Predicting the numbers of older people “helped to live at home”
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Predicting the numbers of older people “helped to live at home”Predicting the numbers of older people “helped to live at home”
A needs-based model and its implications
Project undertaken for ADSS Eastern Region – Project Chair Hugh Gault (Cambridge CC Social Services)
Eastern Region Performance Network
BSPS Conference, University of Kent, 13 Sept 2005
© 2005 Tribal Plc Page 2
Who is “Tribal”?
A leading provider of professional support services, offering a broad range of consultancy and managed services.
Employs over 2,000 people and operates from a network of 60 offices across the UK and Eire.
Operates across the public sector, within education; health and social care; local government, housing & regeneration; and central government.
Works with 80% of secondary schools; 75% of local authorities; 90% of further education colleges; and the majority of strategic health authorities and NHS trusts.
© 2005 Tribal Plc Page 3
What does Tribal do?
Provides a wide range of services:
• Change management
• Performance improvement
• Benchmarking
• Executive resourcing & interim management
• Organisational development
• Direct service
• Strategy development & implementation
© 2005 Tribal Plc Page 4
HTLAH – starting point
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Our hypothesis
Are authorities actually providing services at a level appropriate for the needs of their population?
If so, why is this not reflected in the performance judgements?
Can we identify predictors of need?
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Social care needs model
Older People
No need for social care
Private care Need for public social care
Family networks
Housing quality
Health – mortality/ morbidity
Income (IS)
Voluntary organisations
“Social Capital”
Transport/access
Preventive services
Availability of private sector
Self-funders/income
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People who come in to the Social Services ‘domain’
Referrals Assessments
Care provision
Res/NH care
Intensive
Other HTLAH
No service
Voluntary organisations/direct access?
Eligibility Criteria
NO
YES
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Are there any predictors?
Correlations with data from 2001 census and DWP - links to deprivation:
Older people living alone
Older people in rented accommodation
Index of Multiple Deprivation (IMD 2004)
Pensioners receiving Income Support
Pensioners in overcrowded accommodation
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What about CSSR response?
FSS is allocated according to deprivation factors
£££ - The more you get, the more you
can give
…and so you should!
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The technical analysis
Started with full set of demographic data (IMD, Census and DWP) at LA level.
SPSS (stepwise regression) to identify the strongest predictors
Statistical tests to check robustness and statistical validity
Strongest combination of predictors: “lone pensioners” and “LLTI”
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Predictive model demonstrates that you can use the demographic data to calculate indicative data for HTLaH
Compared this to the actuals for 2003 & 2004
Predicted vs. actual PAF C32 PI
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Predicted vs. actual PAF C32 PI
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C32 and banding of performance
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So What?
Not all authorities have the same levels of community need
LA funding is based on assumptions of different need levels
The model isn’t perfect, but need levels can be predicted
Provision is generally consistent with predicted need levels
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Messages for LAs and CSCI
“More does not necessarily equal better”
It’s wrong to assume that there is a universal linear target
Performance must be judged in context of community needs.
Trying too hard to “improve” may lead to wasteful allocation of scarce resources.
Research, benchmarking and needs mapping are essential to understanding performance
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