Project description:The allocation strategies during challenging situations among the different social groups is based on 9 principles which can be considered either individually: sickest first, waiting list, prognosis, youngest first, instrumental values, lottery, monetary contribution, reciprocity, and individual behavior, or in combination; youngest first and prognosis, for example. In this study, we aim to look into the most important prioritization principles amongst different groups in the Jordanian population, in order to facilitate the decision-making process for any potential medical crisis. We conducted an online survey that tackled how individuals would deal with three different scenarios of medical scarcity: (1) organ donation, (2) limited hospital beds during an influenza epidemic, and (3) allocation of novel therapeutics for lung cancer. In addition, a free-comment option was included at the end of the survey if respondents wished to contribute further. Seven hundred and fifty-four survey responses were gathered, including 372 males (49.3%), and 382 females (50.7%). Five groups of individuals were represented including religion scholars, physicians, medical students, allied health practitioners, and lay people. Of the five surveyed groups, four found "sickest-first" to be the most important prioritization principle in all three scenarios, and only the physicians group documented a disagreement. In the first scenario, physicians regarded "sickest-first" and "combined-criteria" to be of equal importance. In general, no differences were documented between the examined groups in comparison with lay people in the preference of options in all three scenarios; however, physicians were more likely to choose "combination" in both the second and third scenarios (OR 3.70, 95% CI 1.62-8.44, and 2.62, 95% CI 1.48-4.59; p < 0.01), and were less likely to choose "sickest-first" as the single most important prioritization principle (OR 0.57, CI 0.37-0.88, and 0.57; 95% CI 0.36-0.88; p < 0.01). Out of 100 free comments, 27 (27.0%) thought that the "social-value" of patients should also be considered, adding the 10th potential allocation principle. Our findings are concordant with literature in terms of allocating scarce medical resources. However, "social-value" appeared as an important principle that should be addressed when prioritizing scarce medical resources in Jordan.

Project description:BackgroundThe coronavirus 2019 pandemic placed unprecedented pressures on healthcare services and magnified ethical dilemmas related to how resources should be allocated. These resources include, among others, personal protective equipment, personnel, life-saving equipment, and vaccines. Decision-makers have therefore sought ethical decision-making tools so that resources are distributed both swiftly and equitably. To support the development of such a decision-making tool, a systematic review of the literature on relevant ethical values and principles was undertaken. The aim of this review was to identify ethical values and principles in the literature which relate to the equitable allocation of resources in response to an acute public health threat, such as a pandemic.MethodsA rapid systematic review was conducted using MEDLINE, EMBASE, Google Scholar, LitCOVID and relevant reference lists. The time period of the search was January 2000 to 6th April 2020, and the search was restricted to human studies. January 2000 was selected as a start date as the aim was to capture ethical values and principles within acute public health threat situations. No restrictions were made with regard to language. Ethical values and principles were extracted and examined thematically.ResultsA total of 1,618 articles were identified. After screening and application of eligibility criteria, 169 papers were included in the thematic synthesis. The most commonly mentioned ethical values and principles were: Equity, reciprocity, transparency, justice, duty to care, liberty, utility, stewardship, trust and proportionality. In some cases, ethical principles were conflicting, for example, Protection of the Public from Harm and Liberty.ConclusionsAllocation of resources in response to acute public health threats is challenging and must be simultaneously guided by many ethical principles and values. Ethical decision-making strategies and the prioritisation of different principles and values needs to be discussed with the public in order to prepare for future public health threats. An evidence-based tool to guide decision-makers in making difficult decisions is required. The equitable allocation of resources in response to an acute public health threat is challenging, and many ethical principles may be applied simultaneously. An evidence-based tool to support difficult decisions would be helpful to guide decision-makers.

Project description:BACKGROUND:Health resources are limited, which means spending should be focused on the people, places and programs that matter most. Choosing the mix of programs to maximize a health outcome is termed allocative efficiency. Here, we extend the methodology of allocative efficiency to answer the question of how resources should be distributed among different geographic regions. METHODS:We describe a novel geographical optimization algorithm, which has been implemented as an extension to the Optima HIV model. This algorithm identifies an optimal funding of services and programs across regions, such as multiple countries or multiple districts within a country. The algorithm consists of three steps: (1) calibrating the model to each region, (2) determining the optimal allocation for each region across a range of different budget levels, and (3) finding the budget level in each region that minimizes the outcome (such as reducing new HIV infections and/or HIV-related deaths), subject to the constraint of fixed total budget across all regions. As a case study, we applied this method to determine an illustrative allocation of HIV program funding across three representative oblasts (regions) in Ukraine (Mykolayiv, Poltava, and Zhytomyr) to minimize the number of new HIV infections. RESULTS:Geographical optimization was found to identify solutions with better outcomes than would be possible by considering region-specific allocations alone. In the case of Ukraine, prior to optimization (i.e. with status quo spending), a total of 244,000 HIV-related disability-adjusted life years (DALYs) were estimated to occur from 2016 to 2030 across the three oblasts. With optimization within (but not between) oblasts, this was estimated to be reduced to 181,000. With geographical optimization (i.e., allowing reallocation of funds between oblasts), this was estimated to be further reduced to 173,000. CONCLUSIONS:With the increasing availability of region- and even facility-level data, geographical optimization is likely to play an increasingly important role in health economic decision making. Although the largest gains are typically due to reallocating resources to the most effective interventions, especially treatment, further gains can be achieved by optimally reallocating resources between regions. Finally, the methods described here are not restricted to geographical optimization, and can be applied to other problems where competing resources need to be allocated with constraints, such as between diseases.

Project description:BackgroundThis study aimed to investigate the distribution of European Union (EU) healthcare research grants across EU countries, and to study the effect of the potential influencing factors on grant allocation.MethodsWe analysed publicly available data on healthcare research grants from the 7th Framework Programme and the Horizon 2020 Programme allocated to beneficiaries between 2007 and 2016. Grant allocation was analysed at the beneficiary-, country-, and country group-level (EU-15 versus newer Member States, defined as EU-13). The investigated country-level explanatory variables included GDP per capita, population size, overall disease burden, and healthcare research excellence. Grant amounts per 100,000 inhabitants were used as an outcome variable in the regression analyses.ResultsResearch funds were disproportionally allocated to EU-15 versus the EU-13, as 96.9% of total healthcare grants were assigned to EU-15 countries. At the beneficiary level, EU funding was positively influenced by participating in previous grants. The average grant amount per beneficiary was higher for EU-15 organizations. In the multiple regression analysis GDP per capita (p = 0.002) and research excellence (p<0.001) had a significant positive association with EU funding. Population size had an inverted U-shaped relationship with EU funding for healthcare research, having the largest per capita funding in second and the third quartiles (p = 0.03 and p = 0.02).ConclusionThe uneven allocation of healthcare research funds across EU countries was influenced by GDP per capita, medical research excellence and population size. Wealthier countries with an average population size and strong research excellence in healthcare had more EU funding for healthcare research. Higher disease burden apparently was not associated with more EU research funding. While our findings are in line with analyses on previous periods, they suggest that the EU did not implement any effective policy measures to improve the unfair allocation of research grants.

Dataset Information

POINT: Is Considering Social Determinants of Health Ethically Permissible for Fair Allocation of Critical Care Resources During the COVID-19 Pandemic? Yes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets