Fone, David Lawrence ![]() |
Abstract
BACKGROUND: Primary care organisations in the United Kingdom have been given new and challenging population health responsibilities to improve health and address health inequality in local communities through partnership working with local authorities. This requires robust health and social needs assessment data for effective local planning. AIM: To assess the use and value of local authority data shared through partnership working between Caerphilly Local Health Group and Caerphilly County Borough Council. DESIGN OF STUDY: Cross-sectional analysis of aggregate electoral division data. SETTING: Caephilly County Borough, south-east Wales. METHOD: Local authority datasets identified were categorised into one of six domains: income, unemployment, housing, health, education, and social services. Data were presented at electoral division level as rates in thematic maps and correlations between the variables within and between each domain were explored using Spearman's rank correlation coefficient, with particular focus on children in families. Local planning documents were scrutinised to ascertain the use and value of the data. RESULTS: A broad range of data described a comprehensive picture of health and social inequalities within the borough. Multiple deprivation tended to cluster in electoral divisions, particularly for data relating to children, painting an overwhelming picture of inequality in life chances. The data were used in a wide range of local partnership planning initiatives, including the Health Improvement Programme, Children's Services Plan, and a successful Healthy Living Centre bid. CONCLUSION: Local authority data can help primary care organisations in a population approach to needs assessment for use in local partnership planning targeted at reducing health inequalities.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Medicine |
Subjects: | R Medicine > R Medicine (General) R Medicine > RZ Other systems of medicine |
Publisher: | Royal College of General Practitioners |
ISSN: | 0960-1643 |
Related URLs: | |
Last Modified: | 27 Oct 2022 09:56 |
URI: | https://orca.cardiff.ac.uk/id/eprint/68260 |
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