Distribution Of Health Care Resources Research Articles

Bearing allostatic load: insights into a more equitable future within cardio-oncology.

Chronic stress is often regarded as a significant cause of morbidity and mortality; however, the mechanistic link between stress and various disease states has not yet been fully characterized. We explore the concept of allostatic load, a measurement of the physiological burden of chronic stress, as well as its potential role in disease pathogenesis as it relates to cardiovascular disease, cancer, and health-related disparities. Building from this framework, we then posit the potential implications of allostatic load on patient care and research in cardio-oncology. We identify allostatic load as a potential clinically actionable tool to improve health equity in cardio-oncology.

Characteristics of road traffic mortality and distribution of healthcare resources in Thailand

Road traffic mortalities (RTMs), a leading cause of death globally, mostly occur in low- and middle-income countries, and having sufficient healthcare resources could lower the number of these fatalities. Our study aimed to illustrate the incidence of RTMs per 100,000 population and to compare the distribution of healthcare resources from 2011 to 2021 with rates of RTMs in the 77 provinces of Thailand. We divided the population into adults (≥ 15 years) and children (0–14 years). Lorenz curve and Gini coefficient were used to measure the level of distribution and equality of hospital resources and in relation to RTMs across the country. The average number of deaths was 30.34 per 100,000 per year, with male predominance. The RTM rates for adults and children were 32.71 and 19.08 per 100,000 respectively, and motorcycle accidents accounted for the largest percentage of deaths across all age groups. The Gini coefficient showed that operating rooms (0.42) were the least equally distributed hospital resource, while physicians were the most equally distributed (0.34). Anomalies were identified between the distribution of RTMs and available hospital resources. We hope our study will be beneficial in reallocating these resources more fairly to reflect the different numbers of traffic accidents in each province with the aim of reducing lower traffic-related deaths.

Measuring the geographic disparity of comorbidity in commercially insured individuals compared to the distribution of physicians in South Africa

BackgroundMeasuring and addressing the disparity between access to healthcare resources and underlying health needs of populations is a prominent focus in health policy development. More recently, the fair distribution of healthcare resources among population subgroups have become an important indication of health inequities. Single disease outcomes are commonly used for healthcare resource allocations; however, leveraging population-level comorbidity measures for health disparity research has been limited. This study compares the geographical distribution of comorbidity and associated healthcare utilization among commercially insured individuals in South Africa (SA) relative to the distribution of physicians.MethodsA retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidity and physicians for 2.6 million commercially insured individuals over 2016–2017, stratified by geographical districts and population groups in SA. We applied the Johns Hopkins ACG® System across the claims data of a large health plan administrator to measure a comorbidity risk score for each individual. By aggregating individual scores, we determined the average healthcare resource need of individuals per district, known as the comorbidity index (CMI), to describe the disease burden per district. Linear regression models were constructed to test the relationship between CMI, age, gender, population group, and population density against physician density.ResultsOur results showed a tendency for physicians to practice in geographic areas with more insurance enrollees and not necessarily where disease burden may be highest. This was confirmed by a negative relationship between physician density and CMI for the overall population and for three of the four major population groups. Among the population groups, the Black African population had, on average, access to fewer physicians per capita than other population groups, before and after adjusting for confounding factors.ConclusionCMI is a novel measure for healthcare disparities research that considers both acute and chronic conditions contributing to current and future healthcare costs. Our study linked and compared the population-level geographical distribution of CMI to the distribution of physicians using routinely collected data. Our results could provide vital information towards the more equitable distribution of healthcare providers across population groups in SA, and to meet the healthcare needs of disadvantaged communities.

Geographical Distribution of Pancreatic Cancer in the State of Mississippi by Incidence and Mortality From 2003 to 2019.

