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Cited by 79Autism Spectrum Disorder ResearchMedical Coding and Health InformationHealth and Medical Studies

Validity of autism diagnoses using administrative health data

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Dodds, L., Spencer, A., Shea, S., Fell, D., Armson, B.A., Allen, A.C., Bryson, S.·2009·Chronic Diseases in Canada
DOI 10.24095/hpcdp.29.3.02PMC PMC3212104
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Abstract

It is necessary to monitor autism prevalence in order to plan education support and health services for affected children. This study was conducted to assess the accuracy of administrative health databases for autism diagnoses. Three administrative health databases from the province of Nova Scotia were used to identify diagnoses of autism spectrum disorders (ASD): the Hospital Discharge Abstract Database, the Medical Services Insurance Physician Billings Database and the Mental Health Outpatient Information System database. Seven algorithms were derived from combinations of requirements for single or multiple ASD claims from one or more of the three administrative databases. Diagnoses made by the Autism Team of the IWK Health Centre, using state-of-the-art autism diagnostic schedules, were compared with each algorithm, and the sensitivity, specificity and C-statistic (i.e. a measure of the discrimination ability of the model) were calculated. The algorithm with the best test characteristics was based on one ASD code in any of the three databases (sensitivity=69.3%). Sensitivity based on an ASD code in either the hospital or the physician billing databases was 62.5%. Administrative health databases are potentially a cost efficient source for conducting autism surveillance, especially when compared to methods involving the collection of new data. However, additional data sources are needed to improve the sensitivity and accuracy of identifying autism in Canada.

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  • Administrative databases are usually associated with lower sensitivity for case finding, especially in areas with limited availability and/or access to services.

    “but they are usually associated with lower sensitivity for case finding (Dodds et al., 2009), especially in areas with limited availability and/or access to service.”

    From Global prevalence of autism: A systematic review update (2022) · cites this paper as Dodds et al., 2009

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Authors
Dodds, L., Spencer, A., Shea, S., Fell, D., Armson, B. A., Allen, A. C., & Bryson, S.
Affiliations
Dalhousie University (CA)
ORCID
Venue
Chronic Diseases in Canada
Publisher
Health Promotion and Chronic Disease Prevention Branch (HPCDP) Public Health Agency of Canada
Published
2009-05
Volume
29
Issue
3
Pages
102-107
ISSN
  • 0228-8699 (ISSN-L)
  • 1481-8523
DOI
10.24095/hpcdp.29.3.02
PMC
PMC3212104
OpenAlex
W1911918103
Cited by
79
References
2
Citations by year
2026: 2 · 2025: 6 · 2024: 4 · 2023: 6 · 2022: 5 · 2021: 4 · 2020: 5 · 2019: 8 · 2018: 6 · 2017: 5 · 2016: 4 · 2015: 2 · 2014: 2 · 2013: 1 · 2012: 8
FWCI
3.08
Type
journal article
Language
en
Open access
Locations
  • Chronic diseases in Canada (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Autism Speaks (ASCN4975)
  • Dalhousie University
  • Canadian Institutes of Health Research
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
  • Health Sciences › Health Professions › General Health Professions › Health and Medical Studies
Keywords
autism spectrum disorder, autism diagnosis, administrative health data, diagnostic accuracy, hospital discharge abstracts, physician billing data, surveillance algorithms, sensitivity and specificity, Nova Scotia
MeSH terms
Algorithms, Ambulatory Care, Autistic Disorder, Child, Cost-Benefit Analysis, Female, Humans, Insurance Claim Reporting, Male, Nova Scotia, Patient Credit and Collection, Patient Discharge, Population Surveillance, Sensitivity and Specificity, Incidence, Prevalence, Discriminant Analysis, Databases, Factual, International Classification of Diseases

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