Exploring the effect of temperature variations on unplanned asthma admissions

Global climate change is one of the highest concerns in the scientific, health and environmental arena. Establishing association between weather and health exposures are fundamental to learn about the complex exposure-disease relationship but the link between them are still largely unexplored. The Department of Health in England sees unplanned admissions as an important issue, where the National Health Service hospitals will face financial penalties if patients are readmitted as an emergency within 30 days of being discharged. The continuing annual trend in the number of patient readmissions (5% growth during 2007/08 and 2008/09) is causing a serious concern in terms of high demand for services under severe financial cuts (the NHS is expected to save approximately £20bn over five years). We intend to explore the relationship of temperature variations with the unplanned admissions for some selected diseases (COPD, Asthma, and Pneumonia) on local authority area level. For admission information, Hospital Episode Statistics (HES), England and the temperature (maximum, minimum and mean) data from the Met Office, UK for the year 1997-2004 will be used. We linked the HES with temperature based on local authority level and day of weather observation. We will standardise the morbidity rate of unplanned admissions for the selected disease and region by adopting the respective population estimates to explore the regional differences in morbidity rate. The Poisson regression model and Zero-Inflated Poisson regression model could be used to highlight whether the relationship between temperature variations and the unplanned admission counts are significant for those selected diseases after adjusting the effect of air pollutants, age, sex and the day of the admission. The results could be helpful to understand the impact of temperature fluctuations on the unplanned admissions for the diseases and thereby help to revise the future demand of care due to the weather disparity.