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Explaining local variation in home care provision using a longitudinal census of home care

2018 Conference Presentation

Equity ScotlandUnited Kingdom

10 September 2018

Explaining local variation in home care provision using a longitudinal census of home care

David Bell, University of Stirling, United Kingdom

Elizabeth Lemmon, University of Stirling


Background: Effective, high quality care for older people is an objective to which many countries aspire, but as their populations age, they find increasingly difficult to provide. High quality care policy has to be grounded on high quality evidence, but relatively few countries have a clear picture of how the social care sector functions.

Objectives and methods: Scotland is an exception: it has carried out an annual longitudinal census of domiciliary (home) care since 2009. This paper uses this census to explore the reasons for local variation in home care provision across Scotland. It explains how the census is constructed and sets it within the context of social care policy in Scotland, which includes the offer of “free personal care” to those living in their own home and assessed as being in need of such care. By “provision”, we mean both the offer of any care as well as the cost of the care package supplied. Using panel regression techniques, the paper explores how far variations in provision reflect differences in individual or local area characteristics. Individual characteristics include age, gender, living alone, has dementia etc. Area characteristics include level of deprivation, median income, rurality, local authority budget devoted to older people etc.

Results: The paper finds that individuals and area characteristics have an important role in explaining variations in long-term care provision, but there remains significant unexplained variation between local authorities in both the availability and the size of care packages. This suggests that there are opportunities for improving long-term care provision through enhanced efficiency. The paper concludes by discussing possible reasons for this variation and the possibility of use scores derived from the regression analysis to drive such improvements.