Personal responsibility for health in Bulgarian public health law and social legislation.

BACKGROUND: In the last decades all health systems have experienced a lack of resources. Against this background, the idea of ​​applying personal responsibility of the patient as a criterion for allocation of resources (PRCAR) is gaining increasing attention. Bulgarian healthcare reform has been marked by the implementation of many new strategies, that grounded our scientific interest towards investigating PRCAR in Bulgarian public health law and social legislation. METHODS: Through a search of national legal databases 7 documents were selected and subjected to content analysis. RESULTS: Prospective responsibility was found in two and retrospective responsibility - in three documents, two of which imposed explicit penalties on the patient. Two documents did not distinguish between the types of patient responsibility. PRCAR was found to be controversial through the prism of the social justice principle. The discussion was conducted through the perspectives of evidence translation of research to law, particularities of social cohesion in Bulgaria, and the interpretation of principles of public health ethics. CONCLUSION: Although PRCAR was traceable in Bulgarian legislation, no supporting arguments for its introduction were deduced. The applicability of PRCAR should be further studied and wider public debate should be initiated.

Spatial effects of township health centers' health resource allocation efficiency in China.

Introduction: China is a large agricultural nation with the majority of the population residing in rural areas. The allocation of health resources in rural areas significantly affects the basic rights to life and health for rural residents. Despite the progress made by the Chinese government in improving rural healthcare, there is still room for improvement. This study aims to assess the spatial spillover effects of rural health resource allocation efficiency in China, particularly focusing on township health centers (THCs), and examine the factors influencing this efficiency to provide recommendations to optimize the allocation of health resources in rural China. Methods: This study analyzed health resource allocation efficiency in Chinese rural areas from 2012 to 2021 by using the super-efficiency SBM model and the global Malmquist model. Additionally, the spatial auto-correlation of THC health resource allocation efficiency was verified through Moran test, and three spatial econometric models were constructed to further analyze the factors influencing efficiency. Results: The key findings are: firstly, the average efficiency of health resource allocation in THCs was 0.676, suggesting a generally inefficient allocation of health resources over the decade. Secondly, the average Malmquist productivity index of THCs was 0.968, indicating a downward trend in efficiency with both non-scale and non-technical efficient features. Thirdly, Moran's Index analysis revealed that efficiency has a significant spatial auto-correlation and most provinces' values are located in the spatial agglomeration quadrant. Fourthly, the SDM model identified several factors that impact THC health resource allocation efficiency to varying degrees, including the efficiency of total health resource allocation, population density, PGDP, urban unemployment rate, per capita disposable income, per capita healthcare expenditure ratio, public health budget, and passenger traffic volume. Discussion: To enhance the efficiency of THC healthcare resource allocation in China, the government should not only manage the investment of health resources to align with the actual demand for health services but also make use of the spatial spillover effect of efficiency. This involves focusing on factors such as total healthcare resource allocation efficiency, population density, etc. to effectively enhance the efficiency of health resource allocation and ensure the health of rural residents.

Equity and efficiency of health resource allocation in the Chengdu-Chongqing Economic Circle of China.

Objective: This study aimed to evaluate the fairness and efficiency of health resource allocation (HRAE) in Chengdu-Chongqing Economic Circle after the new healthcare reform. This study also aimed to identify existing problems, providing empirical evidence for the government to formulate regional health plans scientifically and reasonably. Methods: The fairness of health resource allocation was analyzed using the Gini coefficient, Theil index, and agglomeration degree from population and geographical area perspectives. The three-stage data envelopment analysis and the Malmquist productivity index were used to analyze HRAE from static and dynamic perspectives. Results: The Gini coefficient for population allocation in Chengdu-Chongqing Economic Circle was 0.066-0.283, and the Gini coefficient for geographical area allocation was 0.297-0.469. The contribution rate within a region was greater than that between regions, and health resources were mainly concentrated in economically developed core areas. The overall fairness of Chengdu Economic Circle was relatively better than that of Chongqing Economic Circle. Moreover, the adjusted mean technical efficiency was 0.806, indicating room for HRAE improvement in Chengdu-Chongqing Economic Circle. Stochastic Frontier Analysis found that different environmental variables have varying degrees of impact on HRAE. The adjusted mean total factor productivity change (Tfpch) was 1.027, indicating an overall upward trend in HRAE since the new healthcare reform. However, scale efficiency change (Sech) (0.997) limited the improvement of Tfpch. Conclusion: The fairness of health resources allocated by population was better than that allocated by geographical area. The unfairness of health resources mainly stemmed from intra-regional differences, with considerable health resources concentrated in core areas. Over the past 13 years, HRAE has improved but exhibited spatial heterogeneity and Sech-hindered productivity improvement. The study recommends strengthening regional cooperation and sharing to promote the integrated and high-quality development of the health and well-being in Chengdu-Chongqing Economic Circle.

