Modelling Prevention Policy Impacts on Local Authority-Funded Social Care Services in England: A System Dynamics Modelling Approach

England’s population is living longer, a sign of progress and better health, but adult social care (ASC) services must adapt to support a growing number of older residents, who may need help to remain independent, safe, and well. Kent County Council (KCC), in South East England, projects a 28% and 53% increase in its residents aged 65+ and 85+, respectively, over the next decade. This study aimed to inform the development of KCC’s ASC Prevention Framework using a System Dynamics Modelling (SDM) approach to evaluate the impact of preventive interventions on ASC demand and expenditure. Using linked local health and social care data and the Johns Hopkins ACG® tool, the 1.3 million adult population was stratified into Patient Needs Groups. Analyses showed that higher ASC costs were associated with being older females, living alone, deprivation, and frailty-related indicators such as dementia, history of falls, etc. Around 28% of older adults aged 65+ accounted for 80% of ASC costs within that cohort, and related scenario testing projected a 48% rise in ASC costs over 10 years without interventions, moderated to 33% with targeted prevention. These findings demonstrate the value of integrated data and modelling to inform strategic, prevention-focused ASC planning.