Grouping Promotes Equality: The Effect of Recipient Grouping on Allocation of Limited Medical Resources.
Ontology highlight
ABSTRACT:
SUBMITTER: Colby H
PROVIDER: S-EPMC4504740 | biostudies-literature | 2015 Jul
REPOSITORIES: biostudies-literature
Publications
Grouping Promotes Equality: The Effect of Recipient Grouping on Allocation of Limited Medical Resources.
Colby Helen H DeWitt Jeff J Chapman Gretchen B GB
Psychological science 20150615 7
Decisions about allocation of scarce resources, such as transplant organs, often entail a trade-off between efficiency (i.e., maximizing the total benefit) and fairness (i.e., dividing resources equally). In three studies, we used a hypothetical scenario for transplant-organ allocation to examine allocation to groups versus individuals. Study 1 demonstrated that allocation to individuals is more efficient than allocation to groups. Study 2 identified a factor that triggers the use of fairness ov ...[more]
Similar Datasets
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:Attention can modulate neural responses in sensory cortical areas and improve behavioral performance in perceptual tasks. However, the nature and purpose of these modulations remain under debate. Here we used voltage-sensitive dye imaging (VSDI) to measure V1 population responses while monkeys performed a difficult detection task under focal or distributed attention. We found that V1 responses at attended locations are significantly elevated relative to actively ignored or irrelevant locations, consistent with the hypothesis that an important goal of attention in V1 is to highlight task-relevant information. Surprisingly, these modulations were indistinguishable under focal and distributed attention, suggesting a minor or no role for attention as a mechanism for allocating limited representational resources in V1. The response elevation at attended locations is additive, is widespread, and starts shortly before stimulus onset. This elevation could contribute to spatial gating by biasing competition in subsequent processing stages in favor of attended stimuli.
| S-EPMC3351693 | biostudies-literature
Project description:Objective. When medical resources are scarce, clinicians must make difficult triage decisions. When these decisions affect public trust and morale, as was the case during the COVID-19 pandemic, experts will benefit from knowing which triage metrics have citizen support. Design. We conducted an online survey in 20 countries, comparing support for 5 common metrics (prognosis, age, quality of life, past and future contribution as a health care worker) to a benchmark consisting of support for 2 no-triage mechanisms (first-come-first-served and random allocation). Results. We surveyed nationally representative samples of 1000 citizens in each of Brazil, France, Japan, and the United States and also self-selected samples from 20 countries (total N = 7599) obtained through a citizen science website (the Moral Machine). We computed the support for each metric by comparing its usability to the usability of the 2 no-triage mechanisms. We further analyzed the polarizing nature of each metric by considering its usability among participants who had a preference for no triage. In all countries, preferences were polarized, with the 2 largest groups preferring either no triage or extensive triage using all metrics. Prognosis was the least controversial metric. There was little support for giving priority to healthcare workers. Conclusions. It will be difficult to define triage guidelines that elicit public trust and approval. Given the importance of prognosis in triage protocols, it is reassuring that it is the least controversial metric. Experts will need to prepare strong arguments for other metrics if they wish to preserve public trust and morale during health crises.HighlightsWe collected citizen preferences regarding triage decisions about scarce medical resources from 20 countries.We find that citizen preferences are universally polarized.Citizens either prefer no triage (random allocation or first-come-first served) or extensive triage using all common triage metrics, with "prognosis" being the least controversial.Experts will need to prepare strong arguments to preserve or elicit public trust in triage decisions.
| S-EPMC9326829 | biostudies-literature
Project description:BackgroundWhenever vaccines for a new pandemic or widespread epidemic are developed, demand greatly exceeds the available supply of vaccine doses in the crucial, initial phases of vaccination. Rationing protocols must then fulfill a number of ethical principles balancing equal treatment of individuals and prioritization of at-risk and instrumental subpopulations. For COVID-19, actual rationing methods used a territory-based first allocation stage based on proportionality to population size, followed by locally-implemented prioritization rules. The results of this procedure have been argued to be ethically problematic.MethodsWe use a formal-analytical approach arising from the mathematical social sciences which allows to investigate whether any allocation methods (known or unknown) fulfill a combination of (ethical) desiderata and, if so, how they are formulated algorithmically.ResultsStrikingly, we find that there exists one and only one method that allows to treat people equally while giving priority to those who are worse off. We identify this method down to the algorithmic level and show that it is easily implementable and it exhibits additional, desirable properties. In contrast, we show that the procedures used during the COVID-19 pandemic violate both principles.ConclusionsOur research delivers an actual algorithm that is readily applicable and improves upon previous ones. Since our axiomatic approach shows that any other algorithm would either fail to treat people equally or fail to prioritize those who are worse off, we conclude that ethical principles dictate the adoption of this algorithm as a standard for the COVID-19 or any other comparable vaccination campaigns.
| S-EPMC9792380 | biostudies-literature
Project description:Objective: Given the ever-changing flow of obstetric patients in the hospital, how the government and hospital management plan and allocate medical resources has become an important problem that needs to be urgently solved. In this study a prediction method for calculating the monthly and daily flow of patients based on time series is proposed to provide decision support for government and hospital management. Methods: The historical patient flow data from the Department of Obstetrics and Gynecology of the First Hospital of Jilin University, China, from January 1, 2018, to February 29, 2020, were used as the training set. Seven models such as XGBoost, SVM, RF, and NNAR were used to predict the daily patient flow in the next 14 days. The HoltWinters model is then used to predict the monthly flow of patients over the next year. Results: The results of this analysis and prediction model showed that the obstetric inpatient flow was not a purely random process, and that patient flow was not only accompanied by the random patient flow but also showed a trend change and seasonal change rule. ACF,PACF,Ljung_box, and residual histogram were then used to verify the accuracy of the prediction model, and the results show that the Holtwiners model was optimal. R2, MAPE, and other indicators were used to measure the accuracy of the 14 day prediction model, and the results showed that HoltWinters and STL prediction models achieved high accuracy. Conclusion: In this paper, the time series model was used to analyze the trend and seasonal changes of obstetric patient flow and predict the patient flow in the next 14 days and 12 months. On this basis, combined with the trend and seasonal changes of obstetric patient flow, a more reasonable and fair horizontal allocation scheme of medical resources is proposed, combined with the prediction of patient flow.
| S-EPMC8562385 | biostudies-literature
Project description:BACKGROUND:In response to the development of highly effective but expensive new medications, policymakers, payors, and health systems are considering novel and pragmatic ways to provide these medications to patients. One approach is to target these treatments to those most likely to benefit. However, to maximize the fairness of these policies, and the acceptance of their implementation, the values and beliefs of patients should be considered. The provision of treatments for chronic hepatitis C (CHC) in the resource-constrained context of the Veterans Health Administration (VHA) offered a real-world example of this situation, providing the opportunity to test the value of using Democratic Deliberation (DD) methods to solicit the informed opinions of laypeople on this complex issue. METHODS:We recruited Veterans (n?=?30) from the VHA to attend a DD session. Following educational presentations from content experts, participants engaged in facilitated small group discussions to: 1) identify strategies to overcome CHC treatment barriers and 2) evaluate, vote on, and modify/improve two CHC treatment policies - "first come, first served" (FCFS) and "sickest first" (SF). We used transcripts and facilitators' notes to identify key themes from the small group discussions. Additionally, participants completed pre- and post-DD surveys. RESULTS:Most participants endorsed the SF policy over the FCFS policy, emphasizing the ethical and medical appropriateness of treating the sickest first. Concerns about SF centered on the difficulty of implementation (e.g., how is "sickest" determined?) and unfairness to other Veterans. Proposed modifications focused on: 1) the need to consider additional health factors, 2) taking behavior and lifestyle into account, 3) offering education and support, 4) improving access, and 5) facilitating better decision-making. CONCLUSIONS:DD offered a robust and useful method for addressing the allocation of the scarce resource of CHC treatment. Participants were able to develop a modified version of the SF policy and offered diverse recommendations to promote fairness and improve quality of care for Veterans. DD is an effective approach for incorporating patient preferences and gaining valuable insights for critical healthcare policy decisions in resource-limited environments.
