Orienting Policy Towards Inequality Minimising Actions (OPTIMA): A systems science approach to 20-minute neighbourhood policy and evaluation

BACKGROUND

The 20-minute neighbourhood (20MN), access to daily service needs within a walkable/wheelable distance, is being rolled out nationally in Scotland, and locally in other parts of the UK and internationally. It explicitly aims to tackle health inequalities. Yet, the current evidence base is insufficient with potential for unintended harms.

Significant investments are being made, and much more will be required for full scale-up. Evidence is required to capture the dynamics, key to measuring changing health inequalities, to avoid suboptimal choices becoming ingrained in sunk costs. AIM To produce timely, effective, actionable evidence on 20MNs and their health inequality implications.

OBJECTIVES Four overarching objectives: 1) synthesise the current evidence-base and stakeholders’ lived experience, making current uncertainties explicit;

2) compile service location data and overlay a synthetic population to identify baseline priority clusters of ‘left behind’ areas;

3) adapt an existing agent-based model (ABM) to capture the complex interactions of individuals accessing services, and services responding to their access, to add to our understanding of which 20MN interventions might maximise health inequality benefits; 4) use the early stakeholder engagement via modelling to inform and deliver additional robust real-world evaluation.

METHODS The project has four work packages (WPs):

WP1 will work iteratively across evidence sources (literature and stakeholders) to inform pathways to health outcomes and behaviour rules of individual and service agents within the system. It will identify uncertainties in this evidence, provide ongoing engagements with decision-makers, and feed co-produced evidence and insights in a timely manner to the WPs that follow.

WP2 will collate and analyse novel data linkages which capture the baseline conditions for the 20MN policy, and geographical changes over time. WP2 extends existing work spatially (to the whole of Great Britain) and adds measures of service quality and sociodemographic profile to highlight area-level needs. The linked dataset created will underpin WP3's simulation models.

We will apply clustering methods to establish a typology of areas which perform similar with respect to outlined 20MN characteristics (e.g., ‘left behind’ areas).

WP3 will use spatially explicit ABMs to bring foresight into (i) which interventions might maximise individual health benefits and (ii) the anticipated impacts of these changes on the local areas (or population groups) for health inequality. For feasibility, we will initially focus on health impacts via active travel and a single Scottish local authority.

Iteratively, we will validate and expand pathways and places. The dynamic insights can flexibly examine projected health inequality impacts to mitigate unintended consequences.

WP4 will identify opportunities and develop plans for natural experimental evaluation with integrated economic evaluation. IMPACT AND DISSEMINATION

The research utilises forward-looking methods, and will progressively output and refine evidence to align with the policy timetable. Since the investments are being planned and managed locally, we expect to be able to have a range of impacts by informing this investment and planning towards minimising health inequality harms (and maximising benefits). We will work closely with our stakeholder advisory group and PPIE group to ensure patient and public benefit and maximal impact.