US Department of Education Data on “Autism” Are Not Reliable for Tracking Autism Prevalence

Abstract

ABSTRACT. Many autism advocacy groups use the data collected by the US Department of Education (USDE) to show a rapidly increasing prevalence of autism. Closer examination of these data to follow each birth-year cohort reveals anomalies within the USDE data on autism. The USDE data show not only a rise in overall autism prevalence with time but also a significant and nearly linear rise in autism prevalence within a birth-year cohort as it ages, with significant numbers of new cases as late as 17 years of age. In addition, an unexpected reduction in the rise of autism prevalence occurs in most cohorts at 12 years of age, the age when most children would be entering middle school. These anomalies point to internal problems in the USDE data that make them unsuitable for tracking autism prevalence. Pediatrics 2005;116:e120-e124. URL: www. pediatrics.org/cgi

Trends in Autism Prevalence: Diagnostic Substitution Revisited

“…A number of researchers have highlighted the complexity of interpreting changes in autism prevalence when relying on administrative data, particularly educational data (Volkmar et al 2004;Newschaffer et al 2005;Mandell and Palmer 2005;Laidler 2005). This is true for the BC data, where a number of factors complicate the interpretation of changes in the proportion of children assigned the special education code for autism.…”

Identification and Evaluation of Children With Autism Spectrum Disorders

“…This reflects the phenomenon of "diagnostic substitution," whereby the number of children receiving special education under other categories (primarily MR, speech impairment, and learning disabilities) has decreased over the same time period. In addition, some increase in prevalence may be attributable to inaccuracies in diagnosis for a number of reasons, including labeling biases when schools used less rigorous criteria than those needed for a DSM diagnosis, [44][45][46][47][48] when educational funding trends influenced diagnosis, 49 and/or when parents of children with marginal criteria advocated for the AD label to qualify for supplementary services (eg, year-round schooling) described in the IDEA amendments. 50,51 The impact of these factors on current prevalence estimates has been controversial and illustrates the reason why educational administrative data reported in some studies that receive media attention should not be considered for epidemiologic studies.…”

Changes in the Administrative Prevalence of Autism Spectrum Disorders: Contribution of Special Education and Health from 2002–2008

“…The CDC's record review system has been found to be conservative in determining ASD case status (Avchen et al 2010). A number of researchers have made the point that surveillance methods that rely on a previous clinical diagnosis only or on single administrative datasets potentially under estimates the number of children with ASD in the population (Barbaresi et al 2005;CDC 2007;CDC 2009;Laidler 2005;Newschaffer et al 2005;PinboroughZimmerman et al 2010;Shattuck 2006). With this in mind efforts are underway to validate Utah's administrative prevalence in a subset of our surveillance population using the CDC's surveillance approach which includes an expert review of abstracted charts for the identification of previously undiagnosed children meeting study ASD case definitions (Van Naarden Braun et al 2007) and verification of the ASD diagnosis in the record.…”

“…Increased availability and access to more data sources has been correlated with higher ASD prevalence in previous studies (CDC 2007;CDC 2009). Conversely, prevalence has been consistently lower in studies in which case ascertainment has been based on health-only or special education-only administrative records (CDC 2007;CDC 2009;Fombonne 2001;Laidler 2005;Newschaffer et al 2005;Pinborough-Zimmerman et al 2010). Demographic factors such as population age also influence prevalence rates.…”