A new solution allows local authorities to access social care data to enable them to proactively plan the sector based on real-world modeling.
Digital transformation specialist Agilisys has launched its solution for modeling the demand and cost of social care, which can be seen by senior leaders and decision makers to assess the impact of social care. .
The goal of the solution is to enable them to make proactive funding decisions based on modeling from the data.
Agilisys worked with local authorities across the UK to address the root cause of excessive spending on social assistance and offer a solution that would help them plan better use of resources.
Chris Hyde, Agilisys ’chief data and vision strategy consultant, said:“ Unfortunately, the growing demand and cost of social care will not go down; certainly without a major long-term structural change.
“Therefore, we need to think about flattening the curve to make sure that excess demand, while it still exists, is mitigated by concerted efforts to reduce dependency and reduce institutionalization.”
The solution allows local authorities to control the demand and delivery of social care and their budgets.
Agilisys created a modeling solution that helps capture disparate data captured by a local authority and apply it to potential scenarios. Using clearly defined baselines, the demand and cost model of social care collects data to illustrate what services it offers and at what cost per person.
“Once local authorities have a chance to see what the cost per person in a given category or cohort is (e.g., 65 to 74 years old, receiving formal nursing care), they can start making fairly simple projections along the way. of time, “Hyde added.
“It may not necessarily be when services become unaffordable, but when they are more unaffordable than they already are. We can then make these projections (costs and data) and use them to test, plan, and choose change scenarios.
“We make investments, approaches, and potential models that can save and reduce demand, and then, if they are successful, we build a evidence base that becomes stronger over time.”