Worcestershire County Council saw a need to develop improved foresight relating to demands on its health and welfare services in response to the pandemic.
The COVID-19 pandemic highlighted just how important it is for councils to have insights about their most vulnerable residents. By connecting disparate datasets with confidence, vulnerable residents can be given the help they need. This integration becomes the backbone of authorities’ plans to provide life-changing support, and to report on their performance both for future planning purposes and the public interest.
Worcestershire County Council saw a need to develop improved foresight relating to demands on its health and welfare services in response to the pandemic. The council also wanted to predict longer-term care needs of individuals in the area. It used risk stratification to identify households likely to need support from older adult social care in the future. The aim was to identify potential target groups or locations in the county for preventative activity, communication, information and advice. This project built on the NHS Digital Project to predict social care self-funder pick-ups.
Worcestershire used a range of datasets with indicators that might predict a need for increased social care. These included energy efficiency (EPC, thermal imaging), hospital admissions and social care (unfortunately, specific data sharing agreements prevented Worcestershire from using Council Tax single occupancy data).
However, once the datasets had been gathered, it was possible to match these and start running analysis by using the UPRN. Some datasets matched by address were hard to correlate due to differing formats (flats, for example), but UPRNs played the key role even when matching had to be done manually as oppose to automatically. This allowed Worcestershire County Council to test by how well indicators identify households currently receiving older adult social care services at home or in the community.
By matching using UPRNs to match disparate datasets, Worcestershire confirmed that thermal imaging data correlated with 0.8% of households receiving social care. In the process, it was also revealed that households in certain areas were six times more likely to have someone over the age of 65 who needed social care. It was also found that households in certain areas with high hospital admission rates were 14 times more likely to have someone over the age of 65 who needed social care.
Challenges & Lessons Learned
Worcestershire found it could use combined datasets to identify households likely to be at higher risk of needing social care. 11.2% of households with a combination of indicators had someone with social care aged 65+ compared with 0.8% for all households. However, it also became apparent that some indicators were not good predictors of risk.
Households with someone aged 65+ receiving social care, for example, were less likely to have a high EPC / poor thermal rating than other households. It was also recognised that the addition of some indicators could increase the proportion likely to be at risk, but also lower the size of the target group. However, Worcestershire’s overall approach and commitment to incorporating the UPRN identified around 1,000 households not currently receiving social care that could be targeted for preventative activity.
The council has plans to work on intervention to reduce risk. The information gathered from the project was provided to the Social Care team at the council who plan to use the data gathered in their responses to predicting long-term care needs. The UPRN played a vital role in the prediction of these needs: in short, the UPRN was the key data set that allowed disparate data sets to be linked together.
Jennie Humphries, Research Project Manager, Worcestershire County Council firstname.lastname@example.org