A transparent, open source and reproducible analytical framework to enable the estimation of inclusion health outcomes on population health metrics.

Research Question: This research seeks to determine the extent to which the health inequalities experienced by inclusion health groups contribute to the overall health statistics of the population in England.

Background: Previous research has established that extreme health inequities are experienced by inclusion health populations, often greater than those in traditional low socioeconomic groups.

However, the contribution of these extreme health disparities to the overall population's health statistics remains unclear.

This research proposal aims to build an analytical framework to understand this contribution, with the ultimate goal of informing health policies and resource allocation.

Aims and Objectives: The primary aim is to establish a transparent, robust, and continuously updated analytical framework to estimate the contribution of inclusion health groups towards population health statistics.

The framework will answer three specific research objectives: 1) determine the size of inclusion groups (people experiencing homelessness, prisoners, international migrants, substance use disorders, sex workers and Gypsy, Roma, and Traveller populations) and the extent of overlapping risk factors for social exclusion in England; 2) estimate the proportion of cause-specific deaths in the general population in England attributable to inclusion health groups; 3) calculate the proportion of morbidity outcomes for selected high burden conditions in the general population in England attributable to inclusion health groups.

Methods: The research will occur in two stages.

Stage 1 involves identification of data for the populations of interest through systematic literature reviews, stakeholder analysis, a national call for evidence, third sector consultation workshops, and people with lived experience consultation workshops. We will combine existing and new data and deduplicate this for overlap, and apply our inclusion criteria to the data.

This approach should comprehensively identify any data that we are not aware of to address known gaps in the data.

Stage 2 involves estimating the impact of inclusion health outcomes on population health metrics by further developing an analytical framework in collaboration with the Institute for Health Metrics and Evaluation.

This framework incorporates diverse epidemiological data, reconciles inconsistent data, and projects data for regions and parameters with limited or no available data. The framework will be adapted using DisMod-MR 2.1 to allow the consistent integration of diverse data.

Consultation workshops with people with lived experience in each inclusion health group will review which data sources were used, output the model estimates, and the limitations of estimates in an interactive manner. Timelines for delivery: The study is planned to occur over two years. Stage 1 will take place from September 2024 to January 2026.

Stage 2 will take place from October 2025 to August 2026.

Anticipated Impact and Dissemination: The research's findings are expected to guide policy development by demonstrating the extent to which tackling extreme inequalities could improve general population health metrics.

The analytical framework will support informed implementation research for inclusion health and wider population initiatives.

The results will be disseminated through a public-facing event to launch the final report, co-produced by the research team and people with lived experience on the advisory board, and through academic publications.