Estimating the lifetime costs and benefits of the Incredible Years Teacher Classroom Management intervention using data from 30 months follow up of the STARS Trial.

OBJECTIVES: The Incredible Years Teacher® Classroom Management (IY-TCM) intervention is associated with short-term improvements in mental health difficulties in young people. The aim was to estimate the long-term impact and cost-effectiveness of the IY-TCM intervention compared to no intervention. METHODS: An existing health economic model (LifeSim 1.0) was used to translate short-term changes in the Strength and difficulties questionnaire (SDQ), based on the STARS cluster randomised controlled trial of the IY-TCM intervention in schools, into estimated medium- and long-term effects using multiple longitudinal datasets. LifeSim 1.0 was adapted to incorporate teacher-reported SDQ and account for individual heterogeneity. Cost-effectiveness analyses were conducted using the trial-based intervention cost with subgroup analyses on deprivation, conduct scores and parental depression in the simulated baseline population. RESULTS: Regression analyses show significant predictor variables for intervention effectiveness including deprivation and baseline SDQ. LifeSim results indicate small gains in long-term outcomes, and cost-effective analyses estimated that the IY-TCM intervention could be cost-effective but there was a large amount of uncertainty (Net monetary benefit (NMB)=£10, Estimated CI = -£134, £156). Benefits and certainty of cost-effectiveness were greater, for some subgroups such as those with high conduct scores at baseline (NMB=£206, Estimated CI = £26, £318). CONCLUSIONS: IY-TCM could be cost-effective but there was a large amount of uncertainty around costs and benefits. Greater benefits for pupils with difficulties at baseline suggest that the intervention may be more cost-effective for schools in more deprived areas with high levels of conduct problems.

Potentially avoidable hospitalizations and socioeconomic status in Switzerland: A small area-level analysis.

The Swiss healthcare system is well known for the quality of its healthcare and population health but also for its high cost, particularly regarding out-of-pocket expenses. We conduct the first national study on the association between socioeconomic status and access to community-based ambulatory care (CBAC). We analyze administrative and hospital discharge data at the small area level over a four-year time period (2014 - 2017). We develop a socioeconomic deprivation indicator and rely on a well-accepted indicator of potentially avoidable hospitalizations as a measure of access to CBAC. We estimate socioeconomic gradients at the national and cantonal levels with mixed effects models pooled over four years. We compare gradient estimates among specifications without control variables and those that include control variables for area geography and physician availability. We find that the most deprived area is associated with an excess of 2.80 potentially avoidable hospitalizations per 1,000 population (3.01 with control variables) compared to the least deprived area. We also find significant gradient variation across cantons with a difference of 5.40 (5.54 with control variables) between the smallest and largest canton gradients. Addressing broader social determinants of health, financial barriers to access, and strengthening CBAC services in targeted areas would likely reduce the observed gap.

Using administrative data to evaluate national policy impacts on child and maternal health: a research framework from the Maternal and Child Health Network (MatCHNet).

Reducing health inequalities by addressing the social circumstances in which children are conceived and raised is a societal priority. Early interventions are key to improving outcomes in childhood and long-term into adulthood. Across the UK nations, there is strong political commitment to invest in the early years. National policy interventions aim to tackle health inequalities and deliver health equity for all children. Evidence to determine the effectiveness of socio-structural policies on child health outcomes is especially pressing given the current social and economic challenges facing policy-makers and families with children. As an alternative to clinical trials or evaluating local interventions, we propose a research framework that supports evaluating the impact of whole country policies on child health outcomes. Three key research challenges must be addressed to enable such evaluations and improve policy for child health: (1) policy prioritisation, (2) identification of comparable data and (3) application of robust methods.

Guidance on the use of complex systems models for economic evaluations of public health interventions.

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Identifying opportunities for upstream evaluations relevant to child and maternal health: a UK policy-mapping review.

