Structural explanations lead young children and adults to rectify resource inequalities

Decisions about how to divide resources have profound social and practical consequences. Do explanations regarding the source of existing inequalities influence how children and adults allocate new resources? When 3- to 6-year-old children (N = 201) learned that inequalities were caused by structural forces (stable external constraints affecting access to resources) as opposed to internal forces (effort), they rectified inequalities, overriding previously documented tendencies to perpetuate inequality or divide resources equally. Adults (N = 201) were more likely than children to rectify inequality spontaneously; this was further strengthened by a structural explanation but reversed by an effort-based explanation. Allocation behaviors were mirrored in judgments of which allocation choices by others were appropriate. These findings reveal how explanations powerfully guide social reasoning and action from childhood through adulthood.

A multi-criteria simulation-optimization coupling approach for effective emergency response in marine oil spill accidents

Effective marine oil spill responses are vital to reduce environmental, societal, and economic damage. This study developed a Multi-Criteria Emergency Response System (MC-ERS) to comprehensively evaluate response efficiency, operational costs, and environmental losses. The proposed system integrates dynamic multiphase simulation of oil weathering and oil cleanup processes and further provides effective planning for multi-stage resource allocation through system optimization. The developed weight-sum model improved the performance of response operations by reducing the complexity of multi-criteria decision-making. Particle Swarm Optimization (PSO) was chosen as the foundational optimization algorithm due to its efficiency in rapid convergence and suitability for complex problems. From extensive comparisons of PSO variants across benchmark functions and inertia strategies, the C-PSO algorithm was developed, demonstrating enhanced optimization performance for MC-ERS. The developed modelling system performance was demonstrated and evaluated through a representative case study. The optimization plan coordinated resource allocation from onshore warehouses to harbors and spill sites, balancing oil recovery efficiency, costs, and ecological losses. Optimized results indicate an oil recovery of up to 76.50% in five days. Additionally, the system cuts costs by 3.45% and environmental losses by 15.75%. The findings enhance the efficiency of marine oil spill emergency response and provide support for such incidents.

Crop-emptying rate and nectar resource allocation in a nectivorous pollinator

In nectivorous pollinators, timing and pattern of allocation of consumed nectar affects fitness traits and foraging behavior. Differences in male and female behaviors can influence these allocation strategies. These physiological patterns are not well studied in Lepidoptera, despite them being important pollinators. In this study we investigate crop-emptying rate and nectar allocation in Manduca sexta (Sphingidae), and how sex and flight influence these physiological patterns. After a single feeding event, moths were dissected at fixed time intervals to measure crop volume and analyze sugar allocation to flight muscle and fat body. Then we compared sedentary and flown moths to test how activity may alter these patterns. Sedentary males and females emptied their crops six hours after a feeding event. Both males and females preferentially allocated these consumed sugars to fat body over flight muscle. Moths began to allocate to the fat body during crop-emptying and retained these nutrients long-term (four and a half days after a feeding event). Males allocated consumed sugar to flight muscles sooner and retained these allocated nutrients in the flight muscle longer than did females. Flight initiated increased crop-emptying in females, but had no effect on males. Flight did not significantly affect allocation to flight muscle or fat body in either sex. This study showed that there are inherent differences in male and female nectar sugar allocation strategies, but that male and female differences in crop-emptying rate are context dependent on flight activity. These differences in physiology may be linked to distinct ways males and females maximize their own fitness.

Surgical waitlist management: Perspectives from surgeons on surgical prioritization at a paediatric hospital

Globally exacerbated surgical waitlists have provided the opportunity to reflect on prioritization and resource allocation decisions. The unique circumstances of paediatric surgery and consequences of surgical delay prompted the study reported in this paper. As part of a larger project to attend to prioritization in our surgical waitlists, we conducted a Quality Improvement study, the purpose of which is to understand surgeon's perspectives regarding the ethical and practical realities of surgical prioritization at our institution. The study comprises semi-structured interviews with nine full-time paediatric surgeons from a variety of subspecialties conducted at our institution, which is a tertiary paediatric hospital with ten surgical subspecialties in a publicly funded healthcare system. Participants articulated how they prioritize their waitlists, and how they understand ethical prioritization. These findings resonate with the growing public concern for ethical practice in healthcare delivery and transparency in prioritization and resource allocation practices. Specifically, more transparency, consistency, and support is required in prioritization practices. This work highlights the importance of institutional dialogue regarding surgical case prioritization. Because quality improvement work is necessarily site-specific, concrete generalizations cannot be offered. However, the insights gleaned from these interviews and the process by which they were gleaned are a valuable knowledge-sharing resource for any institution that is interested in ongoing quality improvement work. The objectives here were to clarify the goals of prioritization within the institution, improve prioritization practices, and make them more ethical and transparent.

Effect of mortality prediction models on resource use benchmarking of intensive care units

PURPOSE

Intensive care requires extensive resources. The ICUs' resource use can be compared using standardized resource use ratios (SRURs). We assessed the effect of mortality prediction models on the SRURs.

MATERIALS AND METHODS

We compared SRURs using different mortality prediction models: the recent Finnish Intensive Care Consortium (FICC) model and the SAPS-II model (n = 68,914 admissions). We allocated the resources to severity of illness strata using deciles of predicted mortality. In each risk and year stratum, we calculated the expected resource use per survivor from our modelling approaches using length of ICU stay and Therapeutic Intervention Scoring System (TISS) points.

RESULTS

Resource use per survivor increased from one length of stay (LOS) day and around 50 TISS points in the first decile to 10 LOS-days and 450 TISS in the tenth decile for both risk scoring systems. The FICC model predicted mortality risk accurately whereas the SAPS-II grossly overestimated the risk of death. Despite this, SRURs were practically identical and consistent.

CONCLUSIONS

SRURs provide a robust tool for benchmarking resource use within and between ICUs. SRURs can be used for benchmarking even if recently calibrated risk scores for the specific population are not available.

Design of load-aware resource allocation for heterogeneous fog computing systems

The execution of delay-aware applications can be effectively handled by various computing paradigms, including the fog computing, edge computing, and cloudlets. Cloud computing offers services in a centralized way through a cloud server. On the contrary, the fog computing paradigm offers services in a dispersed manner providing services and computational facilities near the end devices. Due to the distributed provision of resources by the fog paradigm, this architecture is suitable for large-scale implementation of applications. Furthermore, fog computing offers a reduction in delay and network load as compared to cloud architecture. Resource distribution and load balancing are always important tasks in deploying efficient systems. In this research, we have proposed heuristic-based approach that achieves a reduction in network consumption and delays by efficiently utilizing fog resources according to the load generated by the clusters of edge nodes. The proposed algorithm considers the magnitude of data produced at the edge clusters while allocating the fog resources. The results of the evaluations performed on different scales confirm the efficacy of the proposed approach in achieving optimal performance.

Dietary restriction and life-history trade-offs: insights into mTOR pathway regulation and reproductive investment in Japanese quail

Resources are needed for growth, reproduction and survival, and organisms must trade off limited resources among competing processes. Nutritional availability in organisms is sensed and monitored by nutrient-sensing pathways that can trigger physiological changes or alter gene expression. Previous studies have proposed that one such signalling pathway, the mechanistic target of rapamycin (mTOR), underpins a form of adaptive plasticity when individuals encounter constraints in their energy budget. Despite the fundamental importance of this process in evolutionary biology, how nutritional limitation is regulated through the expression of genes governing this pathway and its consequential effects on fitness remain understudied, particularly in birds. We used dietary restriction to simulate resource depletion and examined its effects on body mass, reproduction and gene expression in Japanese quails (Coturnix japonica). Quails were subjected to feeding at 20%, 30% and 40% restriction levels or ad libitum for 2 weeks. All restricted groups exhibited reduced body mass, whereas reductions in the number and mass of eggs were observed only under more severe restrictions. Additionally, dietary restriction led to decreased expression of mTOR and insulin-like growth factor 1 (IGF1), whereas the ribosomal protein S6 kinase 1 (RPS6K1) and autophagy-related genes (ATG9A and ATG5) were upregulated. The pattern in which mTOR responded to restriction was similar to that for body mass. Regardless of the treatment, proportionally higher reproductive investment was associated with individual variation in mTOR expression. These findings reveal the connection between dietary intake and the expression of mTOR and related genes in this pathway.

