ArticleJournal of attention disorders2019
Validation of the Use of Electronic Health Records for Classification of ADHD Status.
Article in Journal of attention disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A Systematic Review of Algorithms for Identifying Pediatric Neurodevelopmental Outcomes.Pharmacoepidemiology and drug safety · 2025Pooled it
- Neuropsychiatric events associated with montelukast in patients with asthma: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2023Pooled it
- Accuracy of administrative database algorithms for autism spectrum disorder, attention-deficit/hyperactivity disorder and fetal alcohol spectrum disorder case ascertainment: a systematic review.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2022Pooled it
- An electronic health record (EHR) phenotype algorithm to identify patients with attention deficit hyperactivity disorders (ADHD) and psychiatric comorbidities.Journal of neurodevelopmental disorders · 2022Trial
- Prenatal exposure to sedative-hypnotics and the risk of ADHD and ASD in offspring: a nationwide population-based cohort study.Archives of women's mental health · 2026Article
- Early attention deficit hyperactivity disorder prediction from longitudinal electronic health records.Nature. Mental health · 2026Article
- Evaluating Large Language Models for Transparent Quality-of-Care Measurement in Children with ADHD.medRxiv : the preprint server for health sciences · 2026Article
- Telehealth Prescribing of Stimulants for ADHD and Associated Risk for Later Stimulant and Substance Use Disorders.The American journal of psychiatry · 2025Article
- Early identification of children with Attention-Deficit/Hyperactivity Disorder (ADHD).PLOS digital health · 2024Article
- Prevalence and Incidence Trends of Attention Deficit/Hyperactivity Disorder in Children and Youth Aged 1-24 Years in Ontario, Canada: A Validation Study of Health Administrative Data Algorithms: Tendances de la prévalence et de l'incidence du trouble de déficit de l'attention/hyperactivité chez les enfants et les jeunes âgés de 1 à 24 ans, en Ontario, Canada: une étude de validation des algorithmes de données administratives de santé.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2024Article
- Measuring quality-of-care in treatment of young children with attention-deficit/hyperactivity disorder using pre-trained language models.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Article
- Risk factors associated with newly diagnosed attention-deficit/hyperactivity disorder in adults: a retrospective case-control study.BMC psychiatry · 2023Article
- Association Between Receipt of General Anesthesia During Childhood and Attention Deficit Hyperactive Disorder and Neurodevelopment.Journal of Korean medical science · 2023Article
- Article
- Article
- Association Between Exposure of Children to General Anesthesia and Autism Spectrum Disorder.Journal of autism and developmental disorders · 2022Article
- Real-World Crash Circumstances Among Newly Licensed Adolescent Drivers With and Without Attention-Deficit/Hyperactivity Disorder.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2022Article
- Validity of claims-based algorithms to identify neurodevelopmental disorders in children.Pharmacoepidemiology and drug safety · 2021Article
- A strategy for validation of variables derived from large-scale electronic health record data.Journal of biomedical informatics · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveTo validate an electronic health record (EHR)-based algorithm to classify ADHD status of pediatric patients.
methodAs part of an applied study, we identified all primary care patients of The Children's Hospital of Philadelphia [CHOP] health care network who were born 1987-1995 and residents of New Jersey. Patients were classified with ADHD if their EHR indicated an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis code of "314.x" at a clinical visit or on a list of known conditions. We manually reviewed EHRs for ADHD patients ( n = 2,030) and a random weighted sample of non-ADHD patients ( n = 807 of 13,579) to confirm the presence or absence of ADHD.
resultsDepending on assumptions for inconclusive cases, sensitivity ranged from 0.96 to 0.97 (95% confidence interval [CI] = [0.95, 0.97]), specificity from 0.98 to 0.99 [0.97, 0.99], and positive predictive value from 0.83 to 0.98 [0.81, 0.99].
conclusionEHR-based diagnostic codes can accurately classify ADHD status among pediatric patients and can be used by large-scale epidemiologic and clinical studies with high sensitivity and specificity.
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