OBJECTIVE: Interventions to tackle the social determinants of health can improve outcomes during pregnancy and early childhood, leading to better health across the life course. Variation in content, timing and implementation of policies across the 4 UK nations allows for evaluation. We conducted a policy-mapping review (1981-2021) to identify relevant UK early years policies across the social determinants of health framework, and determine suitable candidates for evaluation using administrative data. METHODS: We used open keyword and category searches of UK and devolved Government websites, and hand searched policy reviews. Policies were rated and included using five criteria: (1) Potential for policy to affect maternal and child health outcomes; (2) Implementation variation across the UK; (3) Population reach and expected effect size; (4) Ability to identify exposed/eligible group in administrative data; (5) Potential to affect health inequalities. An expert consensus workshop determined a final shortlist. RESULTS: 336 policies and 306 strategy documents were identified. Policies were mainly excluded due to criteria 2-4, leaving 88. The consensus workshop identified three policy areas as suitable candidates for natural experiment evaluation using administrative data: pregnancy grants, early years education and childcare, and Universal Credit. CONCLUSION: Our comprehensive policy review identifies valuable opportunities to evaluate sociostructural impacts on mother and child outcomes. However, many potentially impactful policies were excluded. This may lead to the inverse evidence law, where there is least evidence for policies believed to be most effective. This could be ameliorated by better access to administrative data, staged implementation of future policies or alternative evaluation methods.

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis.

OBJECTIVES: We conducted a distributional cost-effectiveness analysis (DCEA) to evaluate how Medicare funding of inpatient COVID-19 treatments affected health equity in the United States. METHODS: A DCEA, based on an existing cost-effectiveness analysis model, was conducted from the perspective of a single US payer, Medicare. The US population was divided based on race and ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and county-level social vulnerability index (5 quintile groups) into 15 equity-relevant subgroups. The baseline distribution of quality-adjusted life expectancy was estimated across the equity subgroups. Opportunity costs were estimated by converting total spend on COVID-19 inpatient treatments into health losses, expressed as quality-adjusted life-years (QALYs), using base-case assumptions of an opportunity cost threshold of $150 000 per QALY gained and an equal distribution of opportunity costs across equity-relevant subgroups. RESULTS: More socially vulnerable populations received larger per capita health benefits due to higher COVID-19 incidence and baseline in-hospital mortality. The total direct medical cost of inpatient COVID-19 interventions in the United States in 2020 was estimated at $25.83 billion with an estimated net benefit of 735 569 QALYs after adjusting for opportunity costs. Funding inpatient COVID-19 treatment reduced the population-level burden of health inequality by 0.234%. Conclusions remained robust across scenario and sensitivity analyses. CONCLUSIONS: To the best of our knowledge, this is the first DCEA to quantify the equity implications of funding COVID-19 treatments in the United States. Medicare funding of COVID-19 treatments in the United States could improve overall health while reducing existing health inequalities.

Cost of health inequality to the NHS in Wales.

Background: Forty years from the seminal work of Welsh GP Julian Tudor Hart on the Inverse Care Law, inequalities in health and healthcare remain deeply embedded in Wales. There is a wider gap (over 17 years) in healthy life expectancy between people living in the most and least deprived neighborhoods in Wales. This health inequality is reflected in additional healthcare use. In this study we estimate the cost of inequality associated with this additional healthcare use to the publicly funded National Health Service (NHS) in Wales. Methods: We retrieved administrative data on all NHS inpatient admissions, outpatient and accident and emergency attendances in Wales between April 2018 and March 2019 from Digital Health and Care Wales (DHCW). Hospital service use data were translated to costs using Healthcare Resource Group (HRG) and health service specific unit cost data and linked with area level mid-year population and deprivation indices in order to calculate the healthcare costs associated with socioeconomics deprivation. Results: Inequality in healthcare use between people from more and less deprived neighborhoods was associated with an additional cost of £322 million per year to the NHS in Wales, accounting for 8.7% of total NHS hospital expenditure in the country. Emergency inpatient admissions made up by far the largest component of this additional cost contributing £247.4 million, 77% of the total. There are also substantial costs of inequality for A&E attendances and outpatient visits, though not maternity services. Elective admissions overall have a negative cost of inequality, since among men aged 50-75 and women aged 60-70, elective utilization is actually negatively associated with deprivation. Conclusion: There are wide inequalities in health and healthcare use between people living in more deprived neighborhoods and those living in less deprived neighborhoods in Wales. Tackling health inequality through a combination of health promotion and early intervention policies targeted toward deprived communities could yield substantial improvement in health and wellbeing, as well as savings for the Welsh NHS through reduced use of emergency hospital care.

Evaluating childhood policy impacts on lifetime health, wellbeing and inequality: Lifecourse distributional economic evaluation.

