Accuracy of Electronic Health Record–Derived Data for the Identification of Incident ADHD

  • Matthew F. Daley
  • , Douglas A. Newton
  • , Lynn DeBar
  • , Sophia R. Newcomer
  • , Lisa Pieper
  • , Joseph A. Boscarino
  • , Sengwee Toh
  • , Pamala Pawloski
  • , James D. Nordin
  • , Cynthia Nakasato
  • , Lisa J. Herrinton
  • , Regina Bussing

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Objective: To assess the accuracy of electronic health record (EHR)–derived diagnoses in identifying children with incident (i.e., newly diagnosed) ADHD. Method: In 10 large health care organizations, electronic diagnoses data were used to identify all potential cases of incident ADHD among 3- through 9-year-old children. A random sample of records was manually reviewed to determine whether a diagnosis of ADHD was documented in clinician notes. Results: From electronic diagnoses data, a total of 7,362 children with incident ADHD were identified. Upon manual review of 500 records, the diagnosis of incident ADHD was confirmed in clinician notes for 71.5% (95% confidence interval [CI] = [56.5, 86.4]) of records for 3- through 5-year-old children and 73.6% (95% CI = [65.6, 81.6]) of records for 6- through 9-year-old children. Conclusion: Studies predicated on the identification of incident ADHD cases will need to carefully consider study designs that minimize the likelihood of case misclassification.

Original languageEnglish
Pages (from-to)416-425
Number of pages10
JournalJournal of Attention Disorders
Volume21
Issue number5
DOIs
StatePublished - Mar 1 2017

Keywords

  • ADHD
  • accuracy
  • child
  • electronic health records

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