High ambient temperature impact on the pattern of emergency-room visits due to renal colic in the Middle East

Urolithiasis has a seasonal pattern, with an established increase in incidence during the summer months. This study aims to assess the impact of high ambient temperatures on emergency room (ER) visits related to renal colic (RC) in a Middle Eastern country over the past decade. Population data were extracted using the MDClone Big Data platform. We recorded demographic and clinical data on all RC-associated ER visits from January 2012 to April 2023 and calculated the heat index (HI) that combines daily average coastal plane temperatures and humidity percentages. There was a total of 12,770 ER visits (median age 48 years, 9,236 (72%) males). The number of visits increased during the hottest months (July-October), with the highest numbers recorded during August. The number of visits remained stable throughout the study. We identified a linear association between humidity and the incidence of ER visits (p = 0.002), and a non-linear association between ambient temperature (p < 0.0001) and HI (p < 0.0001). There was a direct relationship between high temperatures and ER visits on the same day (risk ratio [RR]: 1.75, p = 0.036), with a 2-day lag (RR: 1.123, p = 0.024). In Conclusion, there is a significant relationship between temperature, humidity, HI, and the number of ER visits due to RC. Adjusted resource allocation and healthcare workforce availability are essential for managing additional cases during heat waves. Clinical implications: Increased demand is expected during heatwaves and within a 2-day lag, emphasizing the importance of proactive strategies to effectively manage RC patients.

How important is hidden phenotypic plasticity arising from alternative but converging developmental trajectories, and what limits it?

Developmental plasticity -- the capacity for a genotype to develop into different phenotypes, depending on the environment - is typically viewed from the perspective of the resulting phenotype. Thus, if development is viewed as a trajectory towards a target, then developmental plasticity allows environmentally induced alterations to the target. However, there can also be variations in the trajectory. This is seen with compensatory responses, for instance where growth accelerates after an earlier period of food shortage, or where investment in sexual ornaments is maintained even when resources are limiting. If the compensation is complete, the adult phenotype can appear 'normal' (i.e. the different developmental trajectories converge on the same target). However, alternative trajectories to a common target can have multiple long-term consequences, including altered physiological programming and rates of senescence, possibly owing to trade-offs between allocating resources to the prioritized trait versus to body maintenance. This suggests that plasticity in developmental trajectories towards a common target leads to variation in the resilience and robustness of the adult body. This form of developmental plasticity is far more hidden than plasticity in final adult target, but it may be more common. Here, I discuss the causes, consequences and limitations of these different kinds of plasticity, with a special focus on whether they are likely to be adaptive. I emphasize the need to study plasticity in developmental trajectories, and conclude with suggestions for future research to tease apart the different forms of developmental plasticity and the factors that influence their evolution and expression.

Costs and benefits of scaling psychosocial interventions during the perinatal period in England: A simulation modelling study

BACKGROUND

Globally, guidance recommends the integration of mental health into maternal and child healthcare to address common maternal mental health problems during the perinatal period. However, implementing this in the real-world requires substantial resource allocations.

OBJECTIVE

The aim of this study was to estimate the likely costs and consequences linked to scaling the delivery of treatment (in the form of psychosocial interventions) during the perinatal period.

DESIGN

Simulation modelling.

SETTING(S)

England.

METHODS

Costs and consequences were modelled for three scenarios of assumed provision of services, whereby one referred to the projected provision under current government plans, with no additional scaling up of treatment. The other two scenarios referred to additional scaling of treatment: in one scenario, this referred to the provision of treatment by midwives and health visitors trained in the routine enquiry about mental health and delivery of psychosocial interventions; in the other scenario this referred to an expanded provision by primary mental health services. For each scenario and in yearly intervals (covering a ten-year period, 2015 to 2024), unit cots and outcomes were assigned to the activities women were assumed to receive (routine enquiry, assessment, treatment, care coordination). All costs were in 2020 pounds sterling. Data sources for the modelling included: published findings from randomised controlled trials; national unit cost source; national statistics; and expert consultation.

RESULTS

If the projected treatment gap was to be addressed, an estimated additional 111,154 (50,031) women would be accessing treatment in 2015 (2024). Estimated total costs (including cost offsets) in the scenario of projected provision under current government plans would be £73.5 million in 2015 and £95.2 million in 2024, whilst quality-adjusted life years gained would be 901 and 928 respectively. Addressing the treatment gap through provision by trained midwives and health visitors could mean additional costs of £7.3 million in 2015 but lower costs of £18.4 million in 2024. The additional quality-adjusted life years gained are estimated at 2096 in 2015 and 1418 in 2024. A scenario in which the treatment gap would be met by primary mental health services was likely to be more costly and delivered less health gains.

CONCLUSIONS

Findings from this modelling study suggest that scaling the integration of mental health care into routinely delivered care for women during the perinatal period might be economically viable.

REGISTRATION

N/A.

TWEETABLE ABSTRACT

Integrating mental health into maternal and child healthcare might generate economic benefits new study by @a_annettemaria and @knappem @CPEC_LSE finds #increasing access to treatment for women with perinatal mental health problems.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Development and implementation of a breast imaging order panel in the electronic health record: Helping the ordering providers get it right

Appropriate ordering of breast imaging studies is complex due to the variety of clinical indications and available imaging modalities. Incorrect ordering affects radiology resource allocation due to the different workflows and personnel requirements of screening and diagnostic breast imaging. Through the collaborative efforts of stakeholders in Primary Care, Radiology, and Information Services & Solutions, we developed and implemented a breast imaging order panel in the electronic health record with integrated clinical decision support to facilitate correct order selection for screening patients at average-risk and high-risk of breast cancer and for diagnostic breast imaging of symptomatic patients.

Radiologists predict differential resource utilization but not clinical outcome in emergency department patients imaged with ultrasound for right upper quadrant pain

PURPOSE

Radiologists with diverse training, specialization, and habits interpret imaging in the Emergency Department. It is necessary to understand if their variation predicts differential value. The purpose of this study was to determine whether attending radiologist variation predicts major clinical outcomes in adult Emergency Department patients imaged with ultrasound for right upper quadrant pain.

METHODS

Consecutive ED patients imaged with ultrasound for RUQ pain from 10/8/2016 to 8/10/2022 were included (N = 7097). The primary outcome was prediction of hospital admission by signing attending radiologist. Secondary outcomes included: ED and hospital length of stay (LOS), 30-day mortality, 30-day re-presentation rate, subspecialty consultation, advanced imaging follow up (HIDA, MRI, CT), and intervention (ERCP, drainage or surgery). Sample size was determined a priori (detectable effect size: w = 0.06). Data were adjusted for demographic data, Elixhauser comorbidities, number of ED visits in prior year, clinical data, and system factors (38 covariates). P-values were corrected for multiple comparisons (false discovery rate-adjusted p-values).

RESULTS

The included ultrasounds were read by 35 radiologists (median exams/radiologist: 145 [74.5-241.5]). Signing radiologist did not predict hospitalization (p = 0.85), abdominopelvic surgery or intervention within 30 days, re-presentation to the Emergency Department within 30 days, or subspecialty consultation. Radiologist did predict difference in Emergency Department length of stay (p < 0.001) although this difference was small and imprecise. HIDA was mentioned variably by radiologists (range 0-19%, p < 0.001), and mention of HIDA in the ultrasound report increased 10-fold the odds of HIDA being performed in the next 72 h (odds ratio 10.4 [8.0-13.4], p < 0.001).

CONCLUSION

Radiologist variability did not predict meaningful outcome differences for patients with right upper quadrant pain undergoing ultrasound in the Emergency Department, but when radiologists mention HIDA in their reports, it predicts a 10-fold increase in the odds a HIDA is performed. Radiologists are relied on for interpretation that shapes subsequent patient care, and it is important to consider how radiologist variability can influence both outcome and resource utilization.

Bridging the gap: coordinating equity and efficiency in older people care resource allocation in China

BACKGROUND

With the increasing global aging population, how to allocate older people care resources reasonably has become an increasingly urgent international issue. China, as the largest developing country, has made many efforts to actively respond to the challenges of an aging population. However, there are still problems with uneven allocation of older people care resources and low efficiency of allocation. Therefore, this study evaluates the regional differences and dynamic evolution of the equity and efficiency of older people care resource allocation in China from 2009 to 2020, and explores ways to change the current situation.

