A model for forecasting emergency hospital admissions: effect of environmental variables.

This study modeled patterns and trends in emergency hospital admissions at a hospital in Madrid, Spain. The purpose was to quantify qualitative associations that have been detected between such admissions and a number of environmental variables. The following data were used: unscheduled daily emergency hospital admissions, Madrid air pollution data, and meteorological data. Time-series analysis was performed, with Box-Jenkins modeling. A multivariate model was constructed, incorporating the different causes of admissions and the respective environmental variables. Statistically significant associations were found between hospital admissions and other variables, indicating relationships with temperature, relative humidity, and mean daily tropospheric ozone concentrations. Whereas the effect of heat on admissions was short term, that of cold was in evidence from the second week. The association with ozone showed a seven-day lag and basically manifested itself as an influence on admissions for circulatory disease.