Mathematical Structures in Group Decision-Making on Resource Allocation Distributions.
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ABSTRACT:
SUBMITTER: Friedkin NE
PROVIDER: S-EPMC6361985 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Standard guidance for allocating healthcare resources based on cost-effectiveness recommends using different decision rules for independent and mutually exclusive alternatives, although there is some confusion around the definition of "mutually exclusive." This paper reviews the definitions used in the literature and shows that interactions (i.e., non-additive effects, whereby the effect of giving 2 interventions simultaneously does not equal the sum of their individual effects) are the defining feature of mutually exclusive alternatives: treatments cannot be considered independent if the costs and/or benefits of one treatment are affected by the other treatment. The paper then identifies and categorizes the situations in which interventions are likely to have non-additive effects, including interventions targeting the same goal or clinical event, or life-saving interventions given to overlapping populations. We demonstrate that making separate decisions on interventions that have non-additive effects can prevent us from maximizing health gained from the healthcare budget. In contrast, treating combinations of independent options as though they were "mutually exclusive" makes the analysis more complicated but does not affect the conclusions. Although interactions are considered by the World Health Organization, other decision makers, such as the National Institute for Health and Care Excellence (NICE), currently make independent decisions on treatments likely to have non-additive effects. We propose a framework by which interactions could be considered when selecting, prioritizing, and appraising healthcare technologies to ensure efficient, evidence-based decision making.
| S-EPMC5949981 | biostudies-literature
Project description:Introduction: Health systems in many different countries have increasingly been reorienting the delivery of dementia care to home and community care settings. This paper provides information on how health and social care professionals (HSCPs) in Ireland make decisions on resource allocation for people with dementia living at home and how resource constraints affect their decisions and choices. Methods: A balance of care approach was used to assess resource allocation across six dementia case types, from low to high needs. Workshops were held with 24 HSCPs from multiple disciplines. Participants allocated services in two scenarios: allocation with and without a budget constraint. Nominal group technique was used to structure discussions around resource allocation in both scenarios. Thematic analysis was applied to analyse the qualitative data using a general inductive approach. Results: The following themes influenced allocative deliberations: whose needs are being met; what needs are identified; decision making context; decision making process; and allocation outcomes. Participants were proficient in making decisions, using 'decision rules' or heuristics to help them make decisions under fixed budget rules and sticking to conventional provision when constraints were in place. Conclusions: Freedom from a budget constraint allowed HSCPs to consider a broader range of services and to take a more expansive view on what needs should be considered, with a particular emphasis on adopting a proactive, preventative approach to the allocation of resources. The effect of the budget constraint overall was to narrow all considerations, using heuristics to limit the type of needs addressed and the range of services and supports provided. The consequences were a largely reactive, less personalised system of care. The findings emphasise the need for an integrated and comprehensive assessment process that is more concerned with individualised responses rather than relying on existing models of care alone.
| S-EPMC7808053 | biostudies-literature
Project description:It is well established that individuals age differently. Yet the nature of these inter-individual differences is still largely unknown. For humans, two main hypotheses have been recently formulated: individuals may experience differences in aging rate or aging timing. This issue is central because it directly influences predictions for human lifespan and provides strong insights into the biological determinants of aging. In this article, we propose a model which lets population heterogeneity emerge from an evolutionary algorithm. We find that whether individuals differ in (i) aging rate or (ii) timing leads to different emerging population heterogeneity. Yet, in both cases, the same mortality patterns are observed at the population level. These patterns qualitatively reproduce those of yeasts, flies, worms and humans. Such findings, supported by an extensive parameter exploration, suggest that mortality patterns across species and their potential shapes belong to a limited and robust set of possible curves. In addition, we use our model to shed light on the notion of subpopulations, link population heterogeneity with the experimental results of stress induction experiments and provide predictions about the expected mortality patterns. As biology is moving towards the study of the distribution of individual-based measures, the model and framework we propose here paves the way for evolutionary interpretations of empirical and experimental data linking the individual level to the population level.
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Project description:Group decision-making is required in early life in educational settings and central to a well-functioning society. However, there is little research on group decision-making in adolescence, despite the significant neuro-cognitive changes during this period. Researchers have studied adolescent decision-making in 'static' social contexts, such as risk-taking in the presence of peers, and largely deemed adolescent decision-making 'sub-optimal'. It is not clear whether these findings generalise to more dynamic social contexts, such as the discussions required to reach a group decision. Here we test the optimality of group decision-making at different stages of adolescence. Pairs of male pre-to-early adolescents (8 to 13 years of age) and mid-to-late adolescents (14 to 17 years of age) together performed a low-level, perceptual decision-making task. Whenever their individual decisions differed, they were required to negotiate a joint decision. While there were developmental differences in individual performance, the joint performance of both adolescent groups was at adult levels (data obtained from a previous study). Both adolescent groups achieved a level of joint performance expected under optimal integration of their individual information into a joint decision. Young adolescents' joint, but not individual, performance deteriorated over time. The results are consistent with recent findings attesting to the competencies, rather than the shortcomings, of adolescent social behaviour.
| S-EPMC6197285 | biostudies-literature
Project description:Context Recommended best practice for resource allocation decisions by governments include a stepwise process guided by economic evidence. However, the use of economic evidence in preventive health decision-making, which often impacts on multiple sectors of government, is under-researched. This study aimed to explore the resource allocation decision-making processes for preventive health interventions in the New South Wales (NSW) Government in Australia, and specifically examined the barriers and facilitators to the use of economic evidence from the perspective of multiple government departments. Methods This mixed methods study was conducted using semi-structured interviews with NSW Treasury representatives (n = 4), a focus group of NSW Ministry of Health representatives (n = 9), and a quantitative questionnaire of all participants. The schedule for the interviews and focus group was based on resource allocation guidance documents from Australian government agencies. Deductive content analysis was undertaken, guided by the Multiple Streams Framework. Findings NSW Treasury participants believed that decision-making processes where economic efficiency was the key guiding principle was the ideal approach. However, the NSW Ministry of Health participants identified that for preventive health decision-making, economic evidence was not used to inform their own choices but was typically only used to convince other agencies of the merits of proposed initiatives when seeking approval. The key barriers to the use of economic evidence were the lack of capacity within the NSW Ministry of Health to understand and undertake economic evaluations; a lack of collaboration between NSW Treasury and preventive health decision-makers within the NSW Ministry of Health; and deficient processes and governance mechanisms that do not facilitate or incentivise effective inter-sectoral decision-making. Conclusions Institutional structures for resource allocation decision-making regarding preventive health result in processes that contrast with best practice recommendations. The multiple challenges to collaborative decision-making across agencies require organisational change to promote a whole-of-government approach.
| S-EPMC9484643 | biostudies-literature
Project description:Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions.
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Project description:BackgroundThe understanding of appropriate or optimal care is particularly important for dementia, characterised by multiple, long-term, changing needs and the increasing expectations of people using services. However, the response of health and social care services is limited by resource constraints in most countries. This study sought to determine the optimal level, mix and cost of services for different dementia case types across the dementia continuum, and to better understand the resource allocation decision making process among health and social care professionals (HSCPs).MethodsA balance of care framework was applied to the study questions and developed in three ways; firstly by considering optimality across the course of dementia and not just at the margin with residential care; secondly, through the introduction of a fixed budget to reveal constrained optimisation strategies; and thirdly through the use of a mixed methods design whereby qualitative data was collected at workshops using nominal group technique and analysed to obtain a more detailed understanding of the decision-making process. Twenty four HSCPs from a variety of disciplines participated in the resource allocation decision-making exercise.ResultsHSCPs differentiated between case type severity; providing 2.6 times more resources to case types with higher level needs than those with lower level needs. When a resource constraint was introduced there was no evidence of any disproportionate rationing of services on the basis of need, i.e. more severe case types were not favoured over less severe case types. However, the fiscal constraint led to a much greater focus on meeting physical and clinical dependency needs through conventional social care provision. There was less emphasis on day care and psychosocial provision when resources were scarcer following the introduction of a fixed budget constraint.ConclusionsHSCPs completed complex resource allocation exercises for people with dementia, including expected differentiation across case type severity. When rationing was introduced, HSCPs did not discriminate in favour of case types with high levels of need. They did, however, support conventional home care provision over psychosocial care, although participants were still keen to provide some residual cover for the latter, especially for case types that might benefit.
