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A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England

While incidence studies based on hospitalisation counts are commonly used for public health decision-making, no standard methodology to define hospitals' catchment population exists. We conducted a review of all published community-acquired pneumonia studies in England indexed in PubMed and ass...

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Autores principales: Campling, James, Begier, Elizabeth, Vyse, Andrew, Hyams, Catherine, Heaton, Dave, Southern, Jo, Finn, Adam, Madhava, Harish, Gessner, Bradford D., Ellsbury, Gillian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386789/
https://www.ncbi.nlm.nih.gov/pubmed/35811424
http://dx.doi.org/10.1017/S0950268822000917
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author Campling, James
Begier, Elizabeth
Vyse, Andrew
Hyams, Catherine
Heaton, Dave
Southern, Jo
Finn, Adam
Madhava, Harish
Gessner, Bradford D.
Ellsbury, Gillian
author_facet Campling, James
Begier, Elizabeth
Vyse, Andrew
Hyams, Catherine
Heaton, Dave
Southern, Jo
Finn, Adam
Madhava, Harish
Gessner, Bradford D.
Ellsbury, Gillian
author_sort Campling, James
collection PubMed
description While incidence studies based on hospitalisation counts are commonly used for public health decision-making, no standard methodology to define hospitals' catchment population exists. We conducted a review of all published community-acquired pneumonia studies in England indexed in PubMed and assessed methods for determining denominators when calculating incidence in hospital-based surveillance studies. Denominators primarily were derived from census-based population estimates of local geographic boundaries and none attempted to determine denominators based on actual hospital access patterns in the community. We describe a new approach to accurately define population denominators based on historical patient healthcare utilisation data. This offers benefits over the more established methodologies which are dependent on assumptions regarding healthcare-seeking behaviour. Our new approach may be applicable to a wide range of health conditions and provides a framework to more accurately determine hospital catchment. This should increase the accuracy of disease incidence estimates based on hospitalised events, improving information available for public health decision making and service delivery planning.
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spelling pubmed-93867892022-08-23 A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England Campling, James Begier, Elizabeth Vyse, Andrew Hyams, Catherine Heaton, Dave Southern, Jo Finn, Adam Madhava, Harish Gessner, Bradford D. Ellsbury, Gillian Epidemiol Infect Original Paper While incidence studies based on hospitalisation counts are commonly used for public health decision-making, no standard methodology to define hospitals' catchment population exists. We conducted a review of all published community-acquired pneumonia studies in England indexed in PubMed and assessed methods for determining denominators when calculating incidence in hospital-based surveillance studies. Denominators primarily were derived from census-based population estimates of local geographic boundaries and none attempted to determine denominators based on actual hospital access patterns in the community. We describe a new approach to accurately define population denominators based on historical patient healthcare utilisation data. This offers benefits over the more established methodologies which are dependent on assumptions regarding healthcare-seeking behaviour. Our new approach may be applicable to a wide range of health conditions and provides a framework to more accurately determine hospital catchment. This should increase the accuracy of disease incidence estimates based on hospitalised events, improving information available for public health decision making and service delivery planning. Cambridge University Press 2022-07-11 /pmc/articles/PMC9386789/ /pubmed/35811424 http://dx.doi.org/10.1017/S0950268822000917 Text en © Open Health, University of Bristol, and Pfizer 2022 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.
spellingShingle Original Paper
Campling, James
Begier, Elizabeth
Vyse, Andrew
Hyams, Catherine
Heaton, Dave
Southern, Jo
Finn, Adam
Madhava, Harish
Gessner, Bradford D.
Ellsbury, Gillian
A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England
title A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England
title_full A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England
title_fullStr A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England
title_full_unstemmed A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England
title_short A novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in England
title_sort novel approach to estimate the local population denominator to calculate disease incidence for hospital-based health events in england
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386789/
https://www.ncbi.nlm.nih.gov/pubmed/35811424
http://dx.doi.org/10.1017/S0950268822000917
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