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Further analysis of ASCS and PSS SACE data: Case studies of local authority (LA) practice

Abstract

The Maximising the value of survey data in adult social care (MAX) project aims to develop toolkits, with local authority (LA) staff where possible, to encourage and support LAs to make more use of data drawn from the ASCS and PSS SACE1 to inform local policy and practice. The initial fact-finding phase (MAX Phase 1) activities aimed to:learn more about how LAs currently use ASCS and PSS SACE data, including identifying local practices and barriers; identify potential uses of the data to inform local decision-making; and inform the development of a toolkit to support LAs to make better local use of the data. Along with two analysis and interpretation consultation panel workshops conducted early in the second phase of the project, 139 staff from 95 LAs have so far taken part in MAX. In summary, the findings from these activities demonstrate that LAs generally seem to value the ASCS and PSS SACE and, to some extent, are using the views of service users and carers to inform local service planning and delivery. However, there were several challenges. One of these, identified by just over half of the LAs, concerned analysing the survey data and interpreting the findings to address local questions. A number of barriers seem to underlie this challenge, including difficulties with: identifying local information needs; managing and analysing ASCS and PSS SACE data; and being allocated sufficient time to conduct further analysis. While some LAs find analysing ASCS and PSS SACE data challenging, others are carrying out local statistical analysis, over and above those required for national (ASCOF) reporting. The case studies reported here describe how three local authorities have used and analysed the ASCS and PSS SACE data to support local decision-making. In turn, the case studies will be used to inform the development of ‘how to’ guides and tools to help LAs analyse and interpret survey data, as well as report and interpret analysis finding

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