Excess mortality in England and Wales during the first wave of the COVID-19 pandemic

Background: Deaths during the COVID-19 pandemic result directly from infection and exacerbation of other diseases and indirectly from deferment of care for other conditions, and are socially and geographically patterned. We quantified excess mortality in regions of England and Wales during the pandemic, for all causes and for non-COVID-19-associated deaths. Methods: Weekly mortality data for 1 January 2010 to 1 May 2020 for England and Wales were obtained from the Office of National Statistics. Mean-dispersion negative binomial regressions were used to model death counts based on pre-pandemic trends and exponentiated linear predictions were subtracted from: (i) all-cause deaths and (ii) all-cause deaths minus COVID-19 related deaths for the pandemic period (week starting 7 March, to week ending 8 May). Findings: Between 7 March and 8 May 2020, there were 47 243 (95% CI: 46 671 to 47 815) excess deaths in England and Wales, of which 9948 (95% CI: 9376 to 10 520) were not associated with COVID-19. Overall excess mortality rates varied from 49 per 100 000 (95% CI: 49 to 50) in the South West to 102 per 100 000 (95% CI: 102 to 103) in London. Non-COVID-19 associated excess mortality rates ranged from −1 per 100 000 (95% CI: −1 to 0) in Wales (ie, mortality rates were no higher than expected) to 26 per 100 000 (95% CI: 25 to 26) in the West Midlands. Interpretation: The COVID-19 pandemic has had markedly different impacts on the regions of England and Wales, both for deaths directly attributable to COVID-19 infection and for d

Using electronic health records to predict costs and outcomes in stable coronary artery disease

OBJECTIVES: To use electronic health records (EHR) to predict lifetime costs and health outcomes of patients with stable coronary artery disease (stable-CAD) stratified by their risk of future cardiovascular events, and to evaluate the cost-effectiveness of treatments targeted at these populations. METHODS: The analysis was based on 94 966 patients with stable-CAD in England between 2001 and 2010, identified in four prospectively collected, linked EHR sources. Markov modelling was used to estimate lifetime costs and quality-adjusted life years (QALYs) stratified by baseline cardiovascular risk. RESULTS: For the lowest risk tenth of patients with stable-CAD, predicted discounted remaining lifetime healthcare costs and QALYs were £62 210 (95% CI £33 724 to £90 043) and 12.0 (95% CI 11.5 to 12.5) years, respectively. For the highest risk tenth of the population, the equivalent costs and QALYs were £35 549 (95% CI £31 679 to £39 615) and 2.9 (95% CI 2.6 to 3.1) years, respectively. A new treatment with a hazard reduction of 20% for myocardial infarction, stroke and cardiovascular disease death and no side-effects would be cost-effective if priced below £72 per year for the lowest risk patients and £646 per year for the highest risk patients. CONCLUSIONS: Existing EHRs may be used to estimate lifetime healthcare costs and outcomes of patients with stable-CAD. The stable-CAD model developed in this study lends itself to informing decisions about commissioning, pricing and reimbursement. At current prices, to be cost-effective some established as well as future stable-CAD treatments may require stratification by patient risk

Long-term healthcare use and costs in patients with stable coronary artery disease: a population-based cohort using linked health records (CALIBER)

AIMS: To examine long-term healthcare utilization and costs of patients with stable coronary artery disease (SCAD). METHODS AND RESULTS: Linked cohort study of 94 966 patients with SCAD in England, 1 January 2001 to 31 March 2010, identified from primary care, secondary care, disease, and death registries. Resource use and costs, and cost predictors by time and 5-year cardiovascular disease (CVD) risk profile were estimated using generalized linear models. Coronary heart disease hospitalizations were 20.5% in the first year and 66% in the year following a non-fatal (myocardial infarction, ischaemic or haemorrhagic stroke) event. Mean healthcare costs were £3133 per patient in the first year and £10 377 in the year following a non-fatal event. First-year predictors of cost included sex (mean cost £549 lower in females), SCAD diagnosis (non-ST-elevation myocardial infarction cost £656 more than stable angina), and co-morbidities (heart failure cost £657 more per patient). Compared with lower risk patients (5-year CVD risk 3.5%), those of higher risk (5-year CVD risk 44.2%) had higher 5-year costs (£23 393 vs. £9335) and lower lifetime costs (£43 020 vs. £116 888). CONCLUSION: Patients with SCAD incur substantial healthcare utilization and costs, which varies and may be predicted by 5-year CVD risk profile. Higher risk patients have higher initial but lower lifetime costs than lower risk patients as a result of shorter life expectancy. Improved cardiovascular survivorship among an ageing CVD population is likely to require stratified care in anticipation of the burgeoning demand

Lessons learned and lessons missed: impact of the coronavirus disease 2019 (COVID-19) pandemic on all-cause mortality in 40 industrialised countries and US states prior to mass vaccination [version 2; peer review: 2 approved]