We introduce and illustrate a new framework for distributional economic evaluation of childhood policies that takes a broad and long view of the impacts on health, wellbeing and inequality from a cross-sectoral whole-lifetime perspective. Total lifetime benefits and public cost savings are estimated using lifecourse microsimulation of diverse health, social and economic outcomes for each individual in a general population birth cohort from birth to death. Cost-effectiveness analysis, policy targeting analysis and distributional analysis of inequality impacts are then conducted using an index of lifetime wellbeing that allow comparisons of both value-for-money (efficiency) and distributional impact (equity) from a cross-sectoral lifetime perspective. We illustrate how this framework can be applied in practice by re-evaluating a training programme in England for parents of children at risk of conduct disorder. Our illustration uses a simple index of lifetime wellbeing based on health-related quality of life and consumption, but other indices could be used based on other kinds of outcomes data such as life satisfaction or multidimensional quality of life. We create the detailed underpinning data needed to apply the framework by using a previously published meta-analysis of randomised controlled trials to estimate the short-term effects and a previously published lifecourse microsimulation model to extrapolate the long-term effects.

Reducing inequality in avoidable emergency admissions: Case studies of local health care systems in England using a realist approach.

OBJECTIVE: People in disadvantaged areas are more likely to have an avoidable emergency hospital admission. Socio-economic inequality in avoidable emergency hospital admissions is monitored in England. Our aim was to inform local health care purchasing and planning by identifying recent health care system changes (or other factors), as reported by local health system leaders, that might explain narrowing or widening trends. METHODS: Case studies were undertaken in one pilot and at five geographically distinct local health care systems (Clinical Commissioning Groups, CCGs), identified as having consistently increasing or decreasing inequality. Local settings were explored through discussions with CCG officials and stakeholders to identify potential local determinants. Data were analysed using a realist evaluation approach to generate context-mechanism-outcome (CMO) configurations. RESULTS: Of the five geographically distinct CCGs, two had narrowing inequality, two widening, and one narrowing inequality, which widened during the project. None of the CCGs had designed a large-scale package of service changes with the explicit aim of reducing socio-economic inequality in avoidable emergency admissions, and local decision makers were unfamiliar with their own trends. Potential primary and community care determinants included: workforce, case finding and exclusion, proactive care co-ordination for patients with complex needs, and access and quality. Potential commissioning determinants included: data use and incentives, and targeting of services. Other potential determinants included changes in care home services, national A&E targets, and wider issues - such as public services financial constraints, residential gentrification, and health care expectations. CONCLUSIONS: We did not find any bespoke initiatives that explained the inequality trends. The trends were more likely due to an interplay of multiple health care and wider system factors. Local decision makers need greater awareness, understanding and support to interpret, use and act upon inequality indicators. They are unlikely to find simple, cheap interventions to reduce inequalities in avoidable emergency admissions. Rather, long-term multifaceted interventions are required that embed inequality considerations into mainstream decision making.

Health inequality in Britain before 1750.

BACKGROUND: This study examines the claim that social inequality in health in European populations was absent prior to 1750. This claim is primarily based on comparisons of life expectancy at birth in England between general and ducal (elite aristocrat) social classes from the 1550s to the 1870s. METHODS: We examined historic childhood mortality trends among the English ducal class and the general population, based on previously published data. We compared mid-childhood to adolescent mortality (age 5-14) and early-childhood mortality (age 0-4) between the ducal class and the general population from the 17th to 19th centuries. RESULTS: Prior to 1750, ducal early-childhood mortality was higher than the general population. However, mid-childhood to adolescent mortality was lower among the ducal class than the general population in all observed periods for boys, and almost all periods for girls. Among the ducal class, but not the general population, there was a sharp decline in early-childhood mortality around the 1750s which may partly explain the divergent trends in overall life expectancy at birth. CONCLUSION: Health inequality between the ducal class and general population was present in England from the 16th to mid-18th centuries, with disadvantages in mortality for ducal children in infancy and early childhood, but survival advantages in mid-childhood and adolescence. These opposing effects are obscured in life expectancy at birth data. Relatively high early-childhood mortality among ducal families before 1750 likely resulted from short birth intervals and harmful infant feeding practices during this time.

Equity-informative methods of health services research.

