Design and validation of a decision support checklist for efficient resource allocation in research projects during proposal preparation.

PURPOSE: This article presents the design and validation of evaluation criteria checklist aimed at facilitating decision-making processes regarding participation in research projects and allocation of resources before the preparation of research proposals. MATERIALS AND METHODS: A multidisciplinary team developed a comprehensive evaluation focusing on the proposal preparation phase of research projects. A Delphi survey method was used to establish a connection between the relevance of the project and the possible success of research proposals. Assessment criteria were agreed upon, each assigned specific weights. The results of the survey were applied to a database of 62 proposals for which our research group sought funding during 2020-2021. The method was validated using the funding body's outcomes (approval or rejection) of the submitted proposals as the ground truth per project type (national, European and regional). RESULTS: The results of the survey generated a checklist of 8 criteria (excellence, impact, and efficiency aspects) that effectively assess the possibility of success of research proposals during the preparatory phase. For national projects, the tool validation demonstrated a sensitivity of 100% and a specificity of 76.19%; European projects exhibited a sensitivity of 100% and a specificity of 53.84%; and regional projects showed a sensitivity of 80% and a specificity of 30%. CONCLUSIONS: By establishing an agreed set of evaluation criteria, the developed comprehensive index enables a more precise decision support tool for the participation in research proposals and the allocation of necessary resources. This control system saves valuable time and effort for research groups while enhancing the overall efficiency of available resources.

Logical Inconsistencies in the Health Years in Total and Equal Value of Life-Years Gained.

OBJECTIVES: This study aimed to assess whether recently proposed alternatives to the quality-adjusted life-year (QALY), intended to address concerns about discrimination, are suitable for informing resource allocation decisions. METHODS: We consider 2 alternatives to the QALY: the health years in total (HYT), recently proposed by Basu et al, and the equal value of life-years gained (evLYG), currently used by the Institute for Clinical and Economic Review. For completeness we also consider unweighted life-years (LYs). Using a hypothetical example comparing 3 mutually exclusive treatment options, we consider how calculations are performed under each approach and whether the resulting rankings are logically consistent. We also explore some further challenges that arise from the unique properties of the HYT approach. RESULTS: The HYT and evLYG approaches can result in logical inconsistencies that do not arise under the QALY or LY approaches. HYT can violate the independence of irrelevant alternatives axiom, whereas the evLYG can produce an unstable ranking of treatment options. HYT have additional issues, including an implausible assumption that the utilities associated with health-related quality of life and LYs are "separable," and a consideration of "counterfactual" health-related quality of life for patients who are dead. CONCLUSIONS: The HYT and evLYG approaches can result in logically inconsistent decisions. We recommend that decision makers avoid these approaches and that the logical consistency of any approaches proposed in future be thoroughly explored before considering their use in practice.

Barriers and facilitators to implementing priority setting and resource allocation tools in hospital decisions: A systematic review.

Health care budgets in high-income countries are having issues coping with unsustainable growth in demand, particularly in the hospital setting. Despite this, implementing tools systematising priority setting and resource allocation decisions has been challenging. This study answers two questions: (1) what are the barriers and facilitators to implementing priority setting tools in the hospital setting of high-income countries? and (2) what is their fidelity? A systematic review using the Cochrane methods was conducted including studies of hospital-related priority setting tools reporting barriers or facilitators for implementation, published after the year 2000. Barriers and facilitators were classified using the Consolidated Framework for Implementation Research (CFIR). Fidelity was assessed using priority setting tool's standards. Out of thirty studies, ten reported program budgeting and marginal analysis (PBMA), twelve multi-criteria decision analysis (MCDA), six health technology assessment (HTA) related frameworks, and two, an ad hoc tool. Barriers and facilitators were outlined across all CFIR domains. Implementation factors not frequently observed, such as 'evidence of previous successful tool application', 'knowledge and beliefs about the intervention' or 'external policy and incentives' were reported. Conversely, some constructs did not yield any barrier or facilitator including 'intervention source' or 'peer pressure'. PBMA studies satisfied the fidelity criteria between 86% and 100%, for MCDA it varied between 36% and 100%, and for HTA it was between 27% and 80%. However, fidelity was not related to implementation. This study is the first to use an implementation science approach. Results represent the starting point for organisations wishing to use priority setting tools in the hospital setting by providing an overview of barriers and facilitators. These factors can be used to assess readiness for implementation or to serve as the foundation for process evaluations. Through our findings, we aim to improve the uptake of priority setting tools and support their sustainable use.

