Yiannakoulias N, Schopflocher D P, Svenson L W
School of Geography and Earth Sciences, McMaster University, Hamilton, ON.
Chronic Dis Can. 2009;30(1):20-8.
We examined the geographic variability of information generated from different case definitions of childhood asthma derived from administrative health data used in Alberta, Canada. Our objective was to determine if analyses based on different case ascertainment algorithms identify geographic clusters in the same region of the study area. Our study group was based on a closed cohort of asthmatic children born in 1988. We used a spatial scan statistic to identify variations in the approximate location of geographic clusters of asthma based on different case definitions. Our results indicate that the geographic patterns are not greatly affected by the case ascertainment algorithm or the source of data. For example, asthmatics identified from medical claims data showed similar clustering to asthmatics defined through hospitalization and emergency department data. However, estimates of prevalence and incidence require careful consideration and validation against other data sources.
我们研究了从加拿大艾伯塔省使用的行政健康数据得出的不同儿童哮喘病例定义所产生信息的地理变异性。我们的目标是确定基于不同病例确定算法的分析是否能在研究区域的同一地区识别出地理聚集。我们的研究组基于1988年出生的哮喘儿童的封闭队列。我们使用空间扫描统计量来识别基于不同病例定义的哮喘地理聚集大致位置的变化。我们的结果表明,地理模式受病例确定算法或数据来源的影响不大。例如,从医疗索赔数据中识别出的哮喘患者与通过住院和急诊科数据定义的哮喘患者表现出相似的聚集情况。然而,患病率和发病率的估计需要仔细考虑并与其他数据源进行验证。