Upshur Ross E G, Moineddin Rahim, Crighton Eric, Kiefer Lori, Mamdani Muhammad
Department of Family and Community Medicine, University of Toronto, 263 McCaul Street, Toronto, ON M5T 1W7, Canada.
BMC Health Serv Res. 2005 Feb 4;5(1):13. doi: 10.1186/1472-6963-5-13.
Seasonality is a common feature of communicable diseases. Less well understood is whether seasonal patterns occur for non-communicable diseases. The overall effect of seasonal fluctuations on hospital admissions has not been systematically evaluated.
This study employed time series methods on a population based retrospective cohort of for the fifty two most common causes of hospital admissions in the province of Ontario from 1988-2001. Seasonal patterns were assessed by spectral analysis and autoregressive methods. Predictive models were fit with regression techniques.
The results show that 33 of the 52 most common admission diagnoses are moderately or strongly seasonal in occurrence; 96.5% of the predicted values were within the 95% confidence interval, with 37 series having all values within the 95% confidence interval.
The study shows that hospital admissions have systematic patterns that can be understood and predicted with reasonable accuracy. These findings have implications for understanding disease etiology and health care policy and planning.
季节性是传染病的一个常见特征。对于非传染病是否存在季节性模式，人们了解得较少。季节性波动对住院人数的总体影响尚未得到系统评估。
本研究采用时间序列方法，对1988年至2001年安大略省52种最常见的住院病因进行基于人群的回顾性队列研究。通过频谱分析和自回归方法评估季节性模式。采用回归技术拟合预测模型。
结果显示，52种最常见的入院诊断中有33种在发病时有中度或强烈的季节性；96.5%的预测值在95%置信区间内，37个序列的所有值都在95%置信区间内。
该研究表明，住院人数具有可被合理准确理解和预测的系统模式。这些发现对理解疾病病因以及医疗保健政策和规划具有启示意义。
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