Lage Ferrón M B, Díaz Jiménez J, Gestal Otero J J, de la Sierra Pajares Ortíz M, Alberdi Odriozola J C
Centro Universitario de Salud Pública de Madrid.
Rev Esp Salud Publica. 1999 Jan-Feb;73(1):45-60.
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.
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.
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.
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.
本研究旨在确定1994年至1994年期间，科鲁尼亚“胡安·卡纳莱霍”医院因器质性、循环系统和呼吸系统疾病通过急诊室入院的人数与作为外生变量引入的天气变量之间可能存在的关联，以便建立一个预测模型。
采用博克斯-詹金斯方法来获取所考虑的时间序列的单变量自回归积分滑动平均（ARIMA）模型。在残差序列之间建立互相关函数（CCF），这使得能够确定变量之间的权重和滞后，以便随后通过包含环境变量的多变量ARIMA模型进行建模。
气温升高后0至2天，因器质性疾病的急诊入院人数显著增加。呼吸系统疾病导致的入院与气温下降相关，滞后10至14天，而循环系统疾病导致的入院人数因长时间炎热天气（滞后10天）而显著增加。对于65岁以上的人，寒潮也会导致循环系统疾病急诊入院人数显著增加。考虑环境变量影响的多变量ARIMA模型对所有入院变量提供了最佳拟合。
科鲁尼亚“胡安·卡纳莱霍”医疗中心因器质性、呼吸系统和循环系统疾病导致的急诊室入院人数呈现季节性行为模式。呼吸系统疾病导致的入院与气温下降相关，而循环系统疾病导致的入院主要受炎热天气影响，不过对于65岁以上的人来说，寒冷天气也有影响。包含与气候相关变量的多变量ARIMA模型提供了一个根据这些变量预测入院人数的系统，从医院管理的角度来看可能会很有用。