Health resource allocation within the close-knit medical consortium after the Luohu healthcare reform in China: efficiency, productivity, and influencing factors.

Objective: This study aims to assess the efficiency and productivity of the Luohu Hospital Group after the reform and to identify factors influencing the efficiency to support the future development of medical consortia. Methods: Data on health resources from Shenzhen and the Luohu Hospital Group for the years 2015 to 2021 were analyzed using the super-efficiency slack-based measure data envelopment analysis (SE-SBM-DEA) model, Malmquist productivity index (MPI), and Tobit regression to evaluate changes in efficiency and productivity and to identify determinants of efficiency post-reform. Results: After the reform, the efficiency of health resource allocation within the Luohu Hospital Group improved by 33.87%. Community health centers (CHCs) within the group had an average efficiency score of 1.046. Moreover, the Luohu Hospital Group's average total factor productivity change (TFPCH) increased by 2.5%, primarily due to gains in technical efficiency change (EFFCH), which offset declines in technical progress change (TECHCH). The efficiency scores of CHCs were notably affected by the ratio of general practitioners (GPs) to health technicians and the availability of home hospital beds. Conclusion: The reform in the Luohu healthcare system has shown preliminary success, but continuous monitoring is necessary. Future strategies should focus on strengthening technological innovation, training GPs, and implementing the home hospital bed policy. These efforts will optimize the efficiency of health resource allocation and support the integration and development of resources within the medical consortium.

A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

Importance: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (PLTs), to optimize the distribution of scarce therapeutics. Objective: To evaluate whether a machine learning PLT-based method of scarce resource allocation optimizes the treatment benefit of COVID-19 neutralizing monoclonal antibodies (mAbs) during periods of resource constraint. Design, Setting, and Participants: This retrospective cohort study used electronic health record data from October 1, 2021, to December 11, 2021, for the training cohort and data from June 1, 2021, to October 1, 2021, for the testing cohort. The cohorts included patients who had positive test results for SARS-CoV-2 and qualified for COVID-19 mAb therapy based on the US Food and Drug Administration's emergency use authorization criteria, ascertained from the patient electronic health record. Only some of the qualifying candidates received treatment with mAbs. Data were analyzed between from January 2023 to May 2024. Main Outcomes and Measures: The primary outcome was overall expected hospitalization, assessed as the potential reduction in overall expected hospitalization if the PLT-based allocation system was used. This was compared to observed allocation using risk differences. Results: Among 9542 eligible patients in the training cohort (5418 female [56.8%]; age distribution: 18-44 years, 4151 [43.5%]; 45-64 years, 3146 [33.0%]; and ≥65 years, 2245 [23.5%]), a total of 3862 (40.5%) received mAbs. Among 6248 eligible patients in the testing cohort (3416 female [54.7%]; age distribution: 18-44 years, 2827 [45.2%]; 45-64 years, 1927 [30.8%]; and ≥65 years, 1494 [23.9%]), a total of 1329 (21.3%) received mAbs. Treatment allocation using the trained PLT model led to an estimated 1.6% reduction (95% CI, -2.0% to -1.2%) in overall expected hospitalization compared to observed treatment allocation in the testing cohort. The visual assessment showed that the PLT-based point system had a larger reduction in 28-day hospitalization compared with the Monoclonal Antibody Screening Score (maximum overall hospitalization difference, -1.0% [95% CI, -1.3% to -0.7%]) in the testing cohort. Conclusions and Relevance: This retrospective cohort study proposes and tests a PLT method, which can be linked to a electronic health record data platform to improve real-time allocation of scarce treatments. Use of this PLT-based allocation method would have likely resulted in fewer hospitalizations across a population than were observed in usual care, with greater expected reductions than a commonly used point system.