METHODS

The data used in this study were derived from the "China Statistical Yearbook" and the "China Civil Affairs Statistical Yearbook" for the period of 2010-2021. Firstly, the equity of older people care resource allocation was measured using the Gini coefficient, the Theil index, the Older People Care Resource Density Index, and the Older People Care Resource Agglomeration Degree. Secondly, the dynamic Slack-Based Measure data envelopment analysis method was adopted to evaluate efficiency. Lastly, the Z-score is used to normalize the equity index and perform classification matching with the efficiency value. Spatial autocorrelation analysis and hotspot analysis were conducted using GIS technology to examine the dynamic evolution process of older people care resource allocation equity and efficiency, as well as their spatial distribution patterns and coordination across provinces from 2009 to 2020.

RESULTS

The equity analysis showed that the spatial distribution of various types of older people care resources was uneven, and the differences were mainly due to internal differences within each region, with the largest equity differences observed in western provinces. Currently, older people care resources are mainly concentrated in eastern regions, while the total amount of older people care resources in western regions and some central regions is relatively small, which cannot meet the older people care needs of residents. The efficiency analysis results showed that the efficiency of older people care resource allocation has been improving over the past 12 years, and in 2020, 77.42% of provinces were located on the efficiency frontier with an average efficiency value of 0.9396. Finally, the coordination analysis results showed that there were significant spatiotemporal differences in the equity and efficiency of older people care resources allocation.

CONCLUSION

With the development of society and economy, the total amount and service capacity of older people care resources in China have greatly improved. However, there are still significant spatiotemporal differences in the equity and efficiency of older people care resource allocation. The development of older people care services in central and eastern provinces is unbalanced, and there is a polarization trend in terms of equity and efficiency of older people care resource allocation. Most provinces in western regions face the dual dilemma of inadequate older people care resources and low utilization efficiency. It is recommended that policymakers comprehensively consider population and geographic factors in different provinces, establish relevant allocation standards according to local conditions, improve the redistribution system, and focus on increasing the total amount of older people care resources in underdeveloped provinces while promoting resource flow.

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis

BACKGROUND

A lack of health resources is a common problem after the outbreak of infectious diseases, and resource optimization is an important means to solve the lack of prevention and control capacity caused by resource constraints. This study systematically evaluated the similarities and differences in the application of coronavirus disease (COVID-19) resource allocation models and analyzed the effects of different optimal resource allocations on epidemic control.

METHODS

A systematic literature search was conducted of CNKI, WanFang, VIP, CBD, PubMed, Web of Science, Scopus and Embase for articles published from January 1, 2019, through November 23, 2023. Two reviewers independently evaluated the quality of the included studies, extracted and cross-checked the data. Moreover, publication bias and sensitivity analysis were evaluated.

RESULTS

A total of 22 articles were included for systematic review; in the application of optimal allocation models, 59.09% of the studies used propagation dynamics models to simulate the allocation of various resources, and some scholars also used mathematical optimization functions (36.36%) and machine learning algorithms (31.82%) to solve the problem of resource allocation; the results of the systematic review show that differential equation modeling was more considered when testing resources optimization, the optimization function or machine learning algorithm were mostly used to optimize the bed resources; the meta-analysis results showed that the epidemic trend was obviously effectively controlled through the optimal allocation of resources, and the average control efficiency was 0.38(95%CI 0.25-0.51); Subgroup analysis revealed that the average control efficiency from high to low was health specialists 0.48(95%CI 0.37-0.59), vaccines 0.47(95%CI 0.11-0.82), testing 0.38(95%CI 0.19-0.57), personal protective equipment (PPE) 0.38(95%CI 0.06-0.70), beds 0.34(95%CI 0.14-0.53), medicines and equipment for treatment 0.32(95%CI 0.12-0.51); Funnel plots and Egger's test showed no publication bias, and sensitivity analysis suggested robust results.

CONCLUSION

When the data are insufficient and the simulation time is short, the researchers mostly use the constructor for research; When the data are relatively sufficient and the simulation time is long, researchers choose differential equations or machine learning algorithms for research. In addition, our study showed that control efficiency is an important indicator to evaluate the effectiveness of epidemic prevention and control. Through the optimization of medical staff and vaccine allocation, greater prevention and control effects can be achieved.

Optimizing the medical equipment investment in primary care centres in rural China: evidence from a panel threshold model

BACKGROUND

The previous "one-size-fits-all" practice in resource allocation can no longer adapt to the spatial variation in population and health needs. This study aimed to investigate the spatially heterogeneous effect of medical equipment investment in the township health centres in rural China to optimize the investment strategies.

METHODS

Based on the national-scale stratified multistage cluster sampling, 319 township health centres from six provinces were included in the study. The retrospective data from 2013 to 2017 were collected for each sampled township health centres and the corresponding township community. The panel threshold regression model was applied to estimate the nonlinear effect of medical equipment increment on the service utilization due to the township communities' urbanization degree. The influence of township community remoteness on the effects of equipment increment was investigated through subgroup analysis.

RESULTS

Among the township health centres in the neighbouring towns of the county seat (travel time to the county seat < 1 h), the significant effect of medical equipment increment was only found in the township health centres of the towns with high urbanization degrees (the proportion of the residents living in the built-up area > 69.89%), of which the effect size was 774.81 (95% CI 495.63, 1053.98, p < 0.05). Among the township health centres in the remote towns (travel time ≥ 1 h), the effect of medical equipment increment in the township health centres of the low urbanized towns (urban ≤ 5.99%, β = 1052.54, p < 0.01) was around four times the size of that of the counterparts (urban > 5.99%, β = 237.00, p < 0.01).

CONCLUSION

This study demonstrated the spatially heterogeneous effect of medical equipment investment in the primary care centres in rural China. The priority of the equipment investment was suggested to be given to the township health centres in the remote towns with a low urbanization degree and those in the highly-urbanized neighbouring towns of the county seats.

Exploring the landscape of health technology assessment in Iran: perspectives from stakeholders on needs, demand and supply

BACKGROUND

The evaluation of health technologies plays a crucial role in the allocation of resources and the promotion of equitable healthcare access, known as health technology assessment (HTA). This study focuses on Iran's efforts to integrate HTA and aims to gain insights into stakeholder perspectives regarding capacity needs, demand and implementation.

METHODS

In this study, we employed the HTA introduction status analysis questionnaire developed by the International Decision Support Initiative (iDSI), which has been utilized in various countries. The questionnaire consisted of 12 questions divided into three sections: HTA need, demand and supply. To identify key informants, we conducted a literature review and consulted with the Ministry of Health and Medical Education (MOHME), as well we experts in policy-making, health service provision and HTA. We selected stakeholders who held decision-making positions in the healthcare domain. A modified Persian version of the questionnaire was administered online from September 2022 to January 2023 and was pretested for clarity. The analysis of the collected data involved quantitative methods for descriptive analysis and qualitative methods for thematic analysis.

RESULTS

In this study, a total of 103 questionnaires were distributed, resulting in a favourable response rate of 61% from 63 participants, of whom 68% identified as male. The participants, when assessing the needs of HTA, rated allocative efficiency as the highest priority, with a mean rating of 8.53, thereby highlighting its crucial role in optimizing resource allocation. Furthermore, healthcare quality, with a mean rating of 8.17, and transparent decision-making, with a mean rating of 7.92, were highly valued for their impact on treatment outcomes and accountability. The importance of budget control (mean rating 7.58) and equity (mean rating 7.25) were also acknowledged, as they contribute to maintaining sustainability and promoting social justice. In terms of HTA demand, safety concerns were identified as the top priority, closely followed by effectiveness and cost-effectiveness, with an expanded perspective on the economy. However, limited access to local data was reported, which arose from various factors including data collection practices, system fragmentation and privacy concerns. The priorities of HTA users encompassed coverage, payment reform, benefits design, guidelines, service delivery and technology registration. Evidence generation involved the participation of medical universities, research centres and government bodies, albeit with ongoing challenges in research quality, data access and funding. The study highlights government support and medical education as notable strengths in this context.

CONCLUSIONS

This study provides a comprehensive evaluation of Iran's HTA landscape, considering its capacity, demand and implementation aspects. It underlines the vital role of HTA in optimizing resources, improving healthcare quality and promoting equity. The study also sheds light on the strengths of evidence generation in the country, while simultaneously identifying challenges related to data access and system fragmentation. In terms of policy priorities, evidence-based decision-making emerges as crucial for enhancing healthcare access and integrating technology. The study stresses the need for evidence-based practices, a robust HTA infrastructure and collaboration among stakeholders to achieve better healthcare outcomes in Iran.

