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Assessing local chlamydia screening performance by combining survey and administrative data to account for differences in local population characteristics

Green, N; Sherrard-Smith, E; Tanton, C; Sonnenberg, P; Mercer, CH; White, PJ; (2019) Assessing local chlamydia screening performance by combining survey and administrative data to account for differences in local population characteristics. Scientific Reports , 9 , Article 7070. 10.1038/s41598-019-43521-y. Green open access

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Abstract

Reducing health inequalities requires improved understanding of the causes of variation. Local-level variation reflects differences in local population characteristics and health system performance. Identifying low- and high-performing localities allows investigation into these differences. We used Multilevel Regression with Post-stratification (MRP) to synthesise data from multiple sources, using chlamydia testing as our example. We used national probability survey data to identify individual-level characteristics associated with chlamydia testing and combined this with local-level census data to calculate expected levels of testing in each local authority (LA) in England, allowing us to identify LAs where observed chlamydia testing rates were lower or higher than expected, given population characteristics. Taking account of multiple covariates, including age, sex, ethnicity, student and cohabiting status, 5.4% and 3.5% of LAs had testing rates higher than expected for 95% and 99% posterior credible intervals, respectively; 60.9% and 50.8% had rates lower than expected. Residual differences between observed and MRP expected values were smallest for LAs with large proportions of non-white ethnic populations. London boroughs that were markedly different from expected MRP values (≥90% posterior exceedance probability) had actively targeted risk groups. This type of synthesis allows more refined inferences to be made at small-area levels than previously feasible.

Type: Article
Title: Assessing local chlamydia screening performance by combining survey and administrative data to account for differences in local population characteristics
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41598-019-43521-y
Publisher version: https://doi.org/10.1038/s41598-019-43521-y
Language: English
Additional information: © The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Keywords: Bacterial infection, Risk factors
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health > Infection and Population Health
URI: https://discovery.ucl.ac.uk/id/eprint/10074262
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