PURPOSE: We review quantitative methods for analysing the equity impacts of health care and public health interventions: who benefits most and who bears the largest burdens (opportunity costs)? Mainstream health services research focuses on effectiveness and efficiency but decision makers also need information about equity. DESIGN/METHODOLOGY/APPROACH: We review equity-informative methods of quantitative data analysis in three core areas of health services research: effectiveness analysis, cost-effectiveness analysis and performance measurement. An appendix includes further readings and resources. FINDINGS: Researchers seeking to analyse health equity impacts now have a practical and flexible set of methods at their disposal which builds on the standard health services research toolkit. Some of the more advanced methods require specialised skills, but basic equity-informative methods can be used by any health services researcher with appropriate skills in the three core areas. ORIGINALITY/VALUE: We hope that this review will raise awareness of equity-informative methods of health services research and facilitate their entry into the mainstream so that health policymakers are routinely presented with information about who gains and who loses from their decisions.

The inverse care law re-examined: a global perspective.

An inverse care law persists in almost all low-income and middle-income countries, whereby socially disadvantaged people receive less, and lower-quality, health care despite having greater need. By contrast, a disproportionate care law persists in high-income countries, whereby socially disadvantaged people receive more health care, but of worse quality and insufficient quantity to meet their additional needs. Both laws are caused not only by financial barriers and fragmented health insurance systems but also by social inequalities in care seeking and co-investment as well as the costs and benefits of health care. Investing in more integrated universal health coverage and stronger primary care, delivered in proportion to need, can improve population health and reduce health inequality. However, trade-offs sometimes exist between health policy objectives. Health-care technologies, policies, and resourcing should be subjected to distributional analysis of their equity impacts, to ensure the objective of reducing health inequalities is kept in sight.

Development of a checklist to guide equity considerations in health technology assessment.

OBJECTIVES: Health technology assessment (HTA) can impact health inequities by informing healthcare priority-setting decisions. This paper presents a novel checklist to guide HTA practitioners looking to include equity considerations in their work: the equity checklist for HTA (ECHTA). The list is pragmatically organized according to the generic HTA phases and can be consulted at each step. METHODS: A first set of items was based on the framework for equity in HTA developed by Culyer and Bombard. After rewording and reorganizing according to five HTA phases, they were complemented by elements emerging from a literature search. Consultations with method experts, decision makers, and stakeholders further refined the items. Further feedback was sought during a presentation of the tool at an international HTA conference. Lastly, the checklist was piloted through all five stages of an HTA. RESULTS: ECHTA proposes elements to be considered at each one of the five HTA phases: Scoping, Evaluation, Recommendations and Conclusions, Knowledge Translation and Implementation, and Reassessment. More than a simple checklist, the tool provides details and examples that guide the evaluators through an analysis in each phase. A pilot test is also presented, which demonstrates the ECHTA's usability and added value. CONCLUSIONS: ECHTA provides guidance for HTA evaluators wishing to ensure that their conclusions do not contribute to inequalities in health. Several points to build upon the current checklist will be addressed by a working group of experts, and further feedback is welcome from evaluators who have used the tool.

Quality adjusted life years based on health and consumption: A summary wellbeing measure for cross-sectoral economic evaluation.

We introduce a summary wellbeing measure for economic evaluation of cross-sectoral public policies with impacts on health and living standards. We show how to calculate period-specific and lifetime wellbeing using quality-adjusted life years based on widely available data on health-related quality of life and consumption and normative assumptions about three parameters-minimal consumption, standard consumption, and the elasticity of the marginal value of consumption. We also illustrate how these three parameters can be tailored to the decision-making context and varied in sensitivity analysis to provide information about the implications of alternative value judgments. As well as providing a general measure for cost-effectiveness analysis and cost-benefit analysis in terms of wellbeing, this approach also facilitates distributional analysis in terms of how many good years different population subgroups can expect to live under different policy scenarios.

Interventions to reduce inequalities in avoidable hospital admissions: explanatory framework and systematic review protocol.