Procedure dependence in resource allocations: How focusing on resource or target affects variety-seeking.

Many resource allocation tasks involve the assignment of multiple units of a resource (e.g., money, time, labor) to multiple targets (e.g., stocks, expenditure categories, projects to be carried out). The decision-maker can either focus on the individual targets and decide how many resource units each target should receive (allocation-by-target), or focus on the individual resource units and decide which target each unit should be assigned to (allocation-by-unit). We suggest that the two allocation procedures might result in different outcomes. Specifically, we predict that the allocation-by-unit procedure leads to more variety-seeking than the allocation-by-target procedure. Nine experiments (N = 4,152) provided evidence consistent with this procedure dependence hypothesis. We further demonstrate that the effect occurs because the allocation-by-target procedure encourages people to consider the differences between targets whereas the allocation-by-unit procedure induces people to focus more on each undifferentiated unit. As a result, allocation-by-target, relative to allocation-by-unit, leads to a lower variety-seeking, which manifests as a more concentrated distribution of the resource units across the targets. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Influence of broader geographic allograft sharing on outcomes and cost in smaller lung transplant centers.

OBJECTIVE: On November 24, 2017, Organ Procurement and Transplantation Network implemented a change to lung allocation replacing donor service area with a 250 nautical mile radius around donor hospitals. We sought to evaluate the experience of a small to medium size center following implementation. METHODS: Patients (47 pre and 54 post) undergoing lung transplantation were identified from institutional database from January 2016 to October 2019. Detailed chart review and analysis of institutional cost data was performed. Univariate analysis was performed to compare eras. RESULTS: Similar short-term mortality and primary graft dysfunction were observed between groups. Decreased local donation (68% vs 6%; P < .001), increased travel distance (145 vs 235 miles; P = .004), travel cost ($8626 vs $14,482; P < .001), and total procurement cost ($60,852 vs $69,052; P = .001) were observed postimplementation. We also document an increase in waitlist mortality postimplementation (6.9 vs 31.6 per 100 patient-years; P < .001). CONCLUSIONS: Following implementation of the new allocation policy in a small to medium size center, several changes were in accordance with policy intention. However, concerning shifts emerged, including increased waitlist mortality and resource utilization. Continued close monitoring of transplant centers stratified by size and location are paramount to maintaining global availability of lung transplantation to all Americans regardless of geographic residence or socioeconomic status.

A framework to support the integration of priority setting in the preparedness, alert, control and evaluation stages of a disease pandemic.

The COVID-19 pandemic, where the need-resource gap has necessitated decision makers in some contexts to ration access to life-saving interventions, has demonstrated the critical need for systematic and fair priority setting and resource allocation mechanisms. Disease outbreaks are becoming increasingly common and priority setting lessons from previous disease outbreaks could be better harnessed to inform decision making and planning for future disease outbreaks. The purpose of this paper is to discuss how priority setting and resource allocation could, ideally, be integrated into the WHO pandemic planning and preparedness framework and used to inform the COVID-19 pandemic recovery plans and plans for future outbreaks. Priority setting and resource allocation during disease outbreaks tend to evoke a process similar to the 'rule of rescue'. This results in inefficient and unfair resource allocation, negative effects on health and non-health programs and increased health inequities. Integrating priority setting and resource allocation activities throughout the four phases of the WHO emergency preparedness framework could ensure that priority setting during health emergencies is systematic, evidence informed and fair.

Why enterprise resource planning initiatives do succeed in the long run: A case-based causal network.