Investigating ethical tradeoffs in crisis standards of care through simulation of ventilator allocation protocols.

INTRODUCTION: Arguments over the appropriate Crisis Standards of Care (CSC) for public health emergencies often assume that there is a tradeoff between saving the most lives, saving the most life-years, and preventing racial disparities. However, these assumptions have rarely been explored empirically. To quantitatively characterize possible ethical tradeoffs, we aimed to simulate the implementation of five proposed CSC protocols for rationing ventilators in the context of the COVID-19 pandemic. METHODS: A Monte Carlo simulation was used to estimate the number of lives saved and life-years saved by implementing clinical acuity-, comorbidity- and age-based CSC protocols under different shortage conditions. This model was populated with patient data from 3707 adult admissions requiring ventilator support in a New York hospital system between April 2020 and May 2021. To estimate lives and life-years saved by each protocol, we determined survival to discharge and estimated remaining life expectancy for each admission. RESULTS: The simulation demonstrated stronger performance for age-sensitive protocols. For a capacity of 1 bed per 2 patients, ranking by age bands saves approximately 29 lives and 3400 life-years per thousand patients. Proposed protocols from New York and Maryland which allocated without considering age saved the fewest lives (~13.2 and 8.5 lives) and life-years (~416 and 420 years). Unlike other protocols, the New York and Maryland algorithms did not generate significant disparities in lives saved and life-years saved between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations. For all protocols, we observed a positive correlation between lives saved and life-years saved, but also between lives saved overall and inequality in the number of lives saved in different race and ethnicity sub-populations. CONCLUSION: While there is significant variance in the number of lives saved and life-years saved, we did not find a tradeoff between saving the most lives and saving the most life-years. Moreover, concerns about racial discrimination in triage protocols require thinking carefully about the tradeoff between enforcing equality of survival rates and maximizing the lives saved in each sub-population.

[Intensive care and priority setting during catastrophe or war]. / Intensivvård och prioriteringar i fredstida katastrofer och krig.

In this article we discuss some ethically and legally controversial issues in the Swedish priority guidelines for intensive care during the recent covid pandemic. We show how the Swedish ethics platform for priority setting constitutes a robust starting point for such guidance, but that there is a lack of detail leaving some of the more challenging situations without explicit guidance. To provide guidance, which we have reason to do in order to avoid inequality and arbitrariness, we should try to interpret the ethics platform, based on how it is applied in practice together with ethical reasoning. In this article, we illustrate this by focusing on contested guidance concerning biological age when distributing scarce intensive care beds. We conclude that biological age should be interpreted in terms of long-term survival. We also conclude that the ethical platform does not provide guidance in these challenging situations, but needs interpretation. Therefore, there is a need of a legal overview of the principles in order to create an even stronger basis for support in the future.

Patients' perspectives on ethical principles to fairly allocate scarce surgical resources during the COVID-19 pandemic in the Netherlands: a Q-methodology study.

