\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ use_custom_gutter=”on” gutter_width=”2″ specialty=”on” parallax_method_1=”off” parallax_method_2=”off” _builder_version=”3.0.74″ transparent_background=”off”][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax__hover=”off” parallax_method__hover=”off” parallax=”off” parallax_method=”off”][et_pb_sidebar area=”et_pb_widget_area_1″ show_border=”off” admin_label=”Left Nav Sidebar” module_id=”left-nav-menu” _builder_version=”3.0.74″ remove_border=”on”]
\n[\/et_pb_sidebar][\/et_pb_column][et_pb_column type=”2_3″ specialty_columns=”2″ _builder_version=”3.0.47″ parallax__hover=”off” parallax_method__hover=”off” parallax=”off” parallax_method=”off”][et_pb_row_inner admin_label=”Row” _builder_version=”3.0.47″][et_pb_column_inner type=”4_4″ saved_specialty_column_type=”2_3″ _builder_version=”3.0.47″ parallax__hover=”off” parallax_method__hover=”on” parallax=”off” parallax_method=”on”][et_pb_text admin_label=”Text: Work programme 3″ _builder_version=”3.17.6″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” module_alignment=”left” use_border_color=”off”]<\/p>\n
Work programme 3<\/h1>\nInnovative use of data to improve social care practice<\/h2>\n
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.<\/p>\n
Projects<\/h2>\n\n- Unmasking Social Care Inequalities: Using Routine Data to Enable Reablement Equity <\/a> (April 2025 to March 2027).\u00a0 Lead: Dr Sue Davies<\/li>\n
- Developing a Social Care Strengths and Vulnerability Index (SC-SVI) for older people: a feasibility proof of concept study in local authorities<\/a>\u00a0(April 2022 to March 2024).\u00a0 Lead: Dr Paul Clarkson<\/li>\n
- <\/a>Assembling the Data Jigsaw<\/a> (May 2020 to October 2024).\u00a0Lead: Dr Paul Clarkson (social care workstream)<\/li>\n
- Translating evidence of costs and benefits of support at home in later stage dementia: to the NHS, social care and family carers <\/a>(February 2022 to March 2023).\u00a0Lead: Dr Paul Clarkson\u00a0<\/li>\n
- <\/li>\n<\/ul>\n
Background<\/h2>\n
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.\u00a0 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, local authority data organisations, and central government.\u00a0<\/p>\n
Our SC-SVI project\u00a0<\/a>investigated the viability of constructing a tool for social care, predicting well-being and threats to well-being, amongst older service users.\u00a0 The project aimed to help local authorities with their responsibilities under the Care Act, through the collection and analyses of administrative social care data.\u00a0 It sought to predict which older service users are at greater risk of entering care homes, two years after their initial assessments.\u00a0 Our results from this study are published here:\u00a0social care strengths and vulnerability in older people | PLOS One<\/a><\/p>\nOur SCI:RE Project<\/a>\u00a0is seeking to\u00a0understand patterns and trends in reablement services more clearly and how we can improve them. This will gather valuable feedback and insights, helping to improve the services offered by local authorities and how they plan them.\u00a0 We are using routinely held social care administrative data to model reablement access and receipt in Manchester City Council using area-level and person-level indicators to investigate equity in provision.\u00a0<\/span><\/span><\/p>\nOur partners<\/h2>\n\n- Performance and Intelligence, Manchester City Council<\/li>\n
- Local authorities within the\u00a0Greater Manchester Integrated Care Partnership <\/a><\/li>\n
- Department of Computer Science, University of Manchester<\/li>\n
- Division of Informatics, Imaging & Data Sciences, University of Manchester<\/span><\/li>\n
- Christabel Pankhurst Institute | The University of Manchester<\/a><\/span><\/li>\n
- made by mortals<\/a><\/span><\/li>\n
- Local Area Research & Intelligence Association<\/a>\u00a0<\/li>\n<\/ul>\n
Aims<\/h2>\n
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.<\/p>\n
Our aims include:<\/p>\n
\n- 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.<\/li>\n
- Partnership working between university researchers and local authority data officers, in analysing social care data for research.<\/li>\n
- 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.\u00a0<\/li>\n