| S-EPMC7193376 | 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
Project description:ObjectiveThe effects of recipient body mass index (BMI) on waitlist strategies, waitlist outcomes, and post-transplant outcomes among adult patients listed for heart transplantation under the updated 2018 allocation system have not been well characterized.MethodsThe United Network of Organ Sharing data set between October 2015 and March 2021 was analyzed, and patients were grouped based on recipient BMI and whether listing occurred in the old (pre-October 2018) or new allocation system.ResultsListing strategies differed by BMI group, but trends of increased use of temporary mechanical support and decreased use of durable support remained among all BMI groups, except those with BMI > 35 kg/m2 . Waitlist outcomes improved among all BMI cohorts in the new allocation system, including among patients with BMI 30-34.9 and >35 kg/m2 , although patients with higher BMIs continued to have longer waitlist times. Post-transplant outcomes in the new allocation system are worse for patients with BMI > 30 kg/m2 (hazard ratio: 1.47; confidence interval: 1.19-1.82; p < .001).ConclusionsThe 2018 change to the heart transplant allocation system was associated with similar changes in the use of mechanical support for listing strategy across BMI ranges, except in the most obese, and improved waitlist outcomes across all BMI ranges. Post-transplant outcomes in the new allocation system are worse for patients with BMI > 30 kg/m2 compared to patients with BMI < 30 kg/m2 . These findings have important clinical implications for our understanding of the ongoing influence of BMI on waitlist courses and post-transplant outcomes among patients listed for heart transplantation.
| S-EPMC9320797 | biostudies-literature
Project description:BackgroundStark gaps exist between projected health needs in a pandemic situation and the current capacity of health care and medical countermeasure systems. Existing pandemic ethics discussions have advocated to engage the public in scarcity dilemmas and attend the local contexts and cultural perspectives that shape responses to a global health threat. This public engagement study thus considers the role of community and culture in the ethical apportionment of scarce health resources, specifically ventilators, during an influenza pandemic. It builds upon a previous exploration of the values and preferences of Maryland residents regarding how a finite supply of mechanical ventilators ought to be allocated during a severe global outbreak of influenza. An important finding of this earlier research was that local history and place within the state engendered different ways of thinking about scarcity.ObjectiveGiven the intrastate variation in the themes expressed by Maryland participants, the project team sought to examine interstate differences by implementing the same protocol elsewhere to answer the following questions. Does variation in ethical frames of reference exist within different regions of the United States? What practical implications does evidence of sameness and difference possess for pandemic planners and policymakers at local and national levels?MethodsResearch using the same deliberative democracy process from the Maryland study was conducted in Central Texas in March 2018 among 30 diverse participants, half of whom identified as Hispanic or Latino. Deliberative democracy provides a moderated process through which community members can learn facts about a public policy matter from experts and explore their own and others' views.ResultsParticipants proposed that by evenly distributing supplies of ventilators and applying clear eligibility criteria consistently, health authorities could enable fair allocation of scarce lifesaving equipment. The strong identification, attachment, and obligation of persons toward their nuclear and extended families emerged as a distinctive regional and ethnic core value that has practical implications for the substance, administration, and communication of allocation frameworks.ConclusionsMaryland and Central Texas residents expressed a common, overriding concern about the fairness of allocation decisions. Central Texas deliberants, however, more readily expounded upon family as a central consideration. In Central Texas, family is a principal, culturally inflected lens through which life and death matters are often viewed. Conveners of other pandemic-related public engagement exercises in the United States have advocated the benefits of transparency and inclusivity in developing an ethical allocation framework; this study demonstrates cultural competence as a further advantage.
| S-EPMC7141421 | biostudies-literature