Using Discrete Choice Experiments (DCEs) to Compare Social and Personal Preferences for Health and Well-Being Outcomes, 2022

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Economic evaluations in health typically assume a nonwelfarist framework, arguably better served by preferences elicited from a social perspective than a personal one. However, most health state valuation studies elicit personal preferences, leading to a methodological inconsistency. No studies have directly compared social and personal preferences for outcomes using otherwise identical scenarios, leaving their empirical relationship unclear. This unique study examines whether the choice of eliciting preferences from a social or personal perspective influences valuations of health and well-being outcomes. Using discrete choice experiments, social and personal preferences for health and well-being attributes were elicited from the UK general public recruited from an internet panel (n = 1,020 personal, n = 3,009 social surveys). Mixed logit models were estimated, and willingness-to-pay (WTP) values for each attribute were calculated to compare differences between the 2 perspectives. While no significant differences were observed in the effects of physical and mental health, loneliness, and neighborhood safety across the 2 perspectives, significant differences emerged in WTP values for employment and housing quality. For instance, other things being the same, personal preferences rate being retired as more preferable than being an informal caregiver, but the social preferences rate them in the reverse order. Our findings demonstrate that the perspective matters, particularly for valuing outcomes such as employment and housing. These findings indicate that the exclusive use of personal preferences to value states such as employment and housing quality may potentially lead to suboptimal resource allocation, given that such valuations reflect individual rather than societal benefit. This highlights the importance of considering perspective especially in the resource allocation of public health interventions.

THE PROBLEM There is strong evidence that the social and economic conditions in which we grow, live, work and age determine our health to a much larger degree than lifestyle choices. These social determinants of health, such as income, good quality homes, education or work, are not distributed equally in society, which leads to health inequalities. However, we know very little about how specific policies influence the social conditions to prevent ill health and reduce health inequalities. Also, most social determinants of health are the responsibility of policy sectors other than "health", which means policymakers need to promote health in ALL their policies if they are to have a big impact on health. SIPHER will provide new scientific evidence and methods to support such a shift from "health policy" to "healthy public policy". OUR POLICY FOCUS We will work with three policy partners at local, regional and national level to tackle their above-average chronic disease burden and persistent health inequalities: Sheffield City Council, Greater Manchester Combined Authority and Scottish Government. We will focus on four jointly agreed policy priorities for good health: - Creating a fairer economy - Promoting mental wellbeing - Providing affordable, good quality housing - Preventing long-term effects of difficult childhoods. OUR COMPLEX SYSTEMS SCIENCE APPROACH Each of the above policy areas is a complex political system with many competing priorities, where policy choices in one sector (e.g. housing) can have large unintended effects in others (e.g. poverty). There is often no "correct" solution because compromises between different outcomes require value judgements. This means that to assess the true benefits and costs of a policy in relation to health, policy effects and their interdependencies need to be assessed across a wide range of possible outcomes. However, no policymaker has knowledge of the whole system and future economic and political developments are uncertain. Ongoing monitoring of expected and unexpected effects of policies and other system changes is crucial so failing policies can be revised or dropped. We propose to use complex systems modelling, which has been developed to understand and make projections of what might happen in complex systems given different plausible assumptions about future developments. Our models will be underpinned by the best available data and prior research in each policy area. Our new evidence about likely policy effects across a wide range of outcomes will help policy partners decide between alternative policies, depending on how important different outcomes are to them (e.g. improving health or economic growth). We will develop support tools that can visualise the forecasts, identify policies that achieve the desired balance between competing outcomes and update recommendations when new information emerges. Whilst new to public health policy, these methods are well-established in engineering and climate science. We will 1. Work with policy partners to understand the policy systems and evidence needs 2. Bring together existing data and evidence on each policy system (e.g. links between policies and outcomes, interdependencies between outcomes) 3. Explore citizens' preferences for prioritising when not all outcomes can be achieved 4. Link policies and their health and non-health effects in computer models to analyse benefits and costs over time 5. Build an interactive tool to help policy decision-making, inform advocacy action and support political debate. SIPHER's MAIN OUTCOME We will provide policymakers with a new methodology that allows them to estimate the health-related costs and benefits of policies that are implemented outside the health sector. This will be useful to our partners, and others, who want to assess how scarce public sector resources can be spent to maximise the health and wellbeing benefits from all their activities.