Metabolic impact of heterologous protein production in Pseudomonas putida: Insights into carbon and energy flux control

For engineered microorganisms, the production of heterologous proteins that are often useless to host cells represents a burden on resources, which have to be shared with normal cellular processes. Within a certain metabolic leeway, this competitive process has no impact on growth. However, once this leeway, or free capacity, is fully utilized, the extra load becomes a metabolic burden that inhibits cellular processes and triggers a broad cellular response, reducing cell growth and often hindering the production of heterologous proteins. In this study, we sought to characterize the metabolic rearrangements occurring in the central metabolism of Pseudomonas putida at different levels of metabolic load. To this end, we constructed a P. putida KT2440 strain that expressed two genes encoding fluorescent proteins, one in the genome under constitutive expression to monitor the free capacity, and the other on an inducible plasmid to probe heterologous protein production. We found that metabolic fluxes are considerably reshuffled, especially at the level of periplasmic pathways, as soon as the metabolic load exceeds the free capacity. Heterologous protein production leads to the decoupling of anabolism and catabolism, resulting in large excess energy production relative to the requirements of protein biosynthesis. Finally, heterologous protein production was found to exert a stronger control on carbon fluxes than on energy fluxes, indicating that the flexible nature of P. putida's central metabolic network is solicited to sustain energy production.

Resource allocation in public sector programmes: does the value of a life differ between governmental departments?

BACKGROUND

The value of a life is regularly monetised by government departments for informing resource allocation. Guidance documents indicate how economic evaluation should be conducted, often specifying precise values for different impacts. However, we find different values of life and health are used in analyses by departments within the same government despite commonality in desired outcomes. This creates potential inconsistencies in considering trade-offs within a broader public sector spending budget. We provide evidence to better inform the political process and to raise important issues in assessing the value of public expenditure across different sectors.

METHODS

Our document analysis identifies thresholds, explicitly or implicitly, as observed in government-related publications in the following public sectors: health, social care, transport, and environment. We include both demand-side and supply-side thresholds, understood as societies' and governments' willingness to pay for health gains. We look at key countries that introduced formal economic evaluation processes early on and have impacted other countries' policy development: Australia, Canada, Japan, New Zealand, the Netherlands, and the United Kingdom. We also present a framework to consider how governments allocate resources across different public services.

RESULTS

Our analysis supports that identifying and describing the Value of a Life from disparate public sector activities in a manner that facilitates comparison is theoretically meaningful. The optimal allocation of resources across sectors depends on the relative position of benefits across different attributes, weighted by the social value that society puts on them. The value of a Quality-Adjusted Life Year is generally used as a demand-side threshold by Departments of transport and environment. It exceeds those used in health, often by a large enough proportion to be a multiple thereof. Decisions made across departments are generally based on an unspecified rationing rule.

CONCLUSIONS

Comparing government expenditure across different public sector departments, in terms of the value of each department outcome, is not only possible but also desirable. It is essential for an optimal resource allocation to identify the relevant social attributes and to quantify the value of these attributes for each department.

Resource allocation during the coronavirus disease 2019 pandemic and the impact on patients with lung cancer: a systematic review

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic resulted in unprecedented tolls on both economies and human life. Healthcare resources needed to be reallocated away from the care of patients and towards supporting the pandemic response. In this systematic review, we explore the impact of resource allocation during the COVID-19 pandemic on the screening, diagnosis, management and outcomes of patients with lung cancer during the pandemic.

METHODS

PubMed and Embase were systematically searched for articles investigating the impact of the COVID-19 pandemic on patients with lung cancer. Of the 1605 manuscripts originally screened, 47 studies met the inclusion criteria.

RESULTS

Patients with lung cancer during the pandemic experienced reduced rates of screening, diagnostic testing and interventions but did not experience worse outcomes. Population-based modelling studies predict significant increases in mortality for patients with lung cancer in the years to come.

CONCLUSIONS

Reduced access to resources during the pandemic resulted in reduced rates of screening, diagnosis and treatment for patients with lung cancer. While significant differences in outcomes were not identified in the short term, ultimately the effects of the pandemic and reductions in cancer screening will likely be better delineated in the coming years. Future consideration of the long-term implications of resource allocation away from patients with lung cancer with an attempt to provide equitable access to healthcare and limited interruptions of patient care may help to provide the best care for all patients during times of limited resources.

Operationalizing Primary Outcomes to Achieve Reach, Effectiveness, and Equity in Multilevel Interventions

When intervention scientists plan a clinical trial of an intervention, they select an outcome metric that operationalizes their definition of intervention success. The outcome metric that is selected has important implications for which interventions are eventually supported for implementation at scale and, therefore, what health benefits (including how much benefit and for whom) are experienced in a population. Particularly when an intervention is to be implemented in a population that experiences a health disparity, the outcome metric that is selected can also have implications for equity. Some outcome metrics risk exacerbating an existing health disparity, while others may decrease disparities for some but have less effect for the larger population. In this study, we use a computer to simulate implementation of a hypothetical multilevel, multicomponent intervention to highlight the tradeoffs that can occur between outcome metrics that reflect different operationalizations of intervention success. In particular, we highlight tradeoffs between overall mean population benefit and the distribution of health benefits in the population, which has direct implications for equity. We suggest that simulations like the one we present can be useful in the planning of a clinical trial for a multilevel and/or multicomponent intervention, since simulated implementation at scale can illustrate potential consequences of candidate operationalization of intervention success, such that unintended consequences for equity can be avoided.

Characterization of trade-offs between immunity and reproduction in the coral species Astrangia poculata

Background

Living organisms face ubiquitous pathogenic threats and have consequently evolved immune systems to protect against potential invaders. However, many components of the immune system are physiologically costly to maintain and engage, often drawing resources away from other organismal processes such as growth and reproduction. Evidence from a diversity of systems has demonstrated that organisms use complex resource allocation mechanisms to manage competing needs and optimize fitness. However, understanding of resource allocation patterns is limited across taxa. Cnidarians, which include ecologically important organisms like hard corals, have been historically understudied in the context of resource allocations. Improving understanding of resource allocation-associated trade-offs in cnidarians is critical for understanding future ecological dynamics in the face of rapid environmental change.

Methods

Here, we characterize trade-offs between constitutive immunity and reproduction in the facultatively symbiotic coral Astrangia poculata. Male colonies underwent ex situ spawning and sperm density was quantified. We then examined the effects of variable symbiont density and energetic budget on physiological traits, including immune activity and reproductive investment. Furthermore, we tested for potential trade-offs between immune activity and reproductive investment.

Results

We found limited associations between energetic budget and immune metrics; melanin production was significantly positively associated with carbohydrate concentration. However, we failed to document any associations between immunity and reproductive output which would be indicative of trade-offs, possibly due to experimental limitations. Our results provide a preliminary framework for future studies investigating immune trade-offs in cnidarians.

Equilibrium price estimation of green bonds from the perspective of resource allocation

Green bonds offer substantial positive externalities compared to other types of bonds. This leads to a resource distribution efficiency that falls below the optimal level dictated by Pareto efficiency. It becomes essential to determine a means by which green bonds can achieve an equilibrium price, ensuring optimal public resource allocation and maximized social welfare. From the perspective of externalities, this study employs the carbon shadow price (CSP) to determine the equilibrium price of carbon emissions. Subsequently, this value aids in estimating the equilibrium price of green bonds. Firstly, we introduced an optimized bootstrap method to estimate the bias-corrected CSP at the provincial level in China from 2007 to 2020. Then, a pricing framework is developed, integrating both the carbon trading price and the estimated CSP, to determine the green bond's equilibrium price. Numerical simulations indicate that, under current conditions, green bonds cannot achieve the equilibrium price by relying solely on the carbon trading mechanism. Therefore, further development of China's carbon emissions trading market is required.

Performance of an AI algorithm during the different phases of the COVID pandemics: what can we learn from the AI and vice versa

Background

Artificial intelligence (AI) has proved to be of great value in diagnosing and managing Sars-Cov-2 infection. ALFABETO (ALL-FAster-BEtter-TOgether) is a tool created to support healthcare professionals in the triage, mainly in optimizing hospital admissions.