Pancreatic cancer can be a very debilitating disease. In the USA and around the world, pancreatic cancer is among the causes ofcancer-related deaths. This study aims to highlight mortality and incidence rates of pancreatic cancer by geographic location. The study area is the state of Mississippi with atargeted time period between 2003 and 2019. The Mississippi Cancer Registry is the source of data for this study. The subject under investigation was divided into two phases. The first phase involved analyzing data on the incidence rate while the second phase entailed data analysis of the pancreatic cancer mortality rate in Mississippi. In both phases, the focus was on three categories of geographic locations in Mississippi, which includepublic health districts, the regional cancer coalitions in the state, and the interplay between rural and urban locations.Descriptiveand inferential statistical approaches with graphical techniques and tabulations were utilized in data presentation. The results of this study demonstrate there are variations in the incidence rates of pancreatic cancer by geographic location in Mississippi. In the data analysis of the Mississippi public health districts, the worst-hit areas include the rural communities in the rural-urban regional analysis, the Delta region among the cancer coalition regions, and the Central District (incidence rates) and North District (mortality rates). In Mississippi, there is a need for aggressive community-based participation and education. This approach will help improve screening and early detection of pancreatic cancer. Healthcare intake should be boosted and geared toward a reduction in mortality rates. To minimize disparities that eventually lead to differences in disease incidence and mortality from different locations, legislative and non-legislative authorities should advocate for equitable distribution of healthcare resources. An understanding of the geographic distribution of pancreatic cancer in a state will aid in the designation of specific primary prevention measures targeted in the worst-hit communities.

Spatial modeling of vaccine deserts as barriers to controlling SARS-CoV-2

BackgroundCOVID-19 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We sought to measure if the disparities seen in the geographic distribution of other COVID-19 healthcare resources were also present during the initial rollout of the COVID-19 vaccine.MethodsUsing a comprehensive COVID-19 vaccine database (VaccineFinder), we built an empirically parameterized spatial model of access to essential resources that incorporated vaccine supply, time-willing-to-travel for vaccination, and previous vaccination across the US. We then identified vaccine deserts—US Census tracts with localized, geographic barriers to vaccine-associated herd immunity. We link our model results with Census data and two high-resolution surveys to understand the distribution and determinates of spatially accessibility to the COVID-19 vaccine.ResultsWe find that in early 2021, vaccine deserts were home to over 30 million people, >10% of the US population. Vaccine deserts were concentrated in rural locations and communities with a higher percentage of medically vulnerable populations. We also find that in locations of similar urbanicity, early vaccination distribution disadvantaged neighborhoods with more people of color and older aged residents.ConclusionGiven sufficient vaccine supply, data-driven vaccine distribution to vaccine deserts may improve immunization rates and help control COVID-19.

Improving the Efficiency of Geographic Target Regions for Healthcare Interventions.

Appropriate prioritisation of geographic target regions (TRs) for healthcare interventions is critical to ensure the efficient distribution of finite healthcare resources. In delineating TRs, both 'targeting efficiency', i.e., the return on intervention investment, and logistical factors, e.g., the number of TRs, are important. However, existing approaches to delineate TRs disproportionately prioritise targeting efficiency. To address this, we explored the utility of a method found within conservation planning: the software Marxan and an extension, MinPatch ('Marxan + MinPatch'), with comparison to a new method we introduce: the Spatial Targeting Algorithm (STA). Using both simulated and real-world data, we demonstrate superior performance of the STA over Marxan + MinPatch, both with respect to targeting efficiency and with respect to adequate consideration of logistical factors. For example, by design, and unlike Marxan + MinPatch, the STA allows for user-specification of a desired number of TRs. More broadly, we find that, while Marxan + MinPatch does consider logistical factors, it also suffers from several limitations, including, but not limited to, the requirement to apply two separate software tools, which is burdensome. Given these results, we suggest that the STA could reasonably be applied to help prevent inefficiencies arising due to targeting of interventions using currently available approaches.

OR28-1 Racial and Ethnic Disparities in Diabetes Technology Use amongst Persons with Type 1 Diabetes

