
Work programme 3
Innovative use of data to improve social care practice
Work programme 3 focuses on using routinely held social care data, linking social care and health data, and developing data collection and dissemination solutions to stimulate new, innovative ways to benefit social care evaluation and practice.
Projects
- Developing a Social Care Strengths and Vulnerability Index (SC-SVI) for older people: a feasibility proof of concept study in local authorities (April 2022 to March 2024). Lead: Dr Paul Clarkson
- Assembling the Data Jigsaw (May 2020 to October 2023). Lead: Dr Paul Clarkson (social care workstream)
- Translating evidence of costs and benefits of support at home in later stage dementia: to the NHS, social care and family carers (February 2022 to March 2023). Lead: Dr Paul Clarkson
Background
Developed through partnership with local authorities in Greater Manchester (City of Manchester, Stockport, and Salford councils), projects in this programme seek to harness the routinely held social care data that is collected within local authorities and use it for research studies to offer benefits to service delivery and to service users. We are doing this through genuine partnerships with local authorities, responding to their concerns with using data more creatively and widely to examine and evaluate services and share learning with other local authorities and government.
Our SC-SVI project investigated the viability of constructing a tool for social care, predicting well-being and threats to well-being, amongst older service users. The project aimed to help local authorities with their responsibilities under the Care Act, through the collection and analyses of administrative social care data. The study also focused on aspects of routine data in social care highlighted in the social care White Paper, People at the Heart of Care.
Our partners
- Local authorities within the Greater Manchester Integrated Care Partnership
- Department of Computer Science, University of Manchester
- Division of Informatics, Imaging & Data Sciences, University of Manchester
- Christabel Pankhurst Institute | The University of Manchester
- made by mortals
- Local Area Research & Intelligence Association
Aims
We aim to investigate how routinely generated social care data, linked to NHS data if needed, can be used for research and to evaluate policies and practice. We are interested in how these data could help professional staff, such as social workers, in their work with service users or may be used in population care planning and strategic management and evaluation. We aim to generate findings and learning of benefit to local authorities outside the region and to the emerging Integrated Care organisations.
Our aims include:
- Working out how data analysed in a research context might support assessments within local authority social care organisations or might be used to monitor local strategies and plans.
- Partnership working between university researchers and local authority data officers, in analysing social care data for research.
- Working up systems to embed research into practice, for example by sharing learning on how data analysis could be embedded in reporting systems to aid decision making.
- Tackling IT governance/technical issues to prepare routinely held social care data and integrating these with local NHS data for research.
What we are doing
We are working alongside local authority staff – data analysts, managers and practitioners – to collect and analyse the data, address issues and challenges and sharing learning across local authorities more widely.
Our team
- Paul Clarkson – Lead, Senior Lecturer in Social Care, Social Care and Society
- Sue Davies – Co-Lead, Research Associate, Social Care and Society
- Catherine Robinson – Professor of Social Care, Social Care and Society
- Dr Glen Martin – Senior Lecturer in Health Data Sciences, Division of Informatics, Imaging & Data Sciences
- Professor Goran Nenadic – Professor of Computer Science, University of Manchester
- Paul Hine, Made by Mortals CIC, Ashton, Greater Manchester