Institute for Clinical Evaluative Sciences, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada; Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
J Pediatr. 2013 Oct;163(4):1073-9.e3. doi: 10.1016/j.jpeds.2013.05.034. Epub 2013 Jul 1.
To validate an algorithm to identify cases of intussusception using the health administrative data of Ontario, Canada, and to apply the algorithm to estimate provincial incidence of intussusception, preceding the introduction of the universal rotavirus vaccination program.
We determined the accuracy of various combinations of diagnostic, procedural, and billing codes using the chart-abstracted diagnoses of patients of the Children's Hospital of Eastern Ontario as the reference standard. We selected an algorithm that maximized positive predictive value while maintaining a high sensitivity and used it to ascertain annual incidence of intussusception for fiscal years 1995-2010. We explored temporal trends in incidence using Poisson regression.
The selected algorithm included only the International Classification of Diseases (ICD)-9 or ICD-10 code for intussusception in the hospitalization database and was sensitive (89.3%) and highly specific (>99.9%). The positive predictive value of the ICD code was 72.4%, and the negative predictive value was >99.9%. We observed the highest mean incidence (34 per 100000) in male children <1 year of age. Temporal trends in incidence varied by age group. There was a significant mean decrease in incidence of 4% per year in infants (<1 year) until 2004 and rates stabilized thereafter.
We have demonstrated that intussusception can be accurately identified within health administrative data using validated algorithms. We have described changes in temporal trends in intussusception incidence in Ontario and established a baseline to allow ongoing monitoring as part of vaccine safety surveillance.
验证一种使用加拿大安大略省卫生行政数据识别肠套叠病例的算法，并在普遍使用轮状病毒疫苗接种计划之前，应用该算法估计全省肠套叠的发病率。
我们使用安大略省儿童医院的图表摘要患者诊断作为参考标准，确定了各种诊断、程序和计费代码组合的准确性。我们选择了一种在保持高灵敏度的同时最大化阳性预测值的算法，并用于确定 1995 年至 2010 年财政年度的肠套叠年发病率。我们使用泊松回归探索发病率的时间趋势。
选定的算法仅包括住院数据库中的国际疾病分类（ICD）-9 或 ICD-10 肠套叠代码，具有较高的灵敏度（89.3%）和特异性（>99.9%）。ICD 代码的阳性预测值为 72.4%，阴性预测值>99.9%。我们观察到男性<1 岁儿童的平均发病率最高（34/100000）。发病率的时间趋势因年龄组而异。<1 岁的婴儿发病率每年平均下降 4%，直到 2004 年，此后发病率稳定。
我们已经证明，使用经过验证的算法，可以在卫生行政数据中准确识别肠套叠。我们描述了安大略省肠套叠发病率的时间趋势变化，并建立了一个基线，以便作为疫苗安全性监测的一部分进行持续监测。