Abstract Objective Despite recent advances in diabetes technology, the distribution of healthcare resources is often unequal among racial and socio-economic groups. A recent multicenter study looking at technology use amongst young adults with T1D demonstrated that socioeconomic status (SES) was not the sole driver of racial/ethnic disparities and that adjustment for income, insurance level, and health literacy did not significantly attenuate disparities. Here we present a retrospective cohort study looking at racial/ethnic disparities in insulin pump and CGM use in adults with T1D at an urban university hospital system. Methods We reviewed the charts of all adults aged 18 to 89 with T1D who attended the University of Maryland Center for Diabetes and Endocrinology (UMCDE) between 1/2019 and 12/2019. Age, gender, race/ethnicity, type of insurance, ZIP code, BMI, A1c, method of insulin delivery, and type of glucose monitoring device were obtained from each chart. We utilized the 2019 US Census data to determine the median income for each ZIP code. Patient charts were re-accessed in 2021 to check for changes in diabetes technology use from 1/2020 until 12/2021. Logistic regression modeling was done in PRISM to control for age, gender, race, insurance type, ZIP code, last known provider, BMI, and A1c. Hosmer-Lemeshow test was done to evaluate goodness of fit. Stratified analysis was done for potential confounders such as insurance type and income. The Breslow-Day test and Likelihood Ratio test for nested models were used to evaluate their degree and significance. Result A total of 532 adults were included in the study; 277 identified as non-Hispanic (NH) White, 204 identified as NH Black, 7 identified as Hispanic, and 44 identified as other racial/ethnic groups. NH White adults had a significantly higher insulin pump use when compared to NH Black (adjusted ratio 54.0% vs. 18.4%, OR 2.43 after regression, 95%CI [1.41-4.22]). Similarly, NH White adults had significantly higher CGM use when compared to NH Black (66.5% vs. 35.2%, OR 2.00 after regression, 95%CI [1.24-3.22]). Disparities between NH White and NH Black patients did not resolve throughout 2020-2021. Insurance type was a potential effect modifier for CGM prescriptions between NH White and NH Blacks (Crude OR 4.04, Commercial Strata OR 2.68, Medicaid 1.79, Medicare 2.79, Other/Self-pay 25.7, p=0.039 on Breslow-Day test). There was large heterogeneity in the rate of Pump or CGM prescriptions between providers. Conclusion NH White adults with T1D were significantly more likely to have been prescribed diabetes-related technologies when compared to other racial/ethnic groups, and this difference did not resolve over 2 years of follow-up. Future directions include a comprehensive survey of our population regarding patient-derived and patient-perceived factors driving disparities beyond socioeconomic status. Presentation: Tuesday, June 14, 2022 9:45 a.m. - 10:00 a.m.

Markers and associations of nutrition identified in a senior adult oncology clinic

Approximately half of all cancers occur in adults older than 65 and it is estimated that 70% of all cancers will occur among people aged 65 years or older by 2030. [1] Cancer treatment decisions for older adults are complicated by the patients' comorbidities, physical and functional impairments, and poorer social support systems. [2] Nutrition and frailty are known to negatively impact cancer outcomes. [3,4] These factors are influenced by social determinants of health such as the inequitable distribution of both healthcare resources and access to food.

Don’t just call me Latinx: A Call for Data Disaggregation to Disrupt Monolith Views

This paper aims to illuminate how and to what extent non-disaggregated data continues to perpetuate and reproduce the oppression of people of colour within the Latinx community (Freire, 1998), who lay at an intersection of identities (Crenshaw, 1991). Non-disaggregated data may continue to allow the disproportionate distribution of resources, including educational and healthcare resources. This paper mainly focuses on the experiences of AfroLatinx people. This paper details why the authors call for disaggregating data about the Latinx community. Discussions of their findings focus on Anti-racism, intersectionality, and the dangers of single stories. Implications and recommendations for future scholarship, policy legislation, and community activism follow.

MedML: Fusing medical knowledge and machine learning models for early pediatric COVID-19 hospitalization and severity prediction

SummaryThe COVID-19 pandemic has caused devastating economic and social disruption. This has led to a nationwide call for models to predict hospitalization and severe illness in patients with COVID-19 to inform the distribution of limited healthcare resources. To address this challenge, we propose a machine learning model, MedML, to conduct the hospitalization and severity prediction for the pediatric population using electronic health records. MedML extracts the most predictive features based on medical knowledge and propensity scores from over 6 million medical concepts and incorporates the inter-feature relationships in medical knowledge graphs via graph neural networks. We evaluate MedML on the National Cohort Collaborative (N3C) dataset. MedML achieves up to a 7% higher AUROC and 14% higher AUPRC compared to the best baseline machine learning models. MedML is a new machine learnig framework to incorporate clinical domain knowledge and is more predictive and explainable than current data-driven methods.

Respiratory Syncytial Virus During the COVID-19 Pandemic Compared to Historic Levels: A Retrospective Cohort Study of a Health System.

