Autism and autism spectrum disorders (ASD) are not uncommon in the United States. Early diagnosis, along with early, appropriate and consistent intervention is key for improved long term-outcomes in children with ASD. General practitioners, especially pediatricians, are now seeing more children than ever with ASD in their practices. Therefore, general practitioners must increase their knowledge and comfort level in caring for these children. However, research has demonstrated that primary care physicians are more likely to demonstrate outdated beliefs and views about ASDs compared to specialists. Additionally, research has found that while routine screening for ASD is recommended by several medical associations, only 8% of Pediatricians routinely screen for ASDs. Modern computer decision support strategies offer the best hope of equipping general practitioners to deal with the challenging task of diagnosing ASD as early as possible and ensuring the timely implementation of evidence-based treatment plans. We have developed a novel decision support system for implementing clinical guidelines in pediatric practices. CHICA (Child Health Improvement through Computer Automation) combines three elements: (1) pediatric guidelines encoded in Arden Syntax;(2) a dynamic, scannable paper user interface;and (3) an HL7-compliant interface to existing electronic medical record systems. The result is a system that both delivers """"""""just-in-time"""""""" patient-relevant guidelines to physicians during the clinical encounter and accurately captures structured data from all who interact with it. We propose to expand CHICA to include ASD screening, diagnosis, and treatment parameters. The specific research aims of this application are to: (1) expand and modify an existing computer-based decision support system (CHICA) to assist pediatricians with identification and management of ASDs;(2) evaluate the effect of the CHICA system ASD screening and surveillance module on the early identification of ASD in four pediatric practices;(3) collect early data on the effect of the CHICA system on services provided to children diagnosed with ASD and how these affect patient outcomes. This study will include a randomized trial in which screening, diagnosis, and management of ASD before and after implementation of the CHICA system in intervention practices will be compared to control practices. To measure the effect of the CHICA system on ASD screening and diagnosis (aim 2), we will collect data from medical records, reviews of CHICA data, and surveys of providers. Our primary outcome measure of interest for this aim is the percent of children who are screened using an ASD specific screening tool at the 18 or 24-month visit. To evaluate the effect of the CHICA system on ASD treatment and management (aim 3), we will collect process, outcome, and satisfaction measures at baseline, 6 months and 12 months from children between the ages of 18 months and 5 years with a formal diagnosis of ASD. The primary outcome of interest for aim 3 is the number of guideline recommended activities/involvements that a child diagnosed with ASD receives.

Public Health Relevance

The high prevalence of autism spectrum disorders (ASDs), coupled with its chronic and substantial impact on daily life functioning, makes it a major public health concern. Despite routine screening recommendations for ASD, research has demonstrated that a minority of physicians routinely screen for ASDs. Computer decision support systems, such as the Child Health Improvement through Computer Automation (CHICA) system we have developed, offer the best hope of equipping general practitioners to deal with the complex disorder of Autism.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
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Health Care Technology and Decision Science (HTDS)
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Mullican, Charlotte
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Indiana University-Purdue University at Indianapolis
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United States
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Anand, Vibha; Carroll, Aaron E; Biondich, Paul G et al. (2015) Pediatric decision support using adapted Arden Syntax. Artif Intell Med :
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Hendrix, Kristin S; Carroll, Aaron E; Downs, Stephen M (2014) Screen exposure and body mass index status in 2- to 11-year-old children. Clin Pediatr (Phila) 53:593-600
Anand, Vibha; Downs, Stephen M; Bauer, Nerissa S et al. (2014) Prevalence of infant television viewing and maternal depression symptoms. J Dev Behav Pediatr 35:216-24
Klann, Jeffrey G; Anand, Vibha; Downs, Stephen M (2013) Patient-tailored prioritization for a pediatric care decision support system through machine learning. J Am Med Inform Assoc 20:e267-74

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