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Review
. 2022 Jul 11:150:e150.
doi: 10.1017/S0950268822000917.

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

Affiliations
Review

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

James Campling et al. Epidemiol Infect. .

Abstract

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.

Keywords: Community-acquired pneumonia; epidemiology; incidence; pneumonia.

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Figures

Fig. 1.
Fig. 1.
South West England clinical commissioning groups map.
Fig. 2.
Fig. 2.
2017–2019 study hospital admissions by clinical commissioning group of the patients' GP practices.
Fig. 3.
Fig. 3.
A bar chart showing the proportion of persons hospitalised for acute lower respiratory tract disease who were hospitalised at a study hospital, stratified by individual anonymised general practice and patient age group.
Fig. 4.
Fig. 4.
Comparison of study hospital population size (⩾18yrs) by methodology.
Fig. 5.
Fig. 5.
Map showing travel time by car to study hospitals

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