[Effects of environmental factors on the number of emergency admissions to the Hospital Complex Juan Canalejo in La Coruña: creation of a prediction model].

BACKGROUND

This study is aimed at establishing the possible associations between the number of admissions through the emergency room at the "Juan Canalejol" Hospital in Corunna in 1994-1994 due to organic, circulatory and respiratory reasons and the weather variables introduced as being exogenous for the purpose of preparing a prediction model.

METHODS

The Box-Jenkins methodology is used for obtaining univariate ARIMA models of the time-based series taken into consideration. Cross-Correlation Functions (CCF's) are established among the series of residuals which afford the possibility of establishing weights and lags among the variables for a subsequent modeling by means of multivariate ARIMA models which include environmental variables.

RESULTS

The emergency admissions for organic reasons significantly increase 0-2 days following a rise in temperature. The admissions due to respiratory ailments are associated with drops in temperature with 10-14 lags, whilst the admissions for circulatory reasons increase significantly due to long-lasting spells of hot weather (10 lags). For people over age 65, significant increases in emergency admissions for circulatory reasons are also recorded with cold snaps. The multivariate ARIMA models that take into account the effect of environmental variables provided the best adjustment for all of the admissions variables.

CONCLUSIONS

The number of emergency room admissions at the "Juan Canalejo" Medical Center Complex in Corunna due to organic, respiratory and circulatory causes shows a seasonal behavior pattern. The admissions for respiratory reasons are associated with a drop in temperature, whilst the admissions for circulatory reasons are affected fundamentally by hot weather, although also by cold weather as regards people over age 65. The multivariate ARIMA models including climate-related variables provide a system for predicting admissions in terms of said variables that can be useful from the standpoint of hospital management.