OBJECTIVES: During the COVID-19 pandemic, healthcare professionals were faced with prioritisation dilemmas due to limited surgical capacity. While the views of healthcare professionals on fair allocation have been given considerable attention, the views of patients have been overlooked. To address this imbalance, our study aimed to identify which ethical principles are most supported by patients regarding the fair allocation of surgical resources. DESIGN: A Q-methodology study was conducted. Participants ranked ordered 20 statements covering different viewpoints on fair allocation according to their point of view, followed by an interview. Principal component analysis followed by varimax rotation was used to identify subgroups who broadly agreed in terms of their rankings. SETTING: The setting of this study was in the Netherlands. PARTICIPANTS: 16 patient representatives were purposively sampled. RESULTS: Two perspectives were identified, both of which supported utilitarianism. In perspective 1, labelled as 'clinical needs and outcomes', resource allocation should aim to maximise the health gains based on individual patient characteristics. In perspective 2, labelled as 'population outcomes and contribution to society', allocation should maximise health gains as with perspective 1, but this should also consider societal gains. CONCLUSIONS: There was a broad agreement among patient representatives that utilitarianism should be the guiding ethical principle for fair allocation of scarce surgical resources. The insights gained from this study should be integrated into policymaking and prioritisation strategies in future healthcare crises.

The analysis of GM (1, 1) grey model to predict the health resource allocation in Jilin Province, China: An observational study.

To predict the development of health resource allocation in Jilin Province during the 14th 5-Year Plan period, and to provide a scientific basis for promoting the improvement of its service capacity. The data of the health resource from 2015 to 2022 were obtained from the Jilin Statistical Yearbook, and the number of medical institutions, medical beds, health technicians, licensed (assistant) physicians, registered nurses and pharmacists were selected as evaluation indicators, and the grey prediction model constructed by Python was used to predict the development from 2023 to 2025. In the 14th 5-Year Plan period, the health resource in Jilin Province showed an increasing trend, and it is predicted that in 2025, the number of medical institutions, medical beds, health technicians, licensed (assistant) physicians, registered nurses, and pharmacists in Jilin Province will reach 28,999, 196,328, 262,219, 101,273, 129,586, and 9469, respectively. Except that the pharmacist team failed to meet the planning objectives of the 14th 5-Year Plan, the remaining health resources could meet the planning requirements. The allocation level of health resources in Jilin Province has been continuously improved, but it still faces the problems that the allocation of medical beds needs to be optimized, the doctor-nurse ratio needs to be improved, the reserve of registered nurses is insufficient, there is a gap in the pharmacist team, and the development of pharmacy services is slow.

Operationalisation of health equity principles in physiotherapy hospital triage policies.

BACKGROUND: Healthcare triage policies are vital for allocating limited resources fairly and equitably. Despite extensive studies of healthcare equity, consensus on the applied definition of equity in triage remains elusive. This study aimed to investigate how the principles of equity are operationalised in Australian hospital physiotherapy triage tools to guide resource distribution. METHODS: A retrospective, qualitative content analysis of 13 triage policies from 10 hospitals across Australia was conducted. Triage policies from both inpatient and outpatient settings were sourced. Data were coded deductively using the five discrete domains of the multi-faceted operational definition of health equity posited by Lane et al. (2017): 1) point of equalisation in the health service supply/access/outcome chain, 2) need or potential to benefit, 3) groupings of equalisation, 4) caveats to equalisation, 5) close enough is good enough. Descriptive summative statistics were used to analyse and present the frequency of reported equity domains. RESULTS: Within the included triage tools, four out of five domains of equity were evident in the included documents to guide decision making. Allocation based on perceived patient need and overall health outcomes were the central guiding principles across both inpatient and outpatient settings. Equal provision of service relative to patient need and reducing wait times were also prioritised. However, explicit inclusion of certain equity domains such as discrimination, ensuring equal capability to be healthy and other patient factors was limited. CONCLUSIONS: Physiotherapy triage policies consider various domains of equity to guide resource allocation decisions. Policymakers and service providers can use the insights gained from this study to review the application and operationalisation of equity principles within their healthcare systems through mechanisms such as patient triage tools.

Research on the coupling measurement of medical education and health resource allocation under the background of healthy China.

