Validation of the Use of Electronic Health Records for Classification of ADHD Status

Objective: To validate an electronic health record (EHR)–based algorithm to classify ADHD status of pediatric patients. Method: As 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 resid...

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Veröffentlicht in:Journal of attention disorders 2019-11, Vol.23 (13), