Exploring Inequalities in Adult Social Care, CY P03 24 01

The United Kingdom is experiencing a significant demographic shift, with an ageing population and an increasing demand for adult social care services. Eligibility for adult social care services is determined through a needs and means testing process based on criteria defined by National Care and Support Regulations from 2015. The escalating cost pressures associated with staffing Local Authority-run residential care homes and overall limited availability of publicly funded adult social care make Adult Social Care (ASC) one of the most pressing challenges in the domain of public services in the UK. Given this scenario, there are bottlenecks for inequalities in the needs and experiences of ASC. For some groups, high dependency on council-run services, while other must rely on the support from unpaid carers, most of the time family members.

The main objective of this research is therefore to use a data-driven approach to characterise provision and use in ASC. Its core research objective is to develop explainable machine learning models to assess resource allocation in ASC, identifying possible inequalities in service provision among different social groups. The results and findings deriving from these models will be informed to subject-matter experts in an engaging and transparent way, exploring methods to embed transparency and explicability to communicate outputs of machine learning models. The insights and tools developed through the project will support the delivery of evidence based public service provision aimed at supporting positive public-health outcomes within Bradford.

01/03/2023

4 years