Data resource profile: the Scottish Social Care Survey (SCS) and the Scottish Care Home Census (SCHC)

Henderson, D. , Burton, J. K. , Lynch, E., Clark, D., Rintoul, J. and Bailey, N. (2019) Data resource profile: the Scottish Social Care Survey (SCS) and the Scottish Care Home Census (SCHC). International Journal of Population Data Science, 4(1), 24. (doi:10.23889/ijpds.v4i1.1108)

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Abstract

Introduction: Linked health care datasets have been used effectively in Scotland for some time. Use of social care data has been much more limited, partly because responsibility for these services is distributed across multiple local authorities. However, there are substantial interactions between health and social care (also known internationally as long-term care) services, and keen policy interest in better understanding these. We introduce two social care resources that can now be linked to health datasets at a population level across Scotland to study these interdependencies. These data emerge from the Scottish Government’s centralised collation of data from mandatory returns provided by local authorities and care homes. Methods: Deterministic and Probabilistic methods were used to match the Social Care Survey (SCS) and Scottish Care Home Census (SCHC) to the Community Health Index (CHI) number via the National Records of Scotland (NRS) Research Indexing Spine. Results: For the years 2010/11 to 2015/16, an overall match rate of 91.2% was achieved for the SCS to CHI from 31 of Scotland’s 32 local authority areas. This rate varied from 76.7% to 98.5% for local authority areas. A match rate of 89.8% to CHI was achieved for the SCHC in years 2012/13 to 2015/16 but only 52.5% for the years 2010/11 to 2011/12. Conclusion: Indexing of the SCS and SCHC to CHI offers a new and rich resource of data for health and social care research.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Henderson, David and Bailey, Professor Nick and Burton, Dr Jenni
Authors: Henderson, D., Burton, J. K., Lynch, E., Clark, D., Rintoul, J., and Bailey, N.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cardiovascular and Medical Sciences
College of Social Sciences
College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:International Journal of Population Data Science
Publisher:Swansea University
ISSN:2399-4908
ISSN (Online):2399-4908
Published Online:02 September 2019
First Published:First published in International Journal of Population Data Science 4(1):24
Publisher Policy:Reproduced under a Creative Commons license

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
651921Urban Big Data Research CentrePiyushimita ThakuriahEconomic and Social Research Council (ESRC)ES/L011921/1SPS - URBAN STUDIES
645115Scottish Administrative Data Research Centre (ADRC)Nick BaileyEconomic and Social Research Council (ESRC)ES/L007487/1SPS - URBAN STUDIES