@article{230fae06b801427dad1ddb18d4dd6bf1,
title = "A modelling framework for developing early warning systems of COPD emergency admissions",
abstract = "Chronic Obstructive Pulmonary Disease (COPD) is one of the leading causes of mortality worldwide and is a major contributor to the number of emergency admissions in the UK. We introduce a modelling framework for the development of early warning systems for COPD emergency admissions. We analyse the number of COPD emergency admissions using a Poisson generalised linear mixed model. We group risk factors into three main groups, namely pollution, weather and deprivation. We then carry out variable selection within each of the three domains of COPD risk. Based on a threshold of incidence rate, we then identify the model giving the highest sensitivity and specificity through the use of exceedance probabilities. The developed modelling framework provides a principled likelihood-based approach for detecting the exceedance of thresholds in COPD emergency admissions. Our results indicate that socio-economic risk factors are key to enhance the predictive power of the model.",
keywords = "COPD, Early warning system, Exceedance probabilities, Generalised linear mixed model, Spatio-temporal models",
author = "Olatunji Johnson and Jo Knight and Emanuele Giorgi",
note = "Funding Information: This research was funded by Connected Health Cities (CHC) through a PhD studentship to Olatunji. ǣConnected Health Cities is a Northern Health Science Alliance led programme funded by the Department of Health and delivered by a consortium of academic and NHS organisations across the north of England. The work uses data provided by patients and collected by the NHS as part of their care and support. The views expressed are those of the author(s) and not necessarily those of the NHSA, NHS or the Department of Health.ǥ Funding Information: This research was funded by Connected Health Cities (CHC) through a PhD studentship to Olatunji. ?Connected Health Cities is a Northern Health Science Alliance led programme funded by the Department of Health and delivered by a consortium of academic and NHS organisations across the north of England. The work uses data provided by patients and collected by the NHS as part of their care and support. The views expressed are those of the author(s) and not necessarily those of the NHSA, NHS or the Department of Health.? Publisher Copyright: {\textcopyright} 2020",
year = "2021",
month = feb,
day = "1",
doi = "10.1016/j.sste.2020.100392",
language = "English",
volume = "36",
journal = "Spatial and Spatio-temporal Epidemiology",
publisher = "Elsevier BV",
}
