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

15 Scopus citations


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
Issue number5
StatePublished - Mar 1 2017


  • ADHD
  • accuracy
  • child
  • electronic health records


Dive into the research topics of 'Accuracy of Electronic Health Record–Derived Data for the Identification of Incident ADHD'. Together they form a unique fingerprint.

Cite this