BackgroundSurveillance in 2020–2021 showed that seasonal respiratory illnesses were below levels seen during prior seasons, with the exception of interseasonal respiratory syncytial virus (RSV).MethodsElectronic health record data of infants aged <1 year visiting the Duke University Health System from 4 October 2015 to 28 March 2020 (pre–COVID-19) and 29 March 2020 to 30 October 2021 (COVID-19) were assessed. International Classification of Diseases-Tenth Revision (ICD-10) codes for RSV (B97.4, J12.1, J20.5, J21.0) and bronchiolitis (RSV codes plus J21.8, J21.9) were used to detail encounters in the inpatient (IP), emergency department (ED), outpatient (OP), urgent care (UC), and telemedicine (TM) settings.ResultsPre–COVID-19, 88% of RSV and 92% of bronchiolitis encounters were seen in ambulatory settings. During COVID-19, 94% and 93%, respectively, occurred in ambulatory settings. Pre–COVID-19, the highest RSV proportion was observed in December–January (up to 38% in ED), while the peaks during COVID-19 were seen in July–September (up to 41% in ED) across all settings. RSV laboratory testing among RSV encounters was low during pre–COVID-19 (IP, 51%; ED, 51%; OP, 41%; UC, 84%) and COVID-19 outside of UC (IP, 33%; ED, 47%; OP, 47%; UC, 87%). Full-term, otherwise healthy infants comprised most RSV encounters (pre–COVID-19, up to 57% in OP; COVID-19, up to 82% in TM).ConclusionsWith the interruption of historical RSV epidemiologic trends and the emergence of interseasonal disease during COVID-19, continued monitoring of RSV is warranted across all settings as the changing RSV epidemiology could affect the distribution of health care resources and public health policy.

Geographic Variations in Growth of Radiologists and Medicare Enrollees From 2012 to 2019

ObjectiveAnalyze changes in the number of Medicare-serving radiologists and Medicare enrollees nationwide and by geographic region and state from 2012 to 2019 to understand variations in allocation of imaging health care services over the past decade. MethodsThe number of radiologists submitting claims to Medicare was extracted from the CMS Physician and Other Supplier Public Use File Database. The number of Medicare enrollees by state was obtained from the Kaiser Family Foundation. National-, regional-, and state-level changes in rates of growth of radiologists, Medicare enrollees, and radiologists per 100,000 Medicare enrollees from 2012 to 2019 were tabulated. ResultsThe overall number of radiologists per 100,000 Medicare enrollees was 79.7 in 2012, increasing to 79.9 in 2019. In 2012, the number of radiologists per 100,000 enrollees was lower than the national average in the South (66.9; 16% lower) and Midwest (79.1; 0.7% lower) and higher in the Northeast (98.3; 23% higher) and West (88.8; 11% higher). In 2019, the number of radiologists per 100,000 enrollees was lower than the national average in the South (69.8; 12% lower) only and was higher in the Midwest (81.4; 1.9% higher), Northeast (99.3; 24% higher), and West (80.2; 0.4% higher). By state, there was a 4.2-fold variation in the number of radiologists per 100,000 Medicare enrollees, ranging from 38.8 in Wyoming to 161.4 in Minnesota (200.5 in Washington, DC). DiscussionThe growth of Medicare-serving radiologists and Medicare enrollees was stable nationally and demonstrated tremendous variations by US region and state. These variations bring to light potential implications for patient access to care and distribution of health care resources.

Against Futility Judgments for Patients with Prolonged Disorders of Consciousness

Against Futility Judgments for Patients with Prolonged Disorders of Consciousness

Telemedicine Is Becoming an Increasingly Popular Way to Resolve the Unequal Distribution of Healthcare Resources: Evidence From China.

