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.

Meta-evaluation of a whole systems programme, ActEarly: A study protocol.

INTRODUCTION: Living in an area with high levels of child poverty predisposes children to poorer mental and physical health. ActEarly is a 5-year research programme that comprises a large number of interventions (>20) with citizen science and co-production embedded. It aims to improve the health and well-being of children and families living in two areas of the UK with high levels of deprivation; Bradford in West Yorkshire, and the London Borough of Tower Hamlets. This protocol outlines the meta-evaluation (an evaluation of evaluations) of the ActEarly programme from a systems perspective, where individual interventions are viewed as events in the wider policy system across the two geographical areas. It includes investigating the programme's impact on early life health and well-being outcomes, interdisciplinary prevention research collaboration and capacity building, and local and national decision making. METHODS: The ActEarly meta-evaluation will follow and adapt the five iterative stages of the 'Evaluation of Programmes in Complex Adaptive Systems' (ENCOMPASS) framework for evaluation of public health programmes in complex adaptive systems. Theory-based and mixed-methods approaches will be used to investigate the fidelity of the ActEarly research programme, and whether, why and how ActEarly contributes to changes in the policy system, and whether alternative explanations can be ruled out. Ripple effects and systems mapping will be used to explore the relationships between interventions and their outcomes, and the degree to which the ActEarly programme encouraged interdisciplinary and prevention research collaboration as intended. A computer simulation model ("LifeSim") will also be used to evaluate the scale of the potential long-term benefits of cross-sectoral action to tackle the financial, educational and health disadvantages faced by children in Bradford and Tower Hamlets. Together, these approaches will be used to evaluate ActEarly's dynamic programme outputs at different system levels and measure the programme's system changes on early life health and well-being. DISCUSSION: This meta-evaluation protocol presents our plans for using and adapting the ENCOMPASS framework to evaluate the system-wide impact of the early life health and well-being programme, ActEarly. Due to the collaborative and non-linear nature of the work, we reserve the option to change and query some of our evaluation choices based on the feedback we receive from stakeholders to ensure that our evaluation remains relevant and fit for purpose.

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.

Clustering of adverse health and educational outcomes in adolescence following early childhood disadvantage: population-based retrospective UK cohort study.

BACKGROUND: Disadvantage in early childhood (ages 0-5 years) is associated with worse health and educational outcomes in adolescence. Evidence on the clustering of these adverse outcomes by household income is scarce in the generation of adolescents born since the turn of the millennium. We aimed to describe the association between household income in early childhood and physical health, psychological distress, smoking behaviour, obesity, and educational outcomes at age 17 years, including the patterning and clustering of these five outcomes by income quintiles. METHODS: In this population-based, retrospective cohort study, we used data from the Millennium Cohort Study in which individuals born in the UK between Sept 1, 2000, and Jan 1, 2002, were followed up. We collected data on five adverse health and social outcomes in adolescents aged 17 years known to limit life chances: psychological distress, self-assessed ill health, smoking, obesity, and poor educational achievement. We compared how single and multiple outcomes were distributed across early childhood quintile groups of income, as an indicator of disadvantage, and modelled the potential effect of three income-shifting scenarios in early childhood for reducing adverse outcomes in adolescence. FINDINGS: We included 15 245 adolescents aged 17 years, 7788 (51·1%) of whom were male and 7457 (48·9%) of whom were female. Adolescents in the lowest income quintile group in childhood were 12·7 (95% CI 6·4-25·1) times more likely than those in the highest quintile group to have four or five adverse adolescent outcomes, with poor educational achievement (risk ratio [RR] 4·6, 95% CI 4·2-5·0) and smoking (3·6, 3·0-4·2), showing the largest single risk ratios. Shifting up to the second lowest, middle, and highest income groups would reduce multiple adolescent adversities by 4·9% (95% CI -23·8 to 33·6), 32·3% (-2·7 to 67·3), and 83·9% (47·2 to 120·7), respectively. Adjusting for parental education and single parent status moderately attenuated these estimates. INTERPRETATION: Early childhood disadvantage is more strongly correlated with multiple adolescent adversities than any of the five single adverse outcomes. However, shifting children from the lowest income quintile group to the next lowest group is ineffective. Tackling multiple adolescent adversities requires managing early childhood disadvantage across the social gradient, with income redistribution as a central element of coordinated cross-sectoral action. FUNDING: UK Prevention Research Partnership.

Understanding the relationship between income and mental health among 16- to 24-year-olds: Analysis of 10 waves (2009-2020) of Understanding Society to enable modelling of income interventions.

A substantial body of evidence suggests that young people, including those at the crucial transition points between 16 and 24, now face severe mental health challenges. In this article, we analyse data from 10 waves of a major UK longitudinal household cohort study, Understanding Society, to examine the relationship between income and anxiety and depression among 16- to 24-year-olds. Using random effects logistic regression (Model 1) allowing for whether the individual was depressed in the previous period as well as sex, age, ethnicity, whether the individual was born in the UK, region, rurality, highest qualification, marital status, employment status and attrition, we find a significant and inversely monotonic adjusted association between average net equivalised household income quintiles and clinical threshold levels of depressive symptoms SF-12 Mental Component Summary (MCS score ≤45.6). This means that being in a higher income group is associated with a reduced likelihood of clinically significant depressive symptoms, allowing for observable confounding variables. Using a 'within-between' model (Model 2), we find that apart from among those with the very highest incomes, increases in average net equivalised household income over the course of childhood and adolescence are significantly associated with reduced symptoms of anxiety and depression as measured by a higher SF-12 MCS score. Compared with previous reviews, the data presented here provides an estimate of the magnitude of effect that helps facilitate microsimulation modelling of impact on anxiety and depression from changes in socioeconomic circumstances. This enables a more detailed and complete understanding of the types of socioeconomic intervention that might begin to address some of the causes of youth mental health problems.

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.

Comparing healthcare quality: A common framework for both ordinal and cardinal data with an application to primary care variation in England.

The paper proposes a framework for comparing the quality of healthcare providers and assessing the variation in quality between them, which is directly applicable to both ordinal and cardinal quality data on a comparable basis. The resultant measures are sensitive to the full distribution of quality scores for each provider, not just the mean or the proportion meeting some binary quality threshold, thereby making full use of the multicategory response data increasingly available from patient experience surveys. The measures can also be standardized for factors such as age, sex, ethnicity, health and deprivation using a distribution regression model. We illustrate by measuring the quality of primary care services in England in 2019 using three different sources of publicly available, general practice-level information: multicategory response patient experience data, ordinal inspection ratings and cardinal clinical achievement scores. We find considerable variation at both local and regional levels using all three data sources. However, the correlation between the comparative quality indices calculated using the alternative data sources is weak, suggesting that they capture different aspects of general practice quality.

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.