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Project description:It has widely been accepted that aggregating group-level decisions is superior to individual decisions. As compared to individuals, groups tend to show a decision advantage in their response accuracy. However, there has been a lack of research exploring whether group decisions are more efficient than individual decisions with a faster information-processing speed. To investigate the relationship between accuracy and response time (RT) in group decision-making, we applied systems' factorial technology, developed by Townsend and Nozawa (Journal of Mathematical Psychology 39, 321-359, 1995) and regarded as a theory-driven methodology, to study the information-processing properties. More specifically, we measured the workload capacity CAND(t), which only considers the correct responses, and the assessment function of capacity AAND(t), which considers the speed-accuracy trade-off, to make a strong inference about the system-level processing efficiency. A two-interval, forced-choice oddball detection task, where participants had to detect which interval contains an odd target, was conducted in Experiment 1. Then, in Experiment 2, a yes/no Gabor detection task was adopted, where participants had to detect the presence of a Gabor patch. Our results replicated previous findings using the accuracy-based measure: Group detection sensitivity was better than the detection sensitivity of the best individual, especially when the two individuals had similar detection sensitivities. On the other hand, both workload capacity measures, CAND(t) and AAND(t), showed evidence of supercapacity processing, thus suggesting a collective benefit. The ordered relationship between accuracy-based and RT-based collective benefit was limited to the AAND(t) of the correct and fast responses, which may help uncover the processing mechanism behind collective benefits. Our results suggested that AAND(t), which combines both accuracy and RT into inferences, can be regarded as a novel and diagnostic tool for studying the group decision-making process.
| S-EPMC7498531 | biostudies-literature
Project description:When facing many options, we narrow down our focus to very few of them. Although behaviors like this can be a sign of heuristics, they can actually be optimal under limited cognitive resources. Here, we study the problem of how to optimally allocate limited sampling time to multiple options, modeled as accumulators of noisy evidence, to determine the most profitable one. We show that the effective sampling capacity of an agent increases with both available time and the discriminability of the options, and optimal policies undergo a sharp transition as a function of it. For small capacity, it is best to allocate time evenly to exactly five options and to ignore all the others, regardless of the prior distribution of rewards. For large capacities, the optimal number of sampled accumulators grows sublinearly, closely following a power law as a function of capacity for a wide variety of priors. We find that allocating equal times to the sampled accumulators is better than using uneven time allocations. Our work highlights that multialternative decisions are endowed with breadth-depth tradeoffs, demonstrates how their optimal solutions depend on the amount of limited resources and the variability of the environment, and shows that narrowing down to a handful of options is always optimal for small capacities.
| S-EPMC9285422 | biostudies-literature
Project description:Head-mounted displays enable social interactions in immersive virtual environments. However, it is yet unclear whether the technology is also suitable for collaborative work between remote group members. Previous research comparing group performance in nonimmersive computer-mediated communication and face-to-face (FtF) interaction yielded inconsistent results. For this reason, we set out to compare multi-user immersive virtual reality (IVR), video conferencing (VC), and FtF interaction in a group decision task. Furthermore, we examined whether the conditions differed with respect to cognitive load and social presence. Using the hidden profile paradigm, we tested 174 participants in a fictional personnel selection case. Discussion quality in IVR did not differ from VC and FtF interaction. All conditions showed the typical bias for discussing information that was provided for all participants (i.e., shared information) compared with information that was only disclosed to individual participants (i.e., unshared information). Furthermore, we found that IVR groups showed the same probability of solving the task correctly. Social presence in IVR was reduced compared with FtF interaction; however, we found no differences in cognitive load. In sum, our results imply that IVR can effectuate efficient group behavior in a modern working environment that is characterized by a growing demand for remote collaboration.
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