Despite remarkable academic efforts, why Enterprise Resource Planning (ERP) post-implementation success occurs still remains elusive. A reason for this shortage may be the insufficient addressing of an ERP-specific interior boundary condition, i.e., the multi-stakeholder perspective, in explaining this phenomenon. This issue may entail a gap between how ERP success is supposed to occur and how ERP success may actually occur, leading to theoretical inconsistency when investigating its causal roots. Through a case-based, inductive approach, this manuscript presents an ERP success causal network that embeds the overlooked boundary condition and offers a theoretical explanation of why the most relevant observed causal relationships may occur. The results provide a deeper understanding of the ERP success causal mechanisms and informative managerial suggestions to steer ERP initiatives towards long-haul success.

Adequate emergency department resource usage: Applying simulation-based workshop to improve teaching competence among elementary and junior high school teachers in Taiwan.

INTRODUCTION: More than 80% of patients who visited Emergency Department (ED) was not urgent in Taiwan in 2019. It causes insufficient medical services and a latent fiscal threat to the Nation Health Insurance (NHI). This study adopted simulation-based educating modules to explore the effect in teaching competence among primary and middle school teachers for efficient AEDRU (adequate emergency department resource usage) education in the future. METHOD: The subjects were 414 elementary and junior high school teachers in Taiwan. 214 participants attended the simulation-based workshop as the simulation-based group, whereas 200 participants took an online self-learning module as the self-learning group. The workshop was created by an expert panel for decreasing the unnecessary usage amount of ED medial resources. The materials are lecture, board games, miniature ED modules, and simulation-based scenarios. A teaching competence questionnaire including ED knowledge, teaching attitude, teaching skills, and teaching self-efficacy was conducted among participants before and after the intervention. Data were analyzed via McNemar, paired t test and the generalized estimating equations (GEE). RESULTS: The study showed that teachers who participated in the simulation-based workshop had improved more in teaching competence than those who received the online self-learning module. In addition, there were significant differences between the pre-test and post-test among the two groups in teaching competence. CONCLUSION: The simulation-based workshop is effective and it should be spread out. When students know how to use ED medical resources properly, they could affect their families. It can help the ED service to be used properly and benefits the finance of the NHI. The health care cost will be managed while also improving health.

Predicting Hospital Resource Use During COVID-19 Surges: A Simple but Flexible Discretely Integrated Condition Event Simulation of Individual Patient-Hospital Trajectories.

OBJECTIVES: To assist with planning hospital resources, including critical care (CC) beds, for managing patients with COVID-19. METHODS: An individual simulation was implemented in Microsoft Excel using a discretely integrated condition event simulation. Expected daily cases presented to the emergency department were modeled in terms of transitions to and from ward and CC and to discharge or death. The duration of stay in each location was selected from trajectory-specific distributions. Daily ward and CC bed occupancy and the number of discharges according to care needs were forecast for the period of interest. Face validity was ascertained by local experts and, for the case study, by comparing forecasts with actual data. RESULTS: To illustrate the use of the model, a case study was developed for Guy's and St Thomas' Trust. They provided inputs for January 2020 to early April 2020, and local observed case numbers were fit to provide estimates of emergency department arrivals. A peak demand of 467 ward and 135 CC beds was forecast, with diminishing numbers through July. The model tended to predict higher occupancy in Level 1 than what was eventually observed, but the timing of peaks was quite close, especially for CC, where the model predicted at least 120 beds would be occupied from April 9, 2020, to April 17, 2020, compared with April 7, 2020, to April 19, 2020, in reality. The care needs on discharge varied greatly from day to day. CONCLUSIONS: The DICE simulation of hospital trajectories of patients with COVID-19 provides forecasts of resources needed with only a few local inputs. This should help planners understand their expected resource needs.

EEG beta-modulations reflect age-specific motor resource allocation during dual-task walking.

