Administrative data are frequently used to identify Autism Spectrum Disorder (ASD) cases in epidemiological studies. However, validation studies on this mode of case ascertainment have lacked access to high‐quality clinical diagnostic data and have not followed published reporting guidelines. We report on the diagnostic accuracy of using readily available health administrative data for pediatric ASD case ascertainment. The validation cohort included almost all the ASD‐positive children born in British Columbia, Canada from April 1, 2000 to December 31, 2009 and consisted of 8,670 children in total. 4,079 ASD‐positive and 2,787 ASD‐negative children were identified using Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview‐Revised (ADI‐R) assessments done through the British Columbia Autism Assessment Network (BCAAN). An additional 1,804 ADOS/ADI‐R assessed ASD‐positive children were identified using Ministry of Education records. This prospectively collected clinical data (the diagnostic gold standard) was then linked to each child's physician billing and hospital discharge data. The diagnostic accuracy of 11 algorithms that used the administrative data to assign ASD case status was assessed. For all algorithms, high positive predictive values (PPVs) were observed alongside low values for other measures of diagnostic accuracy illustrating that PPVs alone are not an adequate measure of diagnostic accuracy. We show that British Columbia's health administrative data cannot reliably be used to discriminate between children with ASD and children with other developmental disorders. Utilizing these data may result in misclassification bias. Methodologically sound, region‐specific validation studies are needed to support the use of administrative data for ASD case ascertainment. Autism Res 2020, 13: 456–463. © 2019 International Society for Autism Research, Wiley Periodicals, Inc.

中文翻译：

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使用卫生管理数据识别小儿自闭症谱系障碍病例。

在流行病学研究中，经常使用行政数据来识别自闭症谱系障碍（ASD）病例。但是，关于这种病例确定模式的验证研究缺乏获得高质量临床诊断数据的途径，也没有遵循已发布的报告指南。我们报告了使用现成的卫生管理数据进行儿科ASD病例确诊的诊断准确性。验证队列包括从2000年4月1日到2009年12月31日在加拿大不列颠哥伦比亚省出生的几乎所有ASD阳性儿童，包括8670名儿童。通过自闭症诊断观察时间表（ADOS）和通过不列颠哥伦比亚省自闭症评估网络（BCAAN）进行的自闭症诊断面试修订（ADI-R）评估，确定了4,079名ASD阳性和2,787名ASD阴性儿童。根据教育部的记录，还确定了另外1,804名经ADOS / ADI‐R评估的ASD阳性儿童。然后将这些前瞻性收集的临床数据（诊断金标准）链接到每个孩子的医生账单和医院出院数据。评估了11种使用管理数据分配ASD病例状态的算法的诊断准确性。对于所有算法，在其他诊断准确度指标中均观察到较高的阳性预测值（PPV）和较低值，这说明单独使用PPV不足以作为诊断准确度的指标。我们表明，不列颠哥伦比亚省的卫生行政数据不能可靠地用于区分ASD儿童和其他发育障碍儿童。利用这些数据可能会导致分类错误。Autism Res 2020，13：456-463。©2019国际自闭症研究会，Wiley Periodicals，Inc.