Modelling social care need and healthcare demand

The UK is entering a social care crisis, as lower birth rates in recent decades combined with longer lifespans have led to an increasing demand for social care. Unmet care need is a significant problem in the UK, and leads to additional strain on health services.  

Designing policy interventions to address this crisis requires an investigation of the complex family-level decisions lying at the heart of informal care.  Informal care is most commonly provided via small networks of close family members, with a large share of that care coming from family members in the same household as the care receiver.  Numerous factors affect the provision of social care within families, including socioeconomic status; informal care is far more common in lower SES families, whereas wealthier families tend to utilize privately-funded formal care.

We have built a sophisticated agent-based model (ABM) to study the provision of informal and formal social care in the UK. Our simulated agents live complex lives in a virtual UK society – they age, pay tax, find partners and start new households, even enter higher education and migrate domestically in search of employment. When a family member develops care needs, family members negotiate within their kinship networks to determine which members are able to provide care, according to their availability, employment and health status, and financial situation.  Agents with sufficient resources may opt to pay for formal care rather than contribute informal care.  In cases where informal care availability is insufficient, agents will have unmet care need and will be more likely to require additional healthcare services.

This ABM framework allows us to model individual- and family-level decision-making relating to informal care at a level of detail far beyond the reach of statistical approaches. The model outputs detailed information on care provision by agent characteristics and SES, and provides measures of policy cost-effectiveness and impact on healthcare demand.  As the simulation framework continues to evolve, we will be able to simulate the possible effects, both positive and negative, of a wide range of possible policy interventions. 


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