The parallel execution of two motor tasks can lead to performance decrements in either one or both of the tasks. Age-related declines can further magnify the underlying competition for cognitive resources. However, little is known about the neural dynamics underlying motor resource allocation during dual-task walking. To better understand motor resource conflicts, this study investigated sensorimotor brain rhythms in younger and older adults using a dual-task protocol. Time-frequency data from two independent component motor clusters were extracted from electroencephalography data during sitting and walking with an additional task requiring manual responses. Button press-related desynchronization in the alpha and beta frequency range were analyzed for the impact of age (< 35 years, ≥ 70 years) and motor task (sitting, walking). Button press-related desynchronization in the beta band was more pronounced for older participants and both age groups demonstrated less pronounced desynchronizations in both frequency bands during walking compared to sitting. Older participants revealed less power modulations between sitting and walking, and less pronounced changes in beta and alpha suppression were associated with greater slowing in walking speed. Our results indicate age-specific allocations strategies during dual-task walking as well as interdependencies of concurrently performed motor tasks reflected in modulations of sensorimotor rhythms.

Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing.

The purposes are to improve the server deployment capability under Mobile Edge Computing (MEC), reduce the time delay and energy consumption of terminals during task execution, and improve user service quality. After the server deployment problems under traditional edge computing are analyzed and researched, a task resource allocation model based on multi-stage is proposed to solve the communication problem between different supporting devices. This model establishes a combined task resource allocation and task offloading method and optimizes server execution by utilizing the time delay and energy consumption required for task execution and comprehensively considering the restriction processes of task offloading, partition, and transmission. For the MEC process that supports dense networks, a multi-hybrid intelligent algorithm based on energy consumption optimization is proposed. The algorithm converts the original problem into a power allocation problem via a heuristic model. Simultaneously, it determines the appropriate allocation strategy through distributed planning, duality, and upper bound replacement. Results demonstrate that the proposed multi-stage combination-based service deployment optimization model can solve the problem of minimizing the maximum task execution energy consumption combined with task offloading and resource allocation effectively. The algorithm has good performance in handling user fairness and the worst-case task execution energy consumption. The proposed hybrid intelligent algorithm can partition tasks into task offloading sub-problems and resource allocation sub-problems, meeting the user's task execution needs. A comparison with the latest algorithm also verifies the model's performance and effectiveness. The above results can provide a theoretical basis and some practical ideas for server deployment and applications under MEC.

Validation of a Crisis Standards of Care Model for Prioritization of Limited Resources During the Coronavirus Disease 2019 Crisis in an Urban, Safety-Net, Academic Medical Center.

OBJECTIVES: The coronavirus disease 2019 pandemic has overwhelmed healthcare resources even in wealthy nations, necessitating rationing of limited resources without previously established crisis standards of care protocols. In Massachusetts, triage guidelines were designed based on acute illness and chronic life-limiting conditions. In this study, we sought to retrospectively validate this protocol to cohorts of critically ill patients from our hospital. DESIGN: We applied our hospital-adopted guidelines, which defined severe and major chronic conditions as those associated with a greater than 50% likelihood of 1- and 5-year mortality, respectively, to a critically ill patient population. We investigated mortality for the same intervals. SETTING: An urban safety-net hospital ICU. PATIENTS: All adults hospitalized during April of 2015 and April 2019 identified through a clinical database search. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 365 admitted patients, 15.89% had one or more defined chronic life-limiting conditions. These patients had higher 1-year (46.55% vs 13.68%; p < 0.01) and 5-year (50.00% vs 17.22%; p < 0.01) mortality rates than those without underlying conditions. Irrespective of classification of disease severity, patients with metastatic cancer, congestive heart failure, end-stage renal disease, and neurodegenerative disease had greater than 50% 1-year mortality, whereas patients with chronic lung disease and cirrhosis had less than 50% 1-year mortality. Observed 1- and 5-year mortality for cirrhosis, heart failure, and metastatic cancer were more variable when subdivided into severe and major categories. CONCLUSIONS: Patients with major and severe chronic medical conditions overall had 46.55% and 50.00% mortality at 1 and 5 years, respectively. However, mortality varied between conditions. Our findings appear to support a crisis standards protocol which focuses on acute illness severity and only considers underlying conditions carrying a greater than 50% predicted likelihood of 1-year mortality. Modifications to the chronic lung disease, congestive heart failure, and cirrhosis criteria should be refined if they are to be included in future models.

Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation.

COVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke's hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

Development and Validation of a Hospital Indicator of Activity-Based Costs for Injury Admissions.

OBJECTIVES: To develop a hospital indicator of resource use for injury admissions. METHODS: We focused on resource use for acute injury care and therefore adopted a hospital perspective. We included patients ≥16 years old with an Injury Severity Score >9 admitted to any of the 57 trauma centers of an inclusive Canadian trauma system from 2014 to 2018. We extracted data from the trauma registry and hospital financial reports and estimated resource use with activity-based costing. We developed risk-adjustment models by trauma center designation level (I/II and III/IV) for the whole sample, traumatic brain injuries, thoraco-abdominal injuries, orthopedic injuries, and patients ≥65 years old. Candidate variables were selected using bootstrap resampling. We performed benchmarking by comparing the adjusted mean cost in each center, obtained using shrinkage estimates, to the provincial mean. RESULTS: We included 38 713 patients. The models explained between 12% and 36% (optimism-corrected r2) of the variation in resource use. In the whole sample and in all subgroups, we identified centers with higher- or lower-than-expected resource use across level I/II and III/IV centers. CONCLUSIONS: We propose an algorithm to produce the indicator using data routinely collected in trauma registries to prompt targeted exploration of potential areas for improvement in resource use for injury admissions. The r2 of our models suggest that between 64% and 88% of the variation in resource use for injury care is dictated by factors other than patient baseline risk.

Assessment of Disparities Associated With a Crisis Standards of Care Resource Allocation Algorithm for Patients in 2 US Hospitals During the COVID-19 Pandemic.

Importance: Significant concern has been raised that crisis standards of care policies aimed at guiding resource allocation may be biased against people based on race/ethnicity. Objective: To evaluate whether unanticipated disparities by race or ethnicity arise from a single institution's resource allocation policy. Design, Setting, and Participants: This cohort study included adults (aged ≥18 years) who were cared for on a coronavirus disease 2019 (COVID-19) ward or in a monitored unit requiring invasive or noninvasive ventilation or high-flow nasal cannula between May 26 and July 14, 2020, at 2 academic hospitals in Miami, Florida. Exposures: Race (ie, White, Black, Asian, multiracial) and ethnicity (ie, non-Hispanic, Hispanic). Main Outcomes and Measures: The primary outcome was based on a resource allocation priority score (range, 1-8, with 1 indicating highest and 8 indicating lowest priority) that was assigned daily based on both estimated short-term (using Sequential Organ Failure Assessment score) and longer-term (using comorbidities) mortality. There were 2 coprimary outcomes: maximum and minimum score for each patient over all eligible patient-days. Standard summary statistics were used to describe the cohort, and multivariable Poisson regression was used to identify associations of race and ethnicity with each outcome. Results: The cohort consisted of 5613 patient-days of data from 1127 patients (median [interquartile range {IQR}] age, 62.7 [51.7-73.7]; 607 [53.9%] men). Of these, 711 (63.1%) were White patients, 323 (28.7%) were Black patients, 8 (0.7%) were Asian patients, and 31 (2.8%) were multiracial patients; 480 (42.6%) were non-Hispanic patients, and 611 (54.2%) were Hispanic patients. The median (IQR) maximum priority score for the cohort was 3 (1-4); the median (IQR) minimum score was 2 (1-3). After adjustment, there was no association of race with maximum priority score using White patients as the reference group (Black patients: incidence rate ratio [IRR], 1.00; 95% CI, 0.89-1.12; Asian patients: IRR, 0.95; 95% CI. 0.62-1.45; multiracial patients: IRR, 0.93; 95% CI, 0.72-1.19) or of ethnicity using non-Hispanic patients as the reference group (Hispanic patients: IRR, 0.98; 95% CI, 0.88-1.10); similarly, no association was found with minimum score for race, again with White patients as the reference group (Black patients: IRR, 1.01; 95% CI, 0.90-1.14; Asian patients: IRR, 0.96; 95% CI, 0.62-1.49; multiracial patients: IRR, 0.81; 95% CI, 0.61-1.07) or ethnicity, again with non-Hispanic patients as the reference group (Hispanic patients: IRR, 1.00; 95% CI, 0.89-1.13). Conclusions and Relevance: In this cohort study of adult patients admitted to a COVID-19 unit at 2 US hospitals, there was no association of race or ethnicity with the priority score underpinning the resource allocation policy. Despite this finding, any policy to guide altered standards of care during a crisis should be monitored to ensure equitable distribution of resources.