Background: Industrialised countries had varied responses to the COVID-19 pandemic, which may lead to different death tolls from COVID-19 and other diseases. Methods: We applied an ensemble of 16 Bayesian probabilistic models to vital statistics data to estimate the number of weekly deaths if the pandemic had not occurred for 40 industrialised countries and US states from mid-February 2020 through mid-February 2021. We subtracted these estimates from the actual number of deaths to calculate the impacts of the pandemic on all-cause mortality. Results: Over this year, there were 1,410,300 (95% credible interval 1,267,600-1,579,200) excess deaths in these countries, equivalent to a 15% (14-17) increase, and 141 (127-158) additional deaths per 100,000 people. In Iceland, Australia and New Zealand, mortality was lower than would be expected in the absence of the pandemic, while South Korea and Norway experienced no detectable change. The USA, Czechia, Slovakia and Poland experienced >20% higher mortality. Within the USA, Hawaii experienced no detectable change in mortality and Maine a 5% increase, contrasting with New Jersey, Arizona, Mississippi, Texas, California, Louisiana and New York which experienced >25% higher mortality. Mid-February to the end of May 2020 accounted for over half of excess deaths in Scotland, Spain, England and Wales, Canada, Sweden, Belgium, the Netherlands and Cyprus, whereas mid-September 2020 to mid-February 2021 accounted for >90% of excess deaths in Bulgaria, Croatia, Czechia, Hungary, Latvia, Montenegro, Poland, Slovakia and Slovenia. In USA, excess deaths in the northeast were driven mainly by the first wave, in southern and southwestern states by the summer wave, and in the northern plains by the post-September period. Conclusions: Prior to widespread vaccine-acquired immunity, minimising the overall death toll of the pandemic requires policies and non-pharmaceutical interventions that delay and reduce infections, effective treatments for infected patients, and mechanisms to continue routine health care

HTA – algorithm or process? Comment on ‘Expanded HTA: enhancing fairness and legitimacy’

Daniels, Porteny and Urrutia et al make a good case for the idea that that public decisions ought to be made not only “in the light of ” evidence but also “on the basis of ” budget impact, financial protection and equity. Health technology assessment (HTA) should, they say, be accordingly expanded to consider matters additional to safety and cost-effectiveness. They also complain that most HTA reports fail to develop ethical arguments and generally do not even mention ethical issues. This comment argues that some of these defects are more apparent than real and are not inherent in HTA – as distinct from being common characteristics found in poorly conducted HTAs. More generally, HTA does not need “extension” since (1) ethical issues are already embedded in HTA processes, not least in their scoping phases, and (2) HTA processes are already sufficiently flexible to accommodate evidence about a wide range of factors, and will not need fundamental change in order to accommodate the new forms of decision-relevant evidence about distributional impact and financial protection that are now starting to emerge. HTA and related techniques are there to support decision-makers who have authority to make decisions. Analysts like us are there to support and advise them (and not to assume the responsibilities for which they, and not we, are accountable). The required quality in HTA then becomes its effectiveness as a means of addressing the issues of concern to decisionmakers. What is also required is adherence by competent analysts to a standard template of good analytical practice. The competencies include not merely those of the usual disciplines (particularly biostatistics, cognitive psychology, health economics, epidemiology, and ethics) but also the imaginative and interpersonal skills for exploring the “real” question behind the decision-maker’s brief (actual or postulated) and eliciting the social values that necessarily pervade the entire analysis. The product of such exploration defines the authoritative scope of an HTA

Distributional cost-effectiveness analysis in low- and middle-income countries: illustrative example of rotavirus vaccination in Ethiopia

Reducing health inequality is a major policy concern for low- and middle-income countries (LMICs) on the path to universal health coverage. However, health inequality impacts are rarely quantified in cost-effectiveness analyses of health programmes. Distributional cost-effectiveness analysis (DCEA) is a method developed to analyse the expected social distributions of costs and health benefits, and the potential trade-offs that may exist between maximising total health and reducing health inequality. This is the first paper to show how DCEA can be applied in LMICs. Using the introduction of rotavirus vaccination in Ethiopia as an illustrative example, we analyse a hypothetical re-designed vaccination programme, which invests additional resources into vaccine delivery in rural areas, and compare this with the standard programme currently implemented in Ethiopia. We show that the re-designed programme has an incremental cost-effectiveness ratio of US$69 per health-adjusted life year (HALY) compared with the standard programme. This is potentially cost-ineffective when compared with current estimates of health opportunity cost in Ethiopia. However, rural populations are typically less wealthy than urban populations and experience poorer lifetime health. Prioritising such populations can thus be seen as being equitable. We analyse the trade-off between cost-effectiveness and equity using the Atkinson inequality aversion parameter, ε , representing the decision maker’s strength of concern for reducing health inequality. We find that the more equitable programme would be considered worthwhile by a decision maker whose inequality concern is greater than ε = 5.66, which at current levels of health inequality in Ethiopia implies that health gains are weighted at least 3.86 times more highly in the poorest compared with the richest wealth quintile group. We explore the sensitivity of this conclusion to a range of assumptions and cost-per-HALY threshold values, to illustrate how DCEA can inform the thinking of decision makers and stakeholders about health equity trade-offs