Methods

The AI was trained during the pandemic's "first wave" (February-April 2020). Our aim was to assess the performance during the "third wave" of the pandemics (February-April 2021) and evaluate its evolution. The neural network proposed behavior (hospitalization vs home care) was compared with what was actually done. If there were discrepancies between ALFABETO's predictions and clinicians' decisions, the disease's progression was monitored. Clinical course was defined as "favorable/mild" if patients could be managed at home or in spoke centers and "unfavorable/severe" if patients need to be managed in a hub center.

Results

ALFABETO showed accuracy of 76%, AUROC of 83%; specificity was 78% and recall 74%. ALFABETO also showed high precision (88%). 81 hospitalized patients were incorrectly predicted to be in "home care" class. Among those "home-cared" by the AI and "hospitalized" by the clinicians, 3 out of 4 misclassified patients (76.5%) showed a favorable/mild clinical course. ALFABETO's performance matched the reports in literature.

Conclusions

The discrepancies mostly occurred when the AI predicted patients could stay at home but clinicians hospitalized them; these cases could be handled in spoke centers rather than hubs, and the discrepancies may aid clinicians in patient selection. The interaction between AI and human experience has the potential to improve both AI performance and our comprehension of pandemic management.

Should AI allocate livers for transplant? Public attitudes and ethical considerations

BACKGROUND

Allocation of scarce organs for transplantation is ethically challenging. Artificial intelligence (AI) has been proposed to assist in liver allocation, however the ethics of this remains unexplored and the view of the public unknown. The aim of this paper was to assess public attitudes on whether AI should be used in liver allocation and how it should be implemented.

METHODS

We first introduce some potential ethical issues concerning AI in liver allocation, before analysing a pilot survey including online responses from 172 UK laypeople, recruited through Prolific Academic.

FINDINGS

Most participants found AI in liver allocation acceptable (69.2%) and would not be less likely to donate their organs if AI was used in allocation (72.7%). Respondents thought AI was more likely to be consistent and less biased compared to humans, although were concerned about the "dehumanisation of healthcare" and whether AI could consider important nuances in allocation decisions. Participants valued accuracy, impartiality, and consistency in a decision-maker, more than interpretability and empathy. Respondents were split on whether AI should be trained on previous decisions or programmed with specific objectives. Whether allocation decisions were made by transplant committee or AI, participants valued consideration of urgency, survival likelihood, life years gained, age, future medication compliance, quality of life, future alcohol use and past alcohol use. On the other hand, the majority thought the following factors were not relevant to prioritisation: past crime, future crime, future societal contribution, social disadvantage, and gender.

CONCLUSIONS

There are good reasons to use AI in liver allocation, and our sample of participants appeared to support its use. If confirmed, this support would give democratic legitimacy to the use of AI in this context and reduce the risk that donation rates could be affected negatively. Our findings on specific ethical concerns also identify potential expectations and reservations laypeople have regarding AI in this area, which can inform how AI in liver allocation could be best implemented.

Controlling circuitry underlies the growth optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

Nutritional control of developmental processes

Nutritional and metabolic cues are integral to animal development. Organisms use them both as sustenance and environmental indicators, fueling, informing and influencing developmental decisions. Classical examples, such as the Warburg effect, clearly illustrate how genetic programs control metabolic changes. However, the way that nutrition and metabolism can also modulate or drive genetic programs to instruct developmental trajectories is much more elusive, owing to several difficulties including uncoupling permissive and instructive functions. Here, we discuss recent advancements in the field that highlight the developmental role of nutritional and metabolic cues across multiple levels of organismal complexity.

Mining Google Trends data for nowcasting and forecasting colorectal cancer (CRC) prevalence

Background

Colorectal cancer (CRC) is the third most prevalent and second most lethal form of cancer in the world. Consequently, CRC cancer prevalence projections are essential for assessing the future burden of the disease, planning resource allocation, and developing service delivery strategies, as well as for grasping the shifting environment of cancer risk factors. However, unlike cancer incidence and mortality rates, national and international agencies do not routinely issue projections for cancer prevalence. Moreover, the limited or even nonexistent cancer statistics for large portions of the world, along with the high heterogeneity among world nations, further complicate the task of producing timely and accurate CRC prevalence projections. In this situation, population interest, as shown by Internet searches, can be very important for improving cancer statistics and, in the long run, for helping cancer research.

Methods

This study aims to model, nowcast and forecast the CRC prevalence at the global level using a three-step framework that incorporates three well-established univariate statistical and machine-learning models. First, data mining is performed to evaluate the relevancy of Google Trends (GT) data as a surrogate for the number of CRC survivors. The results demonstrate that population web-search interest in the term "colonoscopy" is the most reliable indicator to nowcast CRC disease prevalence. Then, various statistical and machine-learning models, including ARIMA, ETS, and FNNAR, are trained and tested using relevant GT time series. Finally, the updated monthly query series spanning 2004-2022 and the best forecasting model in terms of out-of-sample forecasting ability (i.e., the neural network autoregression) are utilized to generate point forecasts up to 2025.

Results

Results show that the number of people with colorectal cancer will continue to rise over the next 24 months. This in turn emphasizes the urgency for public policies aimed at reducing the population's exposure to the principal modifiable risk factors, such as lifestyle and nutrition. In addition, given the major drop in population interest in CRC during the first wave of the COVID-19 pandemic, the findings suggest that public health authorities should implement measures to increase cancer screening rates during pandemics. This in turn would deliver positive externalities, including the mitigation of the global burden and the enhancement of the quality of official statistics.

Influence of phylogenetic diversity of plant communities on tri-trophic interactions

Phylogenetic diversity of plant communities can influence the interaction between plants, herbivores, and their natural enemies. Plant communities with phylogenetically distant species tend to present a wide variety of functional traits and ecological niches, which in turn can influence competitive interactions among plants as well as food and habitat quality for herbivores and their natural enemies. To assess some different mechanisms by which phylogenetic diversity of plant communities can influence herbivores and their natural enemies, we established 12 experimental plots of tropical trees with two treatments: high and low phylogenetic diversity. We measured plant growth and anti-herbivore defenses, herbivore foliar damage, and predator activity in seven species that were present in both treatments. We found significant differences in the expression of plant traits as a function of species identity and their life history, but also depending on the phylogenetic context in which they grew. Pioneer species had higher growth and produced more phenolics in plots with high phylogenetic diversity versus plants in plots with low phylogenetic diversity. Accordingly, herbivore damage in these species was greater in plots with low phylogenetic diversity. Finally, predator activity on caterpillar clay models placed on plants was greater within the low phylogenetic diversity treatment, but only for non-myrmecophytic species. These results suggest that plant phylogenetic diversity can influence the expression of growth and defensive traits and further modify the interaction between plants, herbivores, and their natural enemies. However, such effects depend on plant life history and the presence of mutualistic interaction with ants.

National Evaluation of HIV Service Resource Allocation in Tanzania

Using time-driven activity-based costing (TDABC), we examined resource allocation and costs for HIV services throughout Tanzania at patient and facility levels. This national, cross-sectional analysis of 22 health facilities quantified costs and resources associated with 886 patients receiving care for five HIV services: antiretroviral therapy, prevention of mother-to-child transmission, HIV testing and counseling, voluntary medical male circumcision, and pre-exposure prophylaxis. We also documented total provider-patient interaction time, the cost of services with and without inclusion of consumables, and conducted fixed-effects multivariable regression analyses to examine patient- and facility-level correlates of costs and provider-patient time. Findings showed that resources and costs for HIV care varied significantly throughout Tanzania, including as a function of patient- and facility-level characteristics. While some variation may be preferable (e.g., needier patients received more resources), other areas suggested a lack of equity (e.g., wealthier patients received more provider time) and presented opportunities to optimize care delivery protocols.

Resource allocation of rural institutional elderly care in China's new era: spatial-temporal differences and adaptation development

OBJECTIVES

In the new era of China, to ensure that rural residents can get the corresponding institutional elderly services equally, it is necessary to investigate the current situation of resource allocation of rural institutional elderly care and make corresponding adaptation suggestions.

STUDY DESIGN

This research discusses the characteristics and evolution pattern of rural aging, the resource allocation of rural elderly care institutions, and the adaptation degree of rural institutional elderly care resource and aging.

METHODS

The research methodology consists of the following stages: entropy-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), kernel density estimation, coupling coordination, spatial autocorrelation, and Theil index decomposition.