BackgroundFew studies focused on the general situation of telemedicine in China.ObjectivesThe purpose of this review is to investigate telemedicine in China, from the aspects of necessity, history, scale, and operation procedure, to improve the further development and implementation of telemedicine service.MethodsA literature search for peer-reviewed studies was conducted using the primary electronic databases. Additional documents from the official websites of Chinese government departments involved telemedicine was also collected. We extracted telemedicine related information focused on China from the final retrieved materials, and the general situation of telemedicine was drawn.ResultsIn China, telemedicine offers a feasible solution to the unequal allocation of healthcare resources, which makes telemedicine increasingly become an important alternative to close the gap between rural and urban in the capability and quality of medical services. China initiated telemedicine in the late 1980s. In 2018, China's telemedicine network has covered more than 3,000 hospitals across the country. As of 2019, almost all of the 31 provinces and municipalities in mainland have established regional telemedicine centers, and the market size of telemedicine reached about USD 2.68 billion. Based on the telemedicine network, remote rural patients can apply for healthcare services of top-tier urban hospitals through local county-level medical institutions.ConclusionsThrough improving the capacity, quality, and efficiency of healthcare in underserved areas, and reducing the unequal distribution of medical resources, telemedicine can help solve the problems of the difficulty and high cost to access to medical services in China.

Screening is not always healthy: an ethical analysis of health screening packages in Singapore

BackgroundHealth screening is undertaken to identify individuals who are deemed at higher risk of disease for further diagnostic testing so that they may possibly benefit from interventions to modify the natural course of disease. In Singapore, screening tests are widely available in the form of a package, which bundles multiple tests in one session and commonly includes non-recommended tests. There are various ethical issues associated with such testing as they may not be clinically appropriate and can result in more harm than benefit. This article describes the practice of health screening packages, identifies the ethical issues arising from such packages and discusses the implications of these ethical issues on policy and practice of screening in Singapore.MethodsA content analysis of the websites of providers offering general health screening packages to individuals was conducted. A total of 14 health screening package providers were analysed for how packages were conducted and promoted, how clinically appropriate screening tests were, and the price range and composition of screening packages. A normative ethical analysis based on the four principles approach of beneficence, non-maleficence, autonomy and justice in biomedical ethics was used.ResultsTwelve of the 14 providers included non-recommended tests such as tumour markers, treadmill stress tests and MRI scans in their general health screening packages. Package prices ranged from S$26 to S$10,561, with providers charging higher when more tests were included. Health screening packages were broadly conducted in three stages: (1) the offer and selection of a health screening package; (2) medical assessment and performance of screening tests; (3) a post-screening review. While material provided by all providers was factual, there was no information on the potential risks or harms of screening.ConclusionSeveral ethical issues were identified that should be addressed with regard to health screening packages in Singapore. A key issue was the information gap between providers and patients, which may result in patients undergoing inappropriate testing that may be more harmful than beneficial. Health screening packages can stimulate unnecessary demand for healthcare and contribute to an inequitable distribution of healthcare resources.

Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review.

BackgroundDigital health technologies (ie, the integration of digital technology and health information) aim to increase the efficiency of health care delivery; they are rapidly adapting to health care contexts to provide improved medical services for citizens. However, contrary to expectations, their rapid adoption appears to have led to health inequities, with differences in health conditions or inequality in the distribution of health care resources among different populations.ObjectiveThis scoping review aims to identify and describe the inequities of health care services brought about by the adoption of digital health technologies. The factors influencing such inequities, as well as the corresponding countermeasures to ensure health equity among different groups of citizens, were also studied.MethodsPrimary studies and literature, including articles and reviews, published in English between 1990 and 2020 were retrieved using appropriate search strategies across the following three electronic databases: Clarivate Analytics’ Web of Science, PubMed, and Scopus. Data management was performed by two authors (RY and WZ) using Thomson Endnote (Clarivate Analytics, Inc), by systematically screening and identifying eligible articles for this study. Any conflicts of opinion were resolved through discussions with the corresponding author. A qualitative descriptive synthesis was performed to determine the outcomes of this scoping review.ResultsA total of 2325 studies were collected during the search process, of which 41 (1.76%) papers were identified for further analysis. The quantity of literature increased until 2016, with a peak in 2020. The United States, the United Kingdom, and Norway ranked among the top 3 countries for publication output. Health inequities caused by the adoption of digital health technologies in health care services can be reflected in the following two dimensions: the inability of citizens to obtain and adopt technology and the different disease outcomes found among citizens under technical intervention measures. The factors that influenced inequities included age, race, region, economy, and education level, together with health conditions and eHealth literacy. Finally, action can be taken to alleviate inequities in the future by government agencies and medical institutions (eg, establishing national health insurance), digital health technology providers (eg, designing high-quality tools), and health care service recipients (eg, developing skills to access digital technologies).ConclusionsThe application of digital health technologies in health care services has caused inequities to some extent. However, existing research has certain limitations. The findings provide a comprehensive starting point for future research, allowing for further investigation into how digital health technologies may influence the unequal distribution of health care services. The interaction between individual subjective factors as well as social support and influencing factors should be included in future studies. Specifically, access to and availability of digital health technologies for socially disadvantaged groups should be of paramount importance.