- Tackling IT governance\/technical issues to prepare routinely held social care data and integrating these with local NHS data for use in research.<\/li>\n<\/ul>\n
What we are doing<\/h2>\n
We are working alongside local authority staff \u2013 data analysts, managers and practitioners \u2013 to collect and analyse the data, address issues and challenges and sharing learning across local authorities more widely.\u00a0<\/p>\n
<\/p>\n
Our team<\/h2>\n\n- <\/a><\/li>\n
- <\/a>Sue Davies<\/u><\/a> \u2013 Lead, Research Fellow, Social Care and Society<\/li>\n
- Paul Clarkson<\/a> – Senior Lecturer in Social Care, Social Care and Society<\/li>\n
- Catherine Robinson<\/a>\u00a0\u2013 Professor of Social Care, Social Care and Society<\/li>\n
- Dr Glen Martin<\/a> \u2013 <\/span>Senior Lecturer in Health Data Sciences<\/span>, Division of Informatics, Imaging & Data Sciences<\/span><\/li>\n
- Professor Goran Nenadic<\/a> \u2013\u00a0Professor of Computer Science,<\/span>\u00a0University of Manchester<\/li>\n
- Paul Hine, Made by Mortals CIC, Ashton, Greater Manchester \/ Honorary Research Fellow, Social Care and Society<\/li>\n
- Helen Zheng<\/a> – Senior Lecturer in Spatial Planning, University of Manchester<\/li>\n
- Leo Wall – Performance and Intelligence, Manchester City Council \/ Honorary Research Fellow, Social Care and Society<\/span><\/li>\n
- <\/li>\n<\/ul>\n
[\/et_pb_text][et_pb_divider _builder_version=”3.17.6″]
\n[\/et_pb_divider][et_pb_text admin_label=”Text: Links to other work programmes” _builder_version=”3.17.6″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” module_alignment=”left” use_border_color=”off”]<\/p>\n
Other work programmes:<\/h3>\n\n- Work programme 1: Health and social care delivery<\/u><\/a><\/li>\n
- Work programme 2: Social care in the criminal and social justice system<\/u><\/a><\/u><\/li>\n
- Work programme 4: Mental health social care<\/u><\/a><\/li>\n<\/ul>\n
[\/et_pb_text][\/et_pb_column_inner][\/et_pb_row_inner][\/et_pb_column][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Connect Title” module_class=”footer-section” _builder_version=”3.0.90″ background_color=”#1d1d1d” custom_padding=”0px||0px|” global_module=”380″][et_pb_row parallax_method_1=”off” parallax_method_2=”off” parallax_method_3=”off” admin_label=”row” module_id=”footer-row” _builder_version=”3.0.89″ locked=”off”][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax=”off” parallax_method=”off”][et_pb_text admin_label=”Contact Us Title” _builder_version=”3.0.74″ text_text_color=”#ffffff” background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark”]<\/p>\n
Contact Us<\/h4>\n
[\/et_pb_text][et_pb_text admin_label=”Contact Us” module_class=”contact-us” _builder_version=”3.0.87″ text_text_color=”#aaaaaa” background_size=”initial” background_position=”top_left” background_repeat=”repeat” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n
+44 (0) 161 306 6000<\/p>\n
[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax=”off” parallax_method=”off”][et_pb_text admin_label=”Find Us Title” _builder_version=”3.0.74″ text_text_color=”#ffffff” background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark”]<\/p>\n
Find Us<\/h4>\n
[\/et_pb_text][et_pb_text admin_label=”Address” module_id=”address” _builder_version=”3.0.87″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n
The University of Manchester
Oxford Rd
Manchester
M13 9PL
UK<\/a><\/p>\n[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax=”off” parallax_method=”off”][et_pb_text admin_label=”Connect Title” _builder_version=”3.0.74″ text_text_color=”#ffffff” background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark”]<\/p>\n
Connect With Us<\/h4>\n
[\/et_pb_text][et_pb_code admin_label=”Social Media” _builder_version=”3.17.6″]<\/p>\n
<\/pee> <\/pee><\/pee> <\/pee><\/p>\n-
![\"Facebook](\"\/\/assets.manchester.ac.uk\/phase1\/templates\/images\/icon-facebook-50.png\")
<\/a><\/li>\n<\/pee><\/pee> <\/pee><\/pee> <\/pee><\/pee> <\/pee><\/p>\n-
![\"Twitter](\"\/\/assets.manchester.ac.uk\/phase1\/templates\/images\/icon-twitter-50.png\")
<\/a><\/li>\n<\/pee><\/pee> <\/pee><\/pee> <\/pee><\/pee> <\/pee><\/p>\n-
![\"YouTube](\"\/\/assets.manchester.ac.uk\/phase1\/templates\/images\/icon-youtube-50.png\")
<\/a><\/li>\n<\/pee><\/pee> <\/pee><\/pee> <\/pee><\/pee> <\/pee><\/p>\n-
![\"Instagram](\"\/\/assets.manchester.ac.uk\/phase1\/templates\/images\/icon-instagram-50.svg\")