RESULTS

The degree of aging in rural areas of China is rising, and the whole population has entered a moderate aging society, showing the spatial characteristics of 'high in the east and low in the west'. The resource allocation of rural institutional elderly care in China is at a low level, and the absolute differences among provinces tend to reduce over time, and the overall resource allocation level tends to decline. The provinces that were in the mismatched adaptation relationship in the early stage have improved; however, the number of provinces with mismatched adaptability has continued to increase. The local spatial autocorrelation of resource adaptation verifies that the middle and lower reaches of the Yangtze River as the core form a hot spot, and during the observation period, the spatial agglomeration effect of the core is strengthened. The Theil index decomposition of resource adaptation indicates that the within-group differences between the eastern and western regions is significantly higher than that between the northeastern and central regions.

CONCLUSIONS

First, special attention should be paid to preventing the resource allocation of rural institutional elderly care in the eastern and western regions from falling again. Second, to avoid more and more low-adapted provinces falling into the 'mismatch dilemma' with the deepening of the aging degree. Third, strengthen cooperation among regions and promote the coordinated development of resource allocation of institutional elderly care in various regions. Fourth, the priority of institutional elderly care balanced development should be given to the eastern region and western region, thus weakening the overall difference.

Time of Delivery Contributes to Mortality and Morbidity in Preterm Infants

INTRODUCTION

Knowledge about the time of birth and its impact on premature infants is essential when planning perinatal and neonatal care and resource allocation. We studied the time of birth and its contribution to early death and morbidity in preterm infants.

METHODS

We explored the time and mode of birth of infants with birthweight of <1,500 g and gestational age of <32+0/7 weeks. Additionally, we divided the infants into three groups stratified by their time of birth, i.e., during office hours, evening, and nighttime and assessed associations between these groups and mortality and morbidity.

RESULTS

The study comprised 1,610 infants of whom 156 (10%) died during their stay in neonatal intensive care unit. The highest number of deliveries occurred on Fridays (21%, n = 341/1,610), primarily due to high number of cesarean sections. Deliveries peaked on workdays at 10 a.m. and 2:00 p.m. Mortality was lowest among infants born on Fridays (6%, n = 21/341) and highest on Mondays (13%, n = 28/218). Intraventricular hemorrhage (IVH) (odds ratio [OR]: 1.50, 95% CI: 1.10-2.03, p = 0.010) and necrotizing enterocolitis (NEC) (OR: 2.11, 95% CI: 1.13-3.91, p = 0.019) were more common among infants born at nighttime. These associations attenuated after adjustment for covariates.

CONCLUSION

Deliveries of premature infants peaked on Fridays. Mortality was lower among those born on Fridays, compared with Mondays. Many low-risk deliveries on Fridays may decrease, and the tendency to postpone high-risk deliveries to Mondays, increase the proportional risk of mortality. Indication of higher risk of IVH and NEC among infants born during nighttime may be due to different patient population.

Using decision tree analysis to identify population groups at risk of subjective unmet need for assistance with activities of daily living

BACKGROUND

Identifying predictors of subjective unmet need for assistance with activities of daily living (ADL) is necessary to allocate resources in social care effectively to the most vulnerable populations. In this study, we aimed at identifying population groups at risk of subjective unmet need for assistance with ADL and instrumental ADL (IADL) taking complex interaction patterns between multiple predictors into account.

METHODS

We included participants aged 55 or older from the cross-sectional German Health Update Study (GEDA 2019/2020-EHIS). Subjective unmet need for assistance was defined as needing any help or more help with ADL (analysis 1) and IADL (analysis 2). Analysis 1 was restricted to participants indicating at least one limitation in ADL (N = 1,957). Similarly, analysis 2 was restricted to participants indicating at least one limitation in IADL (N = 3,801). Conditional inference trees with a Bonferroni-corrected type 1 error rate were used to build classification models of subjective unmet need for assistance with ADL and IADL, respectively. A total of 36 variables representing sociodemographics and impairments of body function were used as covariates for both analyses. In addition, the area under the receiver operating characteristics curve (AUC) was calculated for each decision tree.

RESULTS

Depressive symptoms according to the PHQ-8 was the most important predictor of subjective unmet need for assistance with ADL. Further classifiers that were selected from the 36 independent variables were gender identity, employment status, severity of pain, marital status, and educational level according to ISCED-11. The AUC of this decision tree was 0.66. Similarly, depressive symptoms was the most important predictor of subjective unmet need for assistance with IADL. In this analysis, further classifiers were severity of pain, social support according to the Oslo-3 scale, self-reported prevalent asthma, and gender identity (AUC = 0.63).

CONCLUSIONS

Reporting depressive symptoms was the most important predictor of subjective unmet need for assistance among participants with limitations in ADL or IADL. Our findings do not allow conclusions on causal relationships. Predictive performance of the decision trees should be further investigated before conclusions for practice can be drawn.

Economic burden of chronic migraine in OECD countries: a systematic review

BACKGROUND

Chronic migraine (CM) is a significant neurological condition affecting a substantial portion of the global population. The economic burden of CM includes both direct healthcare costs and indirect costs resulting from productivity losses and intangible impacts on patients' quality of life. However, there is limited research that comprehensively evaluates all cost components associated with CM, highlighting the need for a systematic review.

METHODS

We conducted a systematic literature search in databases including MEDLINE, Embase, and CINAHL to identify studies estimating the cost of illness of chronic migraines. The search was restricted to English language articles published from inception to October 2021, and only findings from Organisation for Economic Co-operation and Development (OECD) countries were included. Methodology features and key findings were extracted from the studies, and reported costs were converted to GBP for cross-country comparisons.

RESULTS

Thirteen cost-of-illness studies on CM from various OECD countries were included in this review. The studies demonstrated substantial variations in monetary estimates, but consistently highlighted the considerable economic burden of CM. Direct costs, particularly hospitalisation and medication expenses, were identified as the highest contributors. However, indirect costs, such as productivity losses due to absenteeism and presenteeism, were often underexplored in the reviewed studies. Additionally, intangible costs related to emotional and social impacts on patients were largely overlooked.

CONCLUSION

Chronic migraine imposes a significant economic burden on individuals, healthcare systems, and society. Policymakers and healthcare stakeholders should consider both direct and indirect cost components, as well as intangible costs, in developing targeted strategies for effective CM management and resource allocation. Further research focusing on comprehensive cost assessments and sensitivity analyses is needed to enhance the understanding of CM's economic implications and inform evidence-based healthcare policy decisions. Addressing these research gaps can alleviate the economic burden of CM and improve patient outcomes.

What makes a health system good? From cost-effectiveness analysis to ethical improvement in health systems

Fair allocation of scarce healthcare resources has been much studied within philosophy and bioethics, but analysis has focused on a narrow range of cases. The Covid-19 pandemic provided significant new challenges, making powerfully visible the extent to which health systems can be fragile, and how scarcities within crucial elements of interlinked care pathways can lead to cascading failures. Health system resilience, while previously a key topic in global health, can now be seen to be a vital concern in high-income countries too. Unfortunately, mainstream philosophical approaches to the ethics of rationing and prioritisation provide little guidance for these new problems of scarcity. Indeed, the cascading failures were arguably exacerbated by earlier attempts to make health systems leaner and more efficient. This paper argues that health systems should move from simple and atomistic approaches to measuring effectiveness to approaches that are holistic both in focusing on performance at the level of the health system as a whole, and also in incorporating a wider range of ethical concerns in thinking about what makes a health system good.

Smart city construction and green technology innovation: evidence at China's city level

In the context of China's economic and social transformation, smart cities are becoming increasingly important for green development. Based on pilot smart cities and panel data from 274 prefecture-level cities in China from 2006 to 2018, this paper mainly evaluates the impact of smart city construction (SCC) on green technology innovation (GTI). To analyze SCC mechanisms and heterogeneity, we used China's smart city pilots as a quasi-natural experiment. In terms of the influencing mechanism, SCC can promote GTI by enhancing the digital economy level. Meanwhile, the optimization allocation of resources, including labor, land, and capital, can effectively foster the promoting effect of SCC on GTI. Moreover, SCC has a spatial diffusion effect; it will not only promote local GTI, but also improve the level of GTI in neighboring cities. In terms of the heterogeneity analysis, smart cities, which present a large scales, rich human capital, and high-level infrastructure, have a strongly positive effect on GTI. This study provides important empirical evidence for the development of SCC and GTI.

