizing the imperative for AI systems to enhance patient well-being while minimizing the risk of harm, both physical and psychological. Justice in the distribution of healthcare resources, including AI technologies, is crucial, and the paper emphasizes the need to address potential disparities in access. Transparent and explainable AI systems are advocated to foster trust among patients, families, and healthcare providers, enabling a better understanding of the rationale behind AI-driven recommendations. [1] The concept of accountability is explored, emphasizing the continued responsibility of healthcare professionals in overseeing and validating AI recommendations to maintain ethical standards. Cultural sensitivity is identified as a key consideration, recognizing and respecting diverse perspectives on end-of-life care. The paper underscores the significance of designing AI systems that accommodate cultural nuances and avoid imposing values that may conflict with patients' beliefs and preferences. Additionally, the emotional and psychological impact of AI-assisted decision-making is addressed, emphasizing the importance of maintaining the human touch in end-of-life care and acknowledging the roles of empathy, compassion, and human connection. The paper provides a comprehensive examination of the ethical dimensions surrounding AI-assisted decision-making in end-of-life care. By addressing autonomy, beneficence, justice, transparency, accountability, cultural sensitivity, and emotional impact, it offers a framework for responsible AI integration that aligns with ethical principles in healthcare, ultimately contributing to the enhancement of end-of-life care practices.