汕头市某三甲医院2002-2012年交通伤害病例的时间序列分析

目的建立汕头市某三甲医院道路交通伤害（road traffic injury,RTI）病例的预测模型,并对该医院接收RTI病例数的变化趋势进行预测分析,为RTI的预防和控制提供参考依据。方法收集汕头市某三甲医院2002年10月～2012年5月RTI病例,以每月发生例数进行整理,采用统计软件SPSS19.0和Stata12.1进行时间序列分析,建立自回归综合移动平均模型（autoregressive integrated moving average,ARIMA）,并进行预测分析。结果通过建模流程最终拟合的模型为ARIMA（1,2,2）,经Box-Ljung检验所有Q统计量均无统计学意义（均有P〉0.05）,残差序列的白噪声检验结果亦显示模型残差序列为白噪声序列,且观察值均在拟合值的可信区间内,说明所建模型拟合度较好,预测分析结果显示该医院接收RTI病例数在未来两年有增加的趋势。结论 ARIMA模型能较好地预测RTI的发生和变化趋势,具有较高的应用价值,可为预防和控制RTI提供信息支持。

The traffic injuries of a tertiary hospital in Shantou City: a time-series analysis, 2002-2012

Objective To establish a predictive model for road traffic injuries （RTI） of a tertiary hospital in Shantou City, and to predict the occurrence and trend of the RTI cases in this hospital for the prevention and control of RTI. Methods The RTI cases of a tertiary hospital in Shantou during October, 2002 to May, 2012 were collected and grouped by monthly occurrence. Statistical software SPSS 19.0 and Stata 12. 1 were used to conduct the time-series analysis, and to establish autoregressive integrated moving average model （ARIMA model）. The trend of RTI was predicted. Results Through the process of modeling, the ultimately fitting model was ARIMA（ 1, 2, 2） ,the Box-Ljung test for the model was not statistically significant （ all P 〉 0. 05） and the residual error was white noise, and all the observed values were in the confidence interval of the fitted values, meaning the model fitted the data well. The predictive analysis results showed that there was an upward trend of the RTI cases of this hospital in the next two years. Conclusions ARIMA model can predict the trend of RTI well and is a significant tool in the prediction of RTI. Therefore, ARIMA can provide evidences for RTI in- tervention and control.