Developing a combined framework for priority setting in integrated health and social care systems

BACKGROUND

There is an international move towards greater integration of health and social care to cope with the increasing demand on services.. In Scotland, legislation was passed in 2014 to integrate adult health and social care services resulting in the formation of 31 Health and Social Care Partnerships (HSCPs). Greater integration does not eliminate resource scarcity and the requirement to make (resource) allocation decisions to meet the needs of local populations. There are different perspectives on how to facilitate and improve priority setting in health and social care organisations with limited resources, but structured processes at the local level are still not widely implemented. This paper reports on work with new HSCPs in Scotland to develop a combined multi-disciplinary priority setting and resource allocation framework.

METHODS

To develop the combined framework, a scoping review of the literature was conducted to determine the key principles and approaches to priority setting from economics, decision-analysis, ethics and law, and attempts to combine such approaches. Co-production of the combined framework involved a multi-disciplinary workshop including local, and national-level stakeholders and academics to discuss and gather their views.

RESULTS

The key findings from the literature review and the stakeholder workshop were taken to produce a final combined framework for priority setting and resource allocation. This is underpinned by principles from economics (opportunity cost), decision science (good decisions), ethics (justice) and law (fair procedures). It outlines key stages in the priority setting process, including: framing the question, looking at current use of resources, defining options and criteria, evaluating options and criteria, and reviewing each stage. Each of these has further sub-stages and includes a focus on how the combined framework interacts with the consultation and involvement of patients, public and the wider staff.

CONCLUSIONS

The integration agenda for health and social care is an opportunity to develop and implement a combined framework for setting priorities and allocating resources fairly to meet the needs of the population. A key aim of both integration and the combined framework is to facilitate the shifting of resources from acute services to the community.

A simulated heat wave-but not herbicide exposure-alters resource investment strategy in an insect

Animals are increasingly exposed to potential stressors related to environmental change, and multiple stressors may alter the dynamics by which animals acquire resources and invest those resources into important life-history traits. Stress may lead to the prioritization of current reproduction to maximize lifetime reproduction (i.e., terminal investment [TI]) or, in contrast, prioritize somatic investment over current reproduction to facilitate future reproductive opportunities (i.e., reproductive restraint [RR]). Tests of the TI and RR hypotheses typically use immune challenges as stressors, and have not been explicitly tested in the context of environmental change even though warming influences resource allocation patterns across taxa. Further, the multiple-stressor framework has been a useful construct to clarify the costs of complex environmental shifts to animals, but it has not been leveraged to understand such effects on investment strategy. Thus, we tested the TI and RR hypotheses by manipulating widespread features of environmental change-glyphosate-based herbicide (GBH; Roundup®) exposure and a simulated heat wave-in the variable field cricket (Gryllus lineaticeps). A simulated heat wave affected the life-history tradeoff between investment into reproduction and soma. Specifically, heat wave prioritized investment into ovary mass over non-reproductive tissue, even after accounting for food consumption, in support of the TI hypothesis. In contrast, GBH exposure did not affect any measured trait, and crickets did not discriminate between tap water and GBH solution during drinking. Therefore, some-but not all-aspects of environmental change may alter resource investment strategies in animals. We encourage continued integration of the multiple-stressor framework and life-history theory to better understand how animals respond to their rapidly changing environments.

Assessing resource allocation based on workload: a data envelopment analysis study on clinical departments in a class a tertiary public hospital in China

OBJECTIVE

Today, the development mode of public hospitals in China is turning from expansion to efficiency, and the management mode is turning from extensive to refined. This study aims to evaluate the efficiency of clinical departments in a Chinese class A tertiary public hospital (Hospital M) to analyze the allocation of hospital resources among these departments providing a reference for the hospital management.

METHODS

The hospitalization data of inpatients from 32 clinical departments of Hospital M in 2021 are extracted from the hospital information system (HIS), and a dataset containing 38,147 inpatients is got using stratified sampling. Considering the non-homogeneity of clinical departments, the 38,147 patients are clustered using the K-means algorithm based on workload-related data labels including inpatient days, intensive care workload index, nursing workload index, and operation workload index, so that the medical resource consumption of inpatients from non-homogeneous clinical departments can be transformed into the homogeneous workload of medical staff. Taking the numbers of doctors, nurses, and beds as input indicators, and the numbers of inpatients assigned to certain clusters as output indicators, an input-oriented BCC model is built named the workload-based DEA model. Meanwhile, a control DEA model with the number of inpatients and medical revenue as output indicators is built, and the outputs of the two models are compared and analyzed.

RESULTS

Clustering of 38,147 patients into 3 categories is of better interpretability. 14 departments reach DEA efficient in the workload-based DEA model, 10 reach DEA efficient in the control DEA model, and 8 reach DEA efficient in both models. The workload-based DEA model gives a relatively rational judge on the increase of income brought by scale expansion, and evaluates some special departments like Critical Care Medicine Dept., Geriatrics Dept. and Rehabilitation Medicine Dept. more properly, which better adapts to the functional orientation of public hospitals in China.

CONCLUSION

The design of evaluating the efficiency of non-homogeneous clinical departments with the workload as output proposed in this study is feasible, and provides a new idea to quantify professional medical human resources, which is of practical significance for public hospitals to optimize the layout of resources, to provide real-time guidance on manpower grouping strategies, and to estimate the expected output reasonably.

Response Time Improvement in Medical Emergency Departments Through Evolutionary Optimization

Modern Internet connectivity provides the ability to perform efficient communications between the control centre of a healthcare system and the internal management processes of the emergency departments in clinics. Based on this, resource management is improved when exploiting the available efficient connectivity for adapting to the operating state of the system. An efficient order of patient treatment tasks inside the emergency department can reduce in real-time the average treatment time per patient. The motivation to use adaptive methods and specifically evolutionary metaheuristics for this time-sensitive task, is the exploitation of the runtime conditions which may vary according to the patient incoming flow and the severity of each specific case. In this work, an evolutionary method improves the efficiency in the emergency department, according to the dynamically structured treatment task order. Specifically, the average time inside the ED is reduced at a small expense of the execution time. This renders similar methods as candidates for resource-allocating tasks.

A severely fragmented concept: Uncovering citizens' subjective accounts of severity of illness

Universal healthcare is constrained by national governments' finite health resources. This gives rise to complex priority-setting dilemmas. In several universal healthcare systems, the notion of severity (Norwegian: 'alvorlighet') is a key consideration in priority setting, such that treatments for 'severe' illness may be prioritised even when evidence suggests it would not be as cost-effective as treatment options for other conditions. However, severity is a poorly-defined concept, and there is no consensus on what severity means in the context of healthcare provision - whether viewed from public, academic, or professional perspectives. Though several public preference-elicitation studies demonstrate that severity is considered relevant in healthcare resource distribution, there is a paucity of research on public perceptions on the actual meaning of severity. We conducted a Q-methodology study between February 2021 and March 2022 to investigate views on severity amongst general public participants in Norway. Group interviews (n = 59) were conducted to gather statements for the Q-sort ranking exercises (n = 34). Data were analysed using by-person factor analysis to identify patterns in the statement rankings. We present a rich picture of perspectives on the term 'severity', and identify four different, partly conflicting, views on severity in the Norwegian population, with few areas of consensus. We argue that policymakers ought to be made aware of these differing perspectives on severity, and that there is need for further research on the prevalence of these views and on how they are distributed within populations.

Indications, Resource Allocation, and Outcomes Associated with Ex-Utero Intrapartum Treatment Procedures: A North American Fetal Therapy Network Survey

INTRODUCTION

Neonates with cardiorespiratory compromise at delivery are at substantial risk of hypoxic neurologic injury and death. Though mitigation strategies such as ex-utero intrapartum treatment (EXIT) exist, the competing interests of neonatal beneficence, maternal non-maleficence, and just distribution of resources require consideration. Due to the rarity of these entities, there are few systematic data to guide evidence-based standards. This multi-institutional, interdisciplinary approach aims to elucidate the current scope of diagnoses that might be considered for such treatments and examine if treatment allocation and/or outcomes could be improved.

METHODS

After IRB approval, a survey investigating diagnoses appropriate for EXIT consultation and procedure, variables within each diagnosis, occurrence of maternal and neonatal adverse outcomes, and instances of suboptimal resource allocation in the last decade was sent to all North American Fetal Treatment Network center representatives. One response was recorded per center.

