Title: Evidence to support efficient and effective reduction of health inequality
Funder: Department of Health and Social Care

Abstract: Existing research has estimated relationships between demographic and socioeconomic characteristics and various aspects of health inequality, such as life expectancy. Routinely collected electronic health data and surveys provide an underexploited source for extracting information on socioeconomic variation in different aspects of health policies performance. However these sources of evidence are not well used in value assessments that inform which policies to fund from limited resources. Further analysis is required to exploit and combine this evidence to estimate the overall impact on health inequality for alternative policies. The current lack of information on health inequality impacts may lead to unintentional provision of policies that increase health inequality. We will use evidence reviews and knowledge gathering exercises with experts and stakeholders to assemble existing evidence on socioeconomic variation in risk factors, diseases, utilisation and performance of health policies, and health outcomes. We will show how this can be combined to compute the degree to which existing health policies influence the level of health inequality. By using the framework of distributional cost effectiveness analysis (DCEA) we will show how these policy impacts on health inequality combine with impact on total population health in assessment of value for money. We will also apply DCEA to interventions designed to modify the impact of health policies on health inequality, for example by increasing uptake in the most disadvantaged groups. We will also generate new evidence by showing how to analyse routinely collected survey, registry and electronic health record data to calculate socioeconomic variation in health policy performance, and how to incorporate this in assessment of value for money using DCEA. We will apply a DCEA framework using aggregate data to estimate, across a broad range of existing health policies, which groups benefit the most in terms of health. This will extend previous research that estimated the maximum health inequality impact of 134 public health interventions evaluated for National Institute for Health and Care Excellence (NICE) guidelines to reflect variation in access and utilisation, and to include policies not evaluated by NICE. We will use two case studies to demonstrate how to estimate the health inequality impact of interventions such as best practice tariffs, and show how to use this in DCEA. The results of this research will provide new information to commissioners about the health inequality impact of existing policies. This can be used to inform decisions about whether to continue funding, and whether there are cost-effective ways to modify the policy to improve impacts on health inequality. The methods demonstrated in this research will show how existing evidence reviews and routine data can be exploited to provide value assessments that integrate goals of improving population health with the goal to reduce health inequality.

Lay abstract: There are big differences in life expectancy and illness across the UK. The poorest groups live 9 years less than the richest in England, and have 19 fewer years in good health. Government spending aims to improve health and to improve the health of the poorest fastest. Those making decisions about how to use Government funds often do not see information on who gains or loses from a policy, or which policies help the poorest most. Our research will show policies that reduce differences in health between groups (such as rich versus poor, but also by other factors such as ethnicity), and those that increase differences. We will show how this information can be used alongside how a policy changes overall health in decisions about which policies to fund. Health policies do not affect everyone the same. Different people have different risks of getting diseases (the poorest are more likely to get cancer). People differ in the amount they use health services, in the type of care they receive, and in the costs and success of that care (the poorest are less likely to survive cancer). These factors combine in a staircase effect that generates differences in final health outcomes. We will review the evidence for the differences between people across each of the steps in the staircase (risk of disease, use of health services, etc.) for a number of health policies. We will combine the information to see how each policy affects the health of different groups, the differences between groups, and the overall health of everyone. We will also look for ways to change health policies to perform better at improving the health of the poorest most. The Government and NHS collect information from members of the public. We will use this information to learn about how policies improve health and reduce differences in health between groups. Statistics can describe the differences in health between groups, but it is people who must decide if those differences are unfair. Our research will rely on members of the public and those in charge of Government health spending to guide us in which groups and policies to investigate, and in how to produce clear and practical evidence. Our results will give funders information on how each policy changes overall health and the health of different groups compared to the benefits from funding other policies. Our method could be used to examine future policies. We will publicise our research online, in publication, and in person, through Department of Health and Social Care (DHSC) and arms length bodies like Public Health England and the National Institute for Health and Care Excellence, and to local funders and Directors of Public Health.

Research activity codes: 8.2 HEALTH AND WELFARE ECONOMICS;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE