HOW ASCOF DATA CAN BE USED TO SUPPORT LOCAL DECISION-MAKING AND SERVICE IMPROVEMENTS

The Adult Social Care Outcomes Framework (ASCOF) provides local authorities (LAs) with robust information that can be used at a local and regional level to guide the design and delivery of local outcomes-focused services (see Table 1). While a number of indicators in the ASCOF are currently populated by data from the Adult Social Care Survey (ASCS) and Carers’ Survey (PSS SACE) [click here for an overview], many of the LA staff we have spoken during the course of our activities expressed uncertainty how to use their survey datasets to fulfil the functions of the framework. The purpose of this blog, therefore, is to provide some suggestions and to highlight the elements of the MAX toolkit that may be of value.
Table 1: Local and regional functions of the adult social care outcomes framework (ASCOF)

ASCOF functions

Local level functions
Proving robust information that enables LAs to monitor the success of local interventions in improving outcomes and identify their priorities for making improvements.
Using data to inform outcomes-based commissioning models and, via Health and Wellbeing boards, inform their strategic planning and leadership role for local commissioning.
Strengthen accountability to local people.
Regional level functions
Support sector-led improvement; bringing LAs together to understand and benchmark their performance and, in turn, stimulating discussions between LAs on priorities for improvement, and promoting the sharing of learning and best practice.

Adapted from the ASCOF 2016/17 handbook of definitions
Monitor the success of local interventions in improving outcomes


LA decision-makers and service teams are (understandably) interested in knowing whether the services and support they provide are helping service users to enjoy a better quality of life. Service impact – in other words, the success of local interventions in improving outcomes – is commonly assessed using direct comparisons of ASCOF 1A (social care-related quality of life [SCRQOL]) and ASCOF 1D (carer-reported quality of life). Calculations produced during another project conducted here at PSSRU (click here for further information) now means that these scores can be adjusted to control for the factors associated with the service user (including the carer) that are known to affect quality of life but are beyond the control of LA services. The adjusted scores provide a more accurate estimate of service impact and can be used to [1] assess how local services are helping service users to have a better quality of life and [2] track changes or differences in service-user reported outcomes over time and between organisations.

From 2016/17, the ASCOF includes the adjustment calculation for the ASCS (ASCOF 1J: adjusted SCRQOL). Those of you wishing to interpret these scores and/or calculate adjusted scores for the previous data collections or the carer equivalent can use the excel-based tools included in the MAX toolkit. Suggestions on how to explore, interpret and report these scores are provided in the EXPLORING ASCS DATA GUIDE and EXPLORING PSS SACE DATA GUIDE and the introduction to ASCOF 1J guide.
Identify priorities for making improvements | Inform the strategic planning and leadership role for local commissioning


Along with monitoring the success of local interventions, LA decision-makers and service teams also need to know where targeted action is required to improve reported outcomes. Focused further analysis of ASCS and PSS SACE data, including that used to populate the ASCOF indicators, can help to identify which service users and carers (if any) are reporting unmet needs, dissatisfaction and/or a low quality of life and, by doing so, establish the proprieties for local service improvements. This analysis, particularly when combined with supplementary sources of data (e.g. respondent comments in the surveys, findings from local research, LA held records), in turn, can highlight the possible reasons for any noted needs and the kinds of remedial action(s) that can be taken. The findings from this analysis can be fed back to relevant groups within your organisation and help guide local commissioning, strategic and operational decision-making and changes to front-line practice.

The ASCS FURTHER ANALYSIS GUIDE and PSS SACE FURTHER ANALYSIS GUIDE included in the MAX toolkit provides suggestions on how to transform your analysis findings into meaningful information that can guide local decision-making and service improvements.  These guides are accompanied by excel-based tools and multi-media training resources, which means that specialist training and additional software is not required.
Strengthen accountability to local people


Clearly documenting the findings from more in-depth statistical (and thematic) analysis shows that you are really are listening to the people who use your services, have identified the issues that are important to them and are committed to using their feedback to improve their quality of life and experience of services.  This not only strengthens accountability but also encourages local people to engage more with your organisation and the surveys. The MAX REPORTING GUIDE can help you to ensure that your analysis findings and/or survey feedback are communicated clearly and concisely to your intended audience(s).
Support sector-led improvements


Finally, the adjusted quality of life scores and findings from further analysis can be used to initiate discussions between local authorities. Such discussions can facilitate the identification and sharing of potentially useful local practices and, by doing so, support sector-led improvements.

As well as showing that LA staff are keen to share insights and learn from each other, our earlier and ongoing work has confirmed that some organisations have implemented strategies to improve the local relevance and value of their ASCS and PSS SACE datasets and have produced findings that can and are used to guide local service improvements. These will be shared where permitted in the MAX toolkit and, it is hoped, will be a valuable source of guidance to other LAs.
This blog is one of a series of short blogs written to help users make the most of the analysis element of the MAX toolkit and transform their ASCS and PSS SACE datasets into meaningful management information. The next blog discusses how LAs can use their survey data to service user and care profiles, and can be accessed here.
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Disclaimers
This blog is based on independent research commissioned and funded by the NIHR Policy Research Programme (Maximising the value of survey data in adult social care (MAX) project and MAX toolkit implementation and impact study). The views expressed in the publication are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health and Social Care or its arm’s length bodies or other government departments.