López del Val J A, Calvete Fernández H I, Carreter Oróñez C A, Abaurrea León J, Muniesa Cuenca M P, García Mata J R, Hernández Navarrete M J, Arribas Llorente J L
Servicio de Medicina Preventiva, Hospital Miguel Servet, Zaragoza.
Med Clin (Barc). 1992 Jun 6;99(2):52-6.
In this study we introduce a new view of hospital infection, to apply time series techniques to it. Our objective is to complement hospital infection's epidemiological surveillance by means of obtaining alert and alarm thresholds that make easy to the epidemiologist the decision of intervention, in case they are exceeded.
We have used the classic time series analysis described by Rumeau-Rouquette, and ARIMA (Autoregresive Integrated Moving Average) models developed by Box and Jenkins. The study focus on three hospital units: one intensive care, one long term care and one surgical unit. The nosocomial infection intervals have been calculated with a 68% (1SD) and 95% (2SD) confidence levels.
We detect an ascending general trend in the last two units, without the detection of seasonal variations. Two ARIMA (1, 0, 0) models we obtained for surgery and long term care, discarding other better adjusted models, more complex and difficult to obtain, but with no real advantage in prediction power. Confidence intervals were calculated with both methods. We did not find general trend and seasonal variations for intensive care unit. No model was considered valid, because of its high random component. The nosocomial infection intervals have been calculated with mean +/- 1SD and mean +/- 2SD.
We think that more precise knowledge of hospital infection, with a high random component in our study, can be in addition useful to assign priority to human and material resources.
在本研究中，我们引入了一种医院感染的新视角，即将时间序列技术应用于其中。我们的目标是通过获取警报阈值来补充医院感染的流行病学监测，以便在阈值被突破时，流行病学家能够轻松做出干预决策。
我们使用了Rumeau - Rouquette描述的经典时间序列分析方法，以及Box和Jenkins开发的ARIMA（自回归积分移动平均）模型。该研究聚焦于三个医院科室：一个重症监护室、一个长期护理科室和一个外科科室。医院感染间隔已根据68%（1标准差）和95%（2标准差）的置信水平进行计算。
我们在最后两个科室中检测到总体呈上升趋势，未检测到季节性变化。我们为外科和长期护理科室获得了两个ARIMA(1, 0, 0)模型，舍弃了其他调整更好但更复杂且难以获得的模型，因为这些模型在预测能力上并无实际优势。两种方法都计算了置信区间。我们未在重症监护室发现总体趋势和季节性变化。由于其随机成分过高，未发现有效的模型。医院感染间隔已根据均值±1标准差和均值±2标准差进行计算。
我们认为，尽管在我们的研究中医院感染存在较高的随机成分，但对其更精确的了解仍有助于为人力和物力资源分配优先级。
