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01-07-2015 | Original Paper

Validation of Autism Spectrum Disorder Diagnoses in Large Healthcare Systems with Electronic Medical Records

Auteurs: Karen J. Coleman, Marta A. Lutsky, Vincent Yau, Yinge Qian, Magdalena E. Pomichowski, Phillip M. Crawford, Frances L. Lynch, Jeanne M. Madden, Ashli Owen-Smith, John A. Pearson, Kathryn A. Pearson, Donna Rusinak, Virginia P. Quinn, Lisa A. Croen

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 7/2015

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Abstract

To identify factors associated with valid Autism Spectrum Disorder (ASD) diagnoses from electronic sources in large healthcare systems. We examined 1,272 charts from ASD diagnosed youth <18 years old. Expert reviewers classified diagnoses as confirmed, probable, possible, ruled out, or not enough information. A total of 845 were classified with 81 % as a confirmed, probable, or possible ASD diagnosis. The predictors of valid ASD diagnoses were >2 diagnoses in the medical record (OR 2.94; 95 % CI 2.03–4.25; p < 0.001) and being male (OR 1.51; 95 % CI 1.05–2.17; p = 0.03). In large integrated healthcare settings, at least two diagnoses can be used to identify ASD patients for population-based research.
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Metagegevens
Titel
Validation of Autism Spectrum Disorder Diagnoses in Large Healthcare Systems with Electronic Medical Records
Auteurs
Karen J. Coleman
Marta A. Lutsky
Vincent Yau
Yinge Qian
Magdalena E. Pomichowski
Phillip M. Crawford
Frances L. Lynch
Jeanne M. Madden
Ashli Owen-Smith
John A. Pearson
Kathryn A. Pearson
Donna Rusinak
Virginia P. Quinn
Lisa A. Croen
Publicatiedatum
01-07-2015
Uitgeverij
Springer US
Gepubliceerd in
Journal of Autism and Developmental Disorders / Uitgave 7/2015
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI
https://doi.org/10.1007/s10803-015-2358-0