<\/a><\/li>\n<\/pee><\/pee> <\/pee> <\/a><\/li>\n<\/pee><\/pee> <\/pee><\/pee> <\/pee><\/pee> <\/pee><\/p>\n-
![\"LinkedIn](\"https:\/\/assets.manchester.ac.uk\/shared\/images\/design\/social-media-icons\/icon-linkedin-R-54.png\")
<\/a><\/li>\n
Background<\/h2>\n
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.\u00a0 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, local authority data organisations, and central government.\u00a0<\/p>\n
Our SC-SVI project\u00a0<\/a>investigated the viability of constructing a tool for social care, predicting well-being and threats to well-being, amongst older service users.\u00a0 The project aimed to help local authorities with their responsibilities under the Care Act, through the collection and analyses of administrative social care data.\u00a0 It sought to predict which older service users are at greater risk of entering care homes, two years after their initial assessments.\u00a0 Our results from this study are published here:\u00a0social care strengths and vulnerability in older people | PLOS One<\/a><\/p>\n Our SCI:RE Project<\/a>\u00a0is seeking to\u00a0understand patterns and trends in reablement services more clearly and how we can improve them. This will gather valuable feedback and insights, helping to improve the services offered by local authorities and how they plan them.\u00a0 We are using routinely held social care administrative data to model reablement access and receipt in Manchester City Council using area-level and person-level indicators to investigate equity in provision.\u00a0<\/span><\/span><\/p>\n 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.<\/p>\n Our aims include:<\/p>\n We are working alongside local authority staff \u2013 data analysts, managers and practitioners \u2013 to collect and analyse the data, address issues and challenges and sharing learning across local authorities more widely.\u00a0<\/p>\n <\/p>\n [\/et_pb_text][et_pb_divider _builder_version=”3.17.6″] [\/et_pb_text][\/et_pb_column_inner][\/et_pb_row_inner][\/et_pb_column][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Connect Title” module_class=”footer-section” _builder_version=”3.0.90″ background_color=”#1d1d1d” custom_padding=”0px||0px|” global_module=”380″][et_pb_row parallax_method_1=”off” parallax_method_2=”off” parallax_method_3=”off” admin_label=”row” module_id=”footer-row” _builder_version=”3.0.89″ locked=”off”][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax=”off” parallax_method=”off”][et_pb_text admin_label=”Contact Us Title” _builder_version=”3.0.74″ text_text_color=”#ffffff” background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark”]<\/p>\n [\/et_pb_text][et_pb_text admin_label=”Contact Us” module_class=”contact-us” _builder_version=”3.0.87″ text_text_color=”#aaaaaa” background_size=”initial” background_position=”top_left” background_repeat=”repeat” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n +44 (0) 161 306 6000<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax=”off” parallax_method=”off”][et_pb_text admin_label=”Find Us Title” _builder_version=”3.0.74″ text_text_color=”#ffffff” background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark”]<\/p>\n [\/et_pb_text][et_pb_text admin_label=”Address” module_id=”address” _builder_version=”3.0.87″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark” use_border_color=”off” border_color=”#ffffff” border_style=”solid”]<\/p>\n The University of Manchester [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.0.47″ parallax=”off” parallax_method=”off”][et_pb_text admin_label=”Connect Title” _builder_version=”3.0.74″ text_text_color=”#ffffff” background_size=”initial” background_position=”top_left” background_repeat=”repeat” background_layout=”dark”]<\/p>\n [\/et_pb_text][et_pb_code admin_label=”Social Media” _builder_version=”3.17.6″]<\/p>\nOur partners<\/h2>\n
\n
Aims<\/h2>\n
\n
What we are doing<\/h2>\n
Our team<\/h2>\n
\n
\n[\/et_pb_divider][et_pb_text admin_label=”Text: Links to other work programmes” _builder_version=”3.17.6″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” module_alignment=”left” use_border_color=”off”]<\/p>\nOther work programmes:<\/h3>\n
\n
Contact Us<\/h4>\n
Find Us<\/h4>\n
Oxford Rd
Manchester
M13 9PL
UK<\/a><\/p>\nConnect With Us<\/h4>\n
<\/pee>
<\/a><\/li>\n <\/a><\/li>\n <\/a><\/li>\n <\/a><\/li>\n <\/a><\/li>\n