POINT: Is Considering Social Determinants of Health Ethically Permissible for Fair Allocation of Critical Care Resources During the COVID-19 Pandemic? Yes.
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ABSTRACT:
SUBMITTER: White DB
PROVIDER: S-EPMC9257161 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
Publications
POINT: Is Considering Social Determinants of Health Ethically Permissible for Fair Allocation of Critical Care Resources During the COVID-19 Pandemic? Yes.
White Douglas B DB Lo Bernard B Peek Monica E ME
Chest 20220701 1
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Project description: Not available
| S-EPMC9257123 | biostudies-literature
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.
| S-EPMC7873904 | biostudies-literature
Project description:A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.
| S-EPMC10444857 | biostudies-literature
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.
| S-EPMC9261249 | biostudies-literature
Project description:Background: The optimal allocation of limited donated hearts to patients on the waiting list is one of the top priorities in heart transplantation management. We developed a simulation model of the US waiting list for heart transplantation to investigate the potential impacts of allocation policies on several outcomes such as pre- and posttransplant mortality. Methods: We used data from the United Network for Organ Sharing (UNOS) and the Scientific Registry of Transplant Recipient (SRTR) to simulate the heart allocation system. The model is validated by comparing the outcomes of the simulation with historical data. We also adapted fairness schemes studied in welfare economics to provide a framework to assess the fairness of allocation policies for transplantation. We considered three allocation policies, each a modification to the current UNOS allocation policy, and analyzed their performance via simulation. The first policy broadens the geographical allocation zones, the second modifies the health status order for receiving hearts, and the third prioritizes patients according to their waiting time. Results: Our results showed that the allocation policy similar to the current UNOS practice except that it aggregates the three immediate geographical allocation zones, improves the health outcomes, and is "closer" to an optimal fair policy compared to all other policies considered in this study. Specifically, this policy could have saved 319 total deaths (out of 3738 deaths) during the 2006 to 2014 time horizon, in average. This policy slightly differs from the current UNOS allocation policy and allows for easy implementation. Conclusion: We developed a model to compare the outcomes of heart allocation policies. Combining the three immediate geographical zones in the current allocation algorithm could potentially reduce mortality rate and is closer to an optimal fair policy.
| S-EPMC6125046 | biostudies-literature
Project description:Effective management of radio resources and service quality assurance are two of the essential aspects to furnish high-quality service in Long Term Evolution (LTE) networks. Despite the base station involving several ingenious scheduling schemes for resource allocation, the intended outcome might be influenced by the interference, especially in heterogeneous scenarios, where many kinds of small cells can be deployed under the coverage of macrocell area. To develop the network of small cells, it is essential to take into account such boundaries, in particular, mobility, interference and resources scheduling a strategy which assist getting a higher spectral efficiency in anticipate small cells. Another challenge with small cellular network deployment is further analyzing the impact of power control techniques in the uplink direction for the network performance. With that being said, this article investigates the problem of interference in LTE-advanced heterogeneous networks. The proposed scheme allows mitigation inter-cell interference through fractional self-powered control performed at each femtocell user. This study analyzes a scheme with optimum power value that provides a compromise between the served uplink signal within unwanted interference plus noise ratio to enhance spectral efficiency in terms of throughput. In particular, the maximum transmit power for user equipment in uplink direction should be reviewed for small cells as a major contributor to the interference. The simulation results showed that the proposed fractional power control approach can outperform the traditional power control employed as a full compensation mode in small cell uplinks.
| S-EPMC8216560 | biostudies-literature
Project description:ObjectivesTo assess hospitals' plans for implementing Minnesota's statewide guidance for allocating scarce critical care resources during the COVID-19 pandemic.Patients and methodsIndividuals from 23 hospitals across Minnesota were invited to complete a 25-item survey between July 20, 2020, and September 18, 2020 to understand how hospitals in the state intended to operationalize statewide clinical triage instructions for scarce resources (including mechanical ventilation) and written ethics guidance on the allocation of critical care resources in the event crisis standards of care triggered triage.ResultsOf individuals invited from 23 hospitals, 14 hospitals completed the survey (60.9% institutional response rate) and described plans for triage at their respective hospitals. Planned triage team composition and size varied. Hospitals' plans for which individuals should assign a triage score (reflecting patients' illness severity) also differed markedly. Most respondents described plans for staff training to address potential bias in triage.ConclusionDespite explicit state guidance to encourage consistency across hospitals, we found considerable heterogeneity in implementation plans. Plans diverged from Minnesota's written ethics guidance on whether to consider race during triage to help mitigate health disparities. Inconsistencies between the state's 2 guidance documents could explain some of these differences. Collaboration between hospitals and committees developing statewide guidance may help identify barriers to effective operationalization. Ongoing review of published guidance and hospital plans can identify issues of clarity and consistency and promote equitable triage.
| S-EPMC11612654 | biostudies-literature
Project description:The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR-bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability, and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability, and Technology (TRUST). The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility, and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.
| S-EPMC10705436 | biostudies-literature
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.
| S-EPMC6849208 | biostudies-literature
Project description:Nutrient intake is often measured with substantial error both in commonly used surrogate instruments such as a food frequency questionnaire (FFQ) and in gold standard-type instruments such as a diet record (DR). If there is a correlated error between the FFQ and DR, then standard measurement error correction methods based on regression calibration can produce biased estimates of the regression coefficient (?) of true intake on surrogate intake. However, if a biomarker exists and the error in the biomarker is independent of the error in the FFQ and DR, then the method of triads can be used to obtain unbiased estimates of ?, provided that there are replicate biomarker data on at least a subsample of validation study subjects. Because biomarker measurements are expensive, for a fixed budget, one can use a either design where a large number of subjects have one biomarker measure and only a small subsample is replicated or a design that has a smaller number of subjects and has most or all subjects validated. The purpose of this paper is to optimize the proportion of subjects with replicated biomarker measures, where optimization is with respect to minimizing the variance of ln(??). The methodology is illustrated using vitamin C intake data from the European Prospective Investigation into Cancer and Nutrition study where plasma vitamin C is the biomarker. In this example, the optimal validation study design is to have 21% of subjects with replicated biomarker measures.
| S-EPMC4268307 | biostudies-literature