OBJECTIVE: To analyze the coupling and coordination level of medical education and health resource allocation in China, and to provide scientific basis for promoting the high-quality development of medical education and the efficient allocation of health resources. METHODS: Based on the panel data from 2011 to 2021, the coupling coordination degree model was used to measure the coupling coordination index of medical education and health resources in China. The spatial auto-correlation model was used to analyze the development status and distribution characteristics of the coupling coordination degree of the two systems. The kernel density estimation method was used to analyze the dynamic evolution trend of the coupling coordination of the two systems. The QR quantile regression model was used to explore the key factors affecting the coupling coordination degree of the two systems. RESULTS: During the observation period, the coupling coordination degree of the two systems increased from 0.393 to 0.465, with a growth rate of 18.3%. The coupling coordination degree between regions gradually decreased in the eastern-central and eastern-western regions, and there were still large differences between the central and western regions. The coupling coordination degree of the two systems in the region was significantly different in the eastern and western regions, and the central region was relatively similar. There is a positive spatial correlation between the provinces, and 25.81% of the provinces have transitions. Finally, the number of points in the first and third quadrants is higher than that in the second and fourth quadrants. In the process of dynamic distribution, the degree of polarization of the coupling coordination degree curve of the two systems is gradually weakened. Per capita GDP, residents ' income difference and population size are the positive and significant factors driving the coupling and coordinated development of the two systems. CONCLUSION: The coupling and coordination degree of the two systems of medical education and health resource allocation showed a stable upward trend during the observation period, and the global spatial positive correlation also gradually increased, showing the spatial agglomeration characteristics of ' high-high agglomeration ' and ' low-low agglomeration '. The spatial difference of coupling coordination degree shows a shrinking trend and develops towards equalization. The coupling coordination degree of the two systems is affected by social, economic and demographic factors to varying degrees. Therefore, it is necessary to innovate the coordinated development mechanism of the two systems, promote the two-way flow of medical education and health resource allocation in talents, technology and other elements, and then promote the coupling and coordinated development of the two systems.

Atenção primária e informação em saúde: desempenho e financiamento no município de Natal/rn / Primary Care and Health Information: Performace and finance in the municipality Natal/RN / Atención Primaria e Información en Salud: Desempenõ y financiamiento en elmunicipio de Natal/RN

Introdução: O país adotou, com a criação do Programa Previne Brasil, uma nova forma de financiamento da Atenção Primária à Saúde, com a portaria ministerial 2.979/2019, a qual estabeleceu critérios para alocação de recursos, com foco para o desempenho e produtividade da Atenção Primária. Talmodelo vem sendo alvo de críticas pelo campo acadêmico da Saúde Coletiva e por gestões municipais, que em diferentes situações demonstram perdas financeiras, sobretudo, devido ao componente de capitação ponderada. Objetivo: Sistematizar o desempenho da Atenção Primária à Saúde do município de Natal, Rio Grande do Norte, com base em indicadores de desempenho do Sistema de Informação em Saúde para a Atenção Básica, e o financiamento da Atenção Primária, com base no Sistema de Informações sobre Orçamentos Públicos em Saúde, entre os anos 2019 a 2022. Metodologia: Trata-se de uma pesquisa descritiva-exploratória, com utilização de dados secundários e sistematização dos sete indicadores de desempenho da Atenção Primária e análise das despesas com saúdedo município de Natal. Resultados:Dos sete indicadores analisados, o município de Natal alcançou a meta em dois indicadores, referente à proporção de gestantes com pelo menos seis consultas pré-natal realizadas (46% em 2022) e com realização de exames para sífilis e HIV (67% em 2022). O município destinou à Atenção Primária, em 2022, apenas 6,33% de todas suas despesas com saúde. Destaca-se, também, que a cobertura da Atenção Primária no município é de 60%, havendo ainda um vazio assistencial para grande parte da população natalense. Conclusões:A análise de indicadores de saúde, torna-se importante ferramenta para a ação avaliativa do Sistema Único de Saúde, bem como dá suporte para a tomada de decisão por parte de gestores e equipes de saúde, além de produzir conhecimento crítico para a qualificação da Atenção Primária à Saúde (AU).