WHO decides what is fair? International HIV treatment guidelines, social value judgements and equitable provision of lifesaving antiretroviral therapy

The new 2013 WHO Consolidated Guidelines on the Use of Antiretroviral Therapy (ART) make aspirational recommendations for ART delivery in low and middle income countries. Comprehensive assessments of available evidence were undertaken and the recommendations made are likely to improve individual health outcomes. However feasibility was downplayed, the Guidelines represent high-cost policy options not all of which are compatible with the core public health principles of decentralization; task-shifting; and a commitment to universality. Critically, their impact on equity and the population-level distribution of health outcomes were not fully considered. We analyze the likely distribution of health outcomes resulting from alternative ways of realising the 2013 Guidelines and assess practicality, feasibility and health attainment amongst different sections of the population in the context of financial and human resource constraints. Claim can be made that direct interpretation of the Guidelines follows a "human rights" based approach in seeking to provide individual patients with the best alternatives amongst those available on the basis of current evidence. However, there lies a basic conflict between this and "consequentialist" public health based approaches that provide more equal population-level outcomes. When determining how to respond to the 2013 Guidelines and fairly allocate scarce lifesaving resources, national policymakers must carefully consider the distribution of outcomes and the underpinning social value judgements required to inform policy choice. It is important to consider whose values should determine what is a just distribution of health outcomes. The WHO Guidelines committees are well placed to compile evidence on the costs and effects of health care alternatives. However, their mandate for making distributional social value judgements remains unclear

Primary care and health inequality : Difference-in-difference study comparing England and Ontario

BACKGROUND: It is not known whether equity-oriented primary care investment that seeks to scale up the delivery of effective care in disadvantaged communities can reduce health inequality within high-income settings that have pre-existing universal primary care systems. We provide some non-randomised controlled evidence by comparing health inequality trends between two similar jurisdictions-one of which implemented equity-oriented primary care investment in the mid-to-late 2000s as part of a cross-government strategy for reducing health inequality (England), and one which invested in primary care without any explicit equity objective (Ontario, Canada). METHODS: We analysed whole-population data on 32,482 neighbourhoods (with mean population size of approximately 1,500 people) in England, and 18,961 neighbourhoods (with mean population size of approximately 700 people) in Ontario. We examined trends in mortality amenable to healthcare by decile groups of neighbourhood deprivation within each jurisdiction. We used linear models to estimate absolute and relative gaps in amenable mortality between most and least deprived groups, considering the gradient between these extremes, and evaluated difference-in-difference comparisons between the two jurisdictions. RESULTS: Inequality trends were comparable in both jurisdictions from 2004-6 but diverged from 2007-11. Compared with Ontario, the absolute gap in amenable mortality in England fell between 2004-6 and 2007-11 by 19.8 per 100,000 population (95% CI: 4.8 to 34.9); and the relative gap in amenable mortality fell by 10 percentage points (95% CI: 1 to 19). The biggest divergence occurred in the most deprived decile group of neighbourhoods. DISCUSSION: In comparison to Ontario, England succeeded in reducing absolute socioeconomic gaps in mortality amenable to healthcare from 2007 to 2011, and preventing them from growing in relative terms. Equity-oriented primary care reform in England in the mid-to-late 2000s may have helped to reduce socioeconomic inequality in health, though other explanations for this divergence are possible and further research is needed on the specific causal mechanisms

Correction to: Which Costs Matter? Costs Included in Economic Evaluation and their Impact on Decision Uncertainty for Stable Coronary Artery Disease

Background: Variation exists in the resource categories included in economic evaluations, and National Institute for Health and Care Excellence (NICE) guidance suggests the inclusion only of costs related to the index condition or intervention. However, there is a growing consensus that all healthcare costs should be included in economic evaluations for Health Technology Assessments (HTAs), particularly those related to extended years of life. Objective and Methods: We aimed to quantify the impact of a range of cost categories on the adoption decision about a hypothetical intervention, and uncertainty around that decision, for stable coronary artery disease (SCAD) based on a dataset comprising 94,966 patients. Three costing scenarios were considered: coronary heart disease (CHD) costs only, cardiovascular disease (CVD) costs and all costs. The first two illustrate different interpretations of what might be regarded as related costs. Results: Employing a 20-year time horizon, the highest mean expected incremental cost was when all costs were included (£2468) and the lowest when CVD costs only were included (£2377). The probability of the treatment being cost effective, estimating health opportunity costs using a ratio of £30,000 per quality-adjusted life-year (QALY), was different for each of the CHD (70%) costs, CVD costs (73%) and all costs (56%) scenarios. The results concern a hypothetical intervention and are illustrative only, as such they cannot necessarily be generalised to all interventions and diseases. Conclusions: Cost categories included in an economic evaluation of SCAD impact on estimates of both cost effectiveness and decision uncertainty. With an aging and co-morbid population, the inclusion of all healthcare costs may have important ramifications for the selection of healthcare provision on economic grounds