INTRODUCTION: Internationally there is pressure to contain costs due to rising numbers of hospital admissions. Alongside age, socioeconomic disadvantage is the strongest risk factor for avoidable hospital admission. This equity-focussed systematic review is required for policymakers to understand what has been shown to work to reduce inequalities in hospital admissions, what does not work and where the current gaps in the evidence-base are. METHODS AND ANALYSIS: An initial framework shows how interventions are hypothesised to reduce socioeconomic inequalities in avoidable hospital admissions. Studies will be included if the intervention focusses exclusively on socioeconomically disadvantaged populations or if the study reports differential effects by socioeconomic status (education, income, occupation, social class, deprivation, poverty or an area-based proxy for deprivation derived from place of residence) with respect to hospital admission or readmission (overall or condition-specific for those classified as ambulatory care sensitive). Studies involving individuals of any age, undertaken in OECD (Organisation for Economic Co-operation and Development) countries, published from 2000 to 29th February 2020 in any language will be included. Electronic searches will include MEDLINE, Embase, CINAHL, Cochrane CENTRAL and the Web of Knowledge platform. Electronic searches will be supplemented with full citation searches of included studies, website searches and retrieval of relevant unpublished information. Study inclusion, data extraction and quality appraisal will be conducted by two reviewers. Narrative synthesis will be conducted and also meta-analysis where possible. The main analysis will examine the effectiveness of interventions at reducing socioeconomic inequalities in hospital admissions. Interventions will be characterised by their domain of action and approach to addressing inequalities. For included studies, contextual information on where, for whom and how these interventions are organised, implemented and delivered will be examined where possible. ETHICS AND DISSEMINATION: Ethical approval was not required for this protocol. The research will be disseminated via peer-reviewed publication, conferences and an open-access policy-orientated paper. PROSPERO REGISTRATION NUMBER: CRD42019153666.

Estimating Social Variation in the Health Effects of Changes in Health Care Expenditure.

Background. A common aim of health expenditure is to reduce unfair inequalities in health. Although previous research has attempted to estimate the total health effects of changes in health expenditure, little is known about how changes affect different groups in the population. Methods. We propose a general framework for disaggregating the total health effects of changes in health expenditure by social groups. This can be performed indirectly when the estimate of the total health effect has first been disaggregated by a secondary factor (e.g., disease area) that can be linked to social characteristics. This is illustrated with an application to the English National Health Service. Evidence on the health effects of expenditure across 23 disease areas is combined with data on the distribution of disease-specific hospital utilization by age, sex, and area-level deprivation. Results. We find that the health effects from NHS expenditure changes are produced largely through disease areas in which individuals from more deprived areas account for a large share of health care utilization, namely, respiratory and neurologic disease and mental health. We estimate that 26% of the total health effect from a change in expenditure would accrue to the fifth of the population living in the most deprived areas, compared with 14% to the fifth living in the least deprived areas. Conclusions. Our approach can be useful for evaluating the health inequality impacts of changing health budgets or funding alternative health programs. However, it requires robust estimates of how health expenditure affects health outcomes. Our example analysis also relied on strong assumptions about the relationship between health care utilization and health effects across population groups.

Universal or targeted cardiovascular screening? Modelling study using a sector-specific distributional cost effectiveness analysis.

Distributional cost effectiveness analysis is a new method that can help to redesign prevention programmes by explicitly modelling the distribution of health opportunity costs as well as the distribution of health benefits. Previously we modelled cardiovascular disease (CVD) screening audit data from Liverpool, UK to see if the city could redesign its cardiovascular screening programme to enhance its cost effectiveness and equity. Building on this previous analysis, we explicitly examined the distribution of health opportunity costs and we looked at new redesign options co-designed with stakeholders. We simulated four plausible scenarios: a) no CVD screening, b) 'current' basic universal CVD screening as currently implemented, c) enhanced universal CVD screening with 'increased' population-wide delivery, and d) 'universal plus targeted' with top-up delivery to the most deprived fifth. We also compared assumptions around whether displaced health spend would come from programmes that might benefit the poor more and how much health these programmes would generate. The main outcomes were net health benefit and change in the slope index of inequality (SII) in QALYs per 100,000 person years. 'Universal plus targeted' dominated 'increased' and 'current' and also reduced health inequality by -0.65 QALYs per 100,000 person years. Results are highly sensitive to assumptions about opportunity costs and, in particular, whether funding comes from health care or local government budgets. By analysing who loses as well as who gains from expenditure decisions, distributional cost effectiveness analysis can help decision makers to redesign prevention programmes in ways that improve health and reduce health inequality.