RESULTS

We received a 91% response rate and all but one center offer EXIT. Most centers (34/40, 85%) performed 1-5 EXIT consultations per year and 17/40 (42.5%) centers performed 1-5 EXIT procedures in the last 10 years. The diagnoses with the highest degree of agreement between centers surveyed to justify consultation for EXIT are head and neck mass (100%), congenital high airway obstruction (90%), and craniofacial skeletal conditions (82.5%). Maternal adverse outcomes were noted in 7.5% of centers while neonatal adverse outcomes in 27.5%. A large percentage of centers report cases of suboptimal selection for risk mitigation procedures and several centers experienced adverse neonatal and maternal outcomes.

CONCLUSION

This study captures the scope of EXIT indications and is the first to demonstrate the mismatch in resource allocation for this population. Further, it reports on attributable adverse outcomes. Given suboptimal allocation and adverse outcomes, further examination of indications, outcomes, and resource use is justified to drive evidence-based protocols.

Collateral damage: has the COVID-19 pandemic more strongly impacted medical research than other scientific areas?

The principle of resource allocation states that diversion of resources to attend a function may compromise others. The COVID-19 pandemic required a rapid response with a justifiable relocation of equipment, funds and human resources. Based on the ecological principle of allocation, we tested whether the relocation of resources to support COVID-19 research was more detrimental to medical research than to research in other scientific areas. We compared the yearly number of published articles from 2015 to 2021 using disease-related keywords and non-medical scientific keywords. Contrary to the expectation, we found an abrupt reduction in the publication rates in all research areas from 2019 to 2020 or 2021, compared to the pre-pandemic period (2015-2019). The allocation effect on medical research may be overshadowed by stronger effects of the pandemic, or it may become evident in the coming years. The drastic reduction in published papers could have negative consequences for scientific advancements, including understanding and curing diseases other than COVID-19 that strongly affect humanity.

General public's understanding of rare diseases and their opinions on medical resource allocation in Japan: a cross-sectional study

BACKGROUND

Rare diseases (RDs) may impose a considerable financial burden on patients and their families. Public acceptance is essential to ensure sustainable public systems supporting RDs, especially in countries with universal healthcare coverage, such as Japan. This study aimed to explore the public's understanding of RDs and identify crucial factors associated with the public acceptance of prioritizing financial support for RDs in Japan.

METHODS

An online questionnaire was sent to 131,220 Japanese residents aged 20-69 years. The items included in the questionnaire were general interest in medical science and medical care, general knowledge regarding RDs and health care systems, opinions on the cost of medical care, opinions on the research and development of RDs and common diseases, and individual characteristics.

RESULTS

The responses of 11,019 respondents were analyzed. Several respondents agreed to partially cover the medication cost of adult and pediatric RDs (59.5% and 66.8%, respectively) with public funding. The major reasons for agreeing were the huge financial burden imposed on patients and their families, limited available treatment options, effects of RDs on the life planning of patients, and difficulties caused by RDs in the patient's social life. Furthermore, the respondents ranked RDs (56.0%) higher than common diseases (44.0%) for government funding for research and development. The reasons for supporting government-funded research and development for RDs included the lack of treatment options for numerous RDs (34.9%) and difficulty of studying RDs owing to the small number of researchers (25.9%). The chief reasons for supporting government-funded research and development for common diseases were the large number of affected patients (59.7%) and the possibility of more treatment options becoming available through the promotion of research and development (22.1%).

CONCLUSIONS

The general public considers burdens associated with daily living or finance more than the epidemiological characteristics of RD while making funding decisions, demonstrating that rarity was less prioritized. A gap appears to exist between the general public and RD experts regarding the understanding of the epidemiological characteristics of RD and its thresholds. This gap should be bridged to ensure that prioritization of financial support for RDs is accepted by the society.

Matching medical staff to long term care facilities to respond to COVID-19 outbreak

BACKGROUND

Staff shortage is a long-standing issue in long term care facilities (LTCFs) that worsened with the COVID-19 outbreak. Different states in the US have employed various tools to alleviate this issue in LTCFs. We describe the actions taken by the Commonwealth of Massachusetts to assist LTCFs in addressing the staff shortage issue and their outcomes. Therefore, the main question of this study is how to create a central mechanism to allocate severely limited medical staff to healthcare centers during emergencies.

METHODS

For the Commonwealth of Massachusetts, we developed a mathematical programming model to match severely limited available staff with LTCF demand requests submitted through a designed portal. To find feasible matches and prioritize facility needs, we incorporated restrictions and preferences for both sides. For staff, we considered maximum mileage they are willing to travel, available by date, and short- or long-term work preferences. For LTCFs, we considered their demand quantities for different positions and the level of urgency for their demand. As a secondary goal of this study, by using the feedback entries data received from the LTCFs on their matches, we developed statistical models to determine the most salient features that induced the LTCFs to submit feedback.

RESULTS

We used the developed portal to complete about 150 matching sessions in 14 months to match staff to LTCFs in Massachusetts. LTCFs provided feedback for 2,542 matches including 2,064 intentions to hire the matched staff during this time. Further analysis indicated that nursing homes and facilities that entered higher levels of demand to the portal were more likely to provide feedback on the matches and facilities that were prioritized in the matching process due to whole facility testing or low staffing levels were less likely to do so. On the staffing side, matches that involved more experienced staff and staff who can work afternoons, evenings, and overnight were more likely to generate feedback from the facility that they were matched to.

CONCLUSION

Developing a central matching framework to match medical staff to LTCFs at the time of a public health emergency could be an efficient tool for responding to staffing shortages. Such central approaches that help allocate a severely limited resource efficiently during a public emergency can be developed and used for different resource types, as well as provide crucial demand and supply information in different regions and/or demographics.

[Care of the severely injured in mass casualty incidents : What is the difference compared to emergency room management?]

The management of a severely injured patient according to the standards and principles of individualized trauma care is a well-established procedure in many hospitals. The process is structured and standardized by the content of several course formats. In contrast, a mass casualty incident (MCI, MANV) is a rare and exceptional situation. In this case the treatment priorities and approaches are changed. The main aim in this situation is to ensure the best possible chance of survival for every casualty by organizational measures to mobilize rooms, personnel and material and to temporarily abandon the standards of individualized trauma care. To be prepared for a MCl situation it is necessary to know the realistic scenarios, to update the hospital emergency plan and to adapt all treatment procedures to the transient lack of resources. This article gives an overview of this process and summarizes the current clinical concepts to cope with a MCl situation and the current principles for the care of the severely injured involving many casualties.

Unit cost repositories for health program planning and evaluation: a report on research in practice with lessons learned

BACKGROUND

Most low- and middle-income countries have limited access to cost data that meets the needs of health policy-makers and researchers in health intervention areas including HIV, tuberculosis, and immunization. Unit cost repositories (UCRs)-searchable databases that systematically codify evidence from costing studies-have been developed to reduce the effort required to access and use existing costing information. These repositories serve as public resources and standard references, which can improve the consistency and quality of resource needs projections used for strategic planning and resource mobilization. UCRs also enable analysis of cost determinants and more informed imputation of missing cost data. This report examines our experiences developing and using seven UCRs (two global, five country-level) for cost projection and research purposes.

DISCUSSION

We identify advances, challenges, enablers, and lessons learned that might inform future work related to UCRs. Our lessons learned include: (1) UCRs do not replace the need for costing expertise; (2) tradeoffs are required between the degree of data complexity and the useability of the UCR; (3) streamlining data extraction makes populating the UCR with new data easier; (4) immediate reporting and planning needs often drive stakeholder interest in cost data; (5) developing and maintaining UCRs requires dedicated staff time; (6) matching decision-maker needs with appropriate cost data can be challenging; (7) UCRs must have data quality control systems; (8) data in UCRs can become obsolete; and (9) there is often a time lag between the identification of a cost and its inclusion in UCRs.

CONCLUSIONS

UCRs have the potential to be a valuable public good if kept up-to-date with active quality control and adequate support available to end-users. Global UCR collaboration networks and greater control by local stakeholders over global UCRs may increase active, sustained use of global repositories and yield higher quality results for strategic planning and resource mobilization.

Lessons Learned from a Global Perspective of Coronavirus Disease-2019

Coronavirus disease-2019 has impacted the world globally. Countries and health care organizations across the globe responded to this unprecedented public health crisis in a varied manner in terms of public health and social measures, vaccination development and rollout, the conduct of research, developments of therapeutics, sharing of information, and in how they continue to deal with the widespread aftermath. This article reviews the various elements of the global response to the pandemic, focusing on the lessons learned and strategies to consider during future pandemics.