Racial-Ethnic Residential Clustering and Early COVID-19 Vaccine Allocations in Five Urban Texas Counties.

Previous research has indicated that racial-ethnic minority communities lack a wide variety of health-related organizations. We examine how this relates to the early COVID-19 vaccine rollout. In a series of spatial error and linear growth models, we analyze how racial-ethnic residential segregation is associated with the distribution of vaccine sites and vaccine doses across ZIP codes in the five largest urban counties in Texas. We find that Black and Latino clustered ZIP codes are less likely to have vaccine distribution sites and that this disparity is partially explained by the lack of hospitals and physicians' offices in these areas. Moreover, Black clustering is also negatively related to the number of allocated vaccine doses, and again, this is largely explained by the unequal distribution of health care resources. These results suggest that extant disparities in service provision are key to understanding racial-ethnic inequality in an acute crisis like the COVID-19 pandemic.

Area-based inequalities and distribution of healthcare resources for managing diabetes in South Korea: a cross-sectional multilevel analysis

ObjectivesWe aimed to identify area-based socioeconomic inequalities in diabetes management and to examine whether the distribution of healthcare resources could explain area-based inequalities in diabetes management.DesignCross-sectional multilevel analysis from national...

COVID-19 Pandemic- Ethical Challenges for Healthcare Workers Practicing in Resource-Limited Settings.

In this review, the ethical issues peculiar to the COVID-19 pandemics and the role of healthcare workers, especially those in resource-limited settings are x-rayed. We contend that there is a pressing ethical issue that needs urgent clarification on the rights and responsibilities of healthcare workers, especially in the current context of COVID-19 pandemic preparedness and responsiveness. We searched MEDLINE, Web of Science, EMBASE, Google Scholar, PUBMED related articles, newspaper articles, and online news sources for relevant information. The various professional codes of conduct (World Medical Association, Medical and Dental Council of Nigeria) were also consulted. The ethical principles of equitable distribution of healthcare resources, confidentiality with associated stigmatization, issues relating to duty to care by the healthcare workers and those pertaining to conduct of clinical trials and access to approved therapies or vaccines were highlighted in this study. We agree with the submission that healthcare workers only have a moral duty to treat patients with COVID-19 if the necessary protective equipment and adequate compensation are not provided. We argue that the duty of physicians and other healthcare workers to care for patients during pandemics such as COVID-19 is obligatory in the absence of required protective equipment and other forms of compensation. There is a need for the government and other stakeholders to put in place a National Pandemic /Epidemic Ethical Framework to address these identified ethical challenges.

Decision Engineering in Healthcare: How Medical Professionals Prioritize Resource Distribution

The equitable distribution of healthcare resources remains a pressing challenge across diverse healthcare systems globally. This study aims to explore the decision-making processes employed by medical professionals in the allocation of healthcare resources, emphasizing the ethical, technological, and management dimensions that influence these decisions. A qualitative research approach was employed, utilizing semi-structured interviews to collect data from a diverse group of 27 medical professionals, including physicians, nurses, and hospital administrators. Interviews were conducted until theoretical saturation was reached, ensuring a comprehensive exploration of decision-making processes. The data were analyzed using thematic analysis to identify recurring themes and patterns. Three main themes were identified: Ethical Considerations, Technology in Decision Making, and Resource Management. These encompassed several categories: under Ethical Considerations, Patient Equity, Decision Transparency, Ethical Dilemmas, and Prioritization Criteria were discussed; Technology in Decision Making included Data Utilization, Decision Support Systems, and Integration Challenges; Resource Management covered Allocation Efficiency, Resource Distribution Challenges, Impact on Patient Care, and Human Factors. Each category highlighted specific issues and strategies relevant to healthcare resource distribution. The study highlights the complex interplay of ethical dilemmas, technological advancements, and practical resource management challenges in healthcare decision-making. It underscores the need for an integrated approach that addresses these dimensions to improve the equity and efficiency of resource distribution in healthcare settings.