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Investigating trends in asthma and COPD through multiple data sources: A small area study.

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journal contribution
posted on 18.09.2019, 16:42 by Areti Boulieri, Anna Hansell, Marta Blangiardo
This paper investigates trends in asthma and COPD by using multiple data sources to help understanding the relationships between disease prevalence, morbidity and mortality. GP drug prescriptions, hospital admissions, and deaths are analysed at clinical commissioning group (CCG) level in England from August 2010 to March 2011. A Bayesian hierarchical model is used for the analysis, which takes into account the complex space and time dependencies of asthma and COPD, while it is also able to detect unusual areas. Main findings show important discrepancies across the different data sources, reflecting the different groups of patients that are represented. In addition, the detection mechanism that is provided by the model, together with inference on the spatial, and temporal variation, provide a better picture of the respiratory health problem.

Funding

The work of the UK Small Area Health Statistics Unit is funded by Public Health England as part of the MRC-PHE Centre for Environment and Health, funded also by the UK Medical Research Council (grant no. MR/L01341X/1). SAHSU holds approvals from the National Research Ethics Service — reference 12/LO/0566 and 12/LO/0567 - and from the Health Research Authority Confidentially Advisory Group (HRA-CAG) for Section 251 support (HRA - 14/CAG/1039). Hospital Episode Statistics data are copyright 2014, re-used with the permission of the Health and Social Care Information Centre. All rights reserved.

History

Citation

Spatial and Spatio-temporal Epidemiology, 2016, 19, pp. 28-36

Author affiliation

/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Health Sciences

Version

VoR (Version of Record)

Published in

Spatial and Spatio-temporal Epidemiology

Publisher

Elsevier

eissn

1877-5853

Acceptance date

17/05/2016

Copyright date

2016

Available date

18/09/2019

Publisher version

https://www.sciencedirect.com/science/article/pii/S1877584515300368?via=ihub

Language

en