The influence of the U.S. response to COVID-19 in Global Health. / A influência da resposta dos EUA à COVID-19 no contexto da Saúde Global.

The American response to the pandemic involves a prominent volume of federal resources, especially for developing and acquiring products for internal use, such as diagnostics or vaccines. Investment mechanisms and historical aspects justify this expenditure. Thus, the social construction of nationalism in American society hinders access to health technologies. The review of such aspects shows how the United States (U.S.) secured a large number of potential products, ensuring excessive local production. This unilateral foreign policy has influenced other countries or regional blocs and undermined global cooperation and solidarity, affecting the collective health of several nations.

A resposta americana à pandemia envolve um proeminente volume de recursos federais, em especial destinados ao desenvolvimento e aquisição de produtos no uso interno, como diagnósticos ou vacinas. As justificativas para esse desembolso se baseiam em mecanismos de investimentos e aspectos históricos. Assim, a construção social do nacionalismo na formação na sociedade americana prejudica o acesso a tecnologias em saúde. A revisão desses aspectos demonstra como os Estados Unidos (EUA) garantiram compra de grande quantitativo de produtos em potencial, inclusive assegurando excessiva produção local. Essa política externa unilateral tem influenciado outros países ou blocos regionais e prejudicado a cooperação e a solidariedade global com impacto na saúde coletiva de diversas nações.

Increased SARS-CoV-2 Testing Capacity with Pooled Saliva Samples.

We analyzed feasibility of pooling saliva samples for severe acute respiratory syndrome coronavirus 2 testing and found that sensitivity decreased according to pool size: 5 samples/pool, 7.4% reduction; 10 samples/pool, 11.1%; and 20 samples/pool, 14.8%. When virus prevalence is >2.6%, pools of 5 require fewer tests; when <0.6%, pools of 20 support screening strategies.

COVID-19 in aged care homes: a comparison of effects initial government policies had in the UK (primarily focussing on England) and Australia during the first wave.

BACKGROUND: COVID-19 pandemic has had a major impact globally, with older people living in aged care homes suffering high death rates. OBJECTIVES: We aimed to compare the impact of initial government policies on this vulnerable older population between the UK and Australia during the first wave of attack. METHODS: We searched websites of governments in the UK and Australia and media outlets. We examined the key policies including the national lockdown dates and the distribution of some important resources (personal protective equipment and testing) and the effects of these initial policies on the mortality rates in the aged care homes during the first wave of attack of COVID-19. RESULTS: We found that both countries had prioritized resources to hospitals over aged care homes during the first wave of attack. Both countries had lower priority for aged care residents in hospitals (e.g. discharging without testing for COVID-19 or discouraging admissions). However, deaths in aged care homes were 270 times higher in the UK than in Australia as on 7 May 2020 (despite UK having a population only 2.5 times larger than Australia). The lower fatality rate in Australia may have been due to the earlier lockdown strategy when the total daily cases were low in Australia (118) compared to the UK (over 1000), as well as the better community viral testing regime in Australia. CONCLUSION: In conclusion, the public health policy in Australia aimed towards earlier intervention with earlier national lockdown and more viral testing to prevent new cases. This primary prevention could have resulted in more lives being saved. In contrast, the initial policy in the UK focussed mainly on protecting resources for hospitals, and there was a delay in national lockdown intervention and lower viral testing rate, resulting in more lives lost in the aged care sector.