Introduction:The country adopted, with the creation of the Previne Brasil Program, a new form of financing Primary Health Care, with ministerial decree 2.979/2019, which established criteria for resource allocation, focusing on the performance and productivity of Primary Care. This model has been criticized by the academic field of Public Health and by municipal administrations, which in different situations demonstrate financial losses, mainly due to the weighted capitation component. Objective:Systematize the performance of Primary Health Care in the city of Natal, Rio Grande do Norte, based on performance indicators from the Health Information System for Primary Care, and the financing of Primary Care, based on the Information System of Public Health Budgets, between the years 2019 and 2022. Methodology:This is descriptive-exploratory research, using secondary data and systematization of the seven Primary Care performance indicators and analysis of health expenses in the city of Natal. Results: Of the seven indicators analyzed, the municipality of Natal reached the target in two indicators, referring to the proportion of pregnant women with at least six prenatal consultations carried out (46% in 2022) and with tests for syphilis and HIV (67% in 2022). In 2022, the municipality allocated only 6.33% of all its health expenses to PrimaryCare. It is also noteworthy that Primary Care coverage in the municipality is 60%, with there still being a care gap for a large part of the population of Natal. Conclusions:The analysis of health indicators becomes an important tool for the evaluative action of the Unified Health System, as well as providing support for decision-making by managers and health teams, in addition to producing critical knowledge for the qualification of Primary Health Care (AU).

Introducción: El país adoptó, con la creación del Previne Brasil, una nueva forma de financiamiento de la Atención Primaria de Salud, con el decreto ministerial 2.979/2019, que estableció criterios para la asignación de recursos, con foco en el desempeño y productividad de la Atención Primaria. Este modelo ha sido criticado por el ámbito académico de la Salud Pública y por las administraciones municipales, que en diferentes situaciones demuestran pérdidas financieras, principalmente por el componente de capitación ponderada. Objetivo: Sistematizar el desempeño de la Atención Primaria de Salud en la ciudad de Natal, Rio Grande do Norte, con base en indicadores de desempeño del Sistema de Información en Salud para la Atención Primaria, y el su financiamiento, con base en el Sistema de Información Presupuestaria Pública en Salud, entre los años 2019 y 2022. Metodología: Se trata de una investigación descriptiva-exploratoria, utilizando datos secundarios y sistematización de siete indicadores de desempeño de la Atención Básica y análisis del gasto en salud. Resultados: De los siete indicadores analizados, el municipio de Natal alcanzó la meta en dos indicadores, referidos a la proporción de gestantes con al menos seis consultas prenatales realizadas (46% en 2022) y con pruebas de sífilis y HIV (67% en 2022). En 2022, el municipio destinó sólo el 6,33% de todos sus gastos sanitarios a la Atención Primaria. También se destaca que la cobertura de Atención Primaria en el municipio es del 60%, existiendo aún brecha de atención para gran parte de la población. Conclusiones: El análisis de indicadores de salud se convierte en herramienta importante para la acción de evaluación del Sistema Único de Salud, además de brindar apoyo para la toma de decisiones de gestores y equipos de salud, además de producir conocimiento crítico para la calificación de la Atención Primaria de Salud (AU).

Assessing the impact of vaccination and medical resource allocation on infectious disease outbreak management: a case study of COVID-19 in Taiyuan City.

Introduction: Amidst an emerging infectious disease outbreak, the rational allocation of vaccines and medical resources is crucial for controlling the epidemic's progression. Method: Analysing COVID-19 data in Taiyuan City from December 2022 to January 2023, this study constructed a S V 1 V 2 V 3 E I Q H R dynamics model to assess the impact of COVID-19 vaccination and resource allocation on epidemic trends. Results: Vaccination significantly reduces infection rates, hospitalisations, and severe cases, while also curtailing strain on medical resources by reducing congestion periods. An early and sufficient reserve of medical resources can delay the onset of medical congestion, and with increased maximum capacity of medical resources, the congestion's end can be accelerated. Stronger resource allocation capabilities lead to earlier congestion resolution within a fixed total resource pool. Discussion: Integrating vaccination and medical resource allocation can effectively reduce medical congestion duration and alleviate the epidemic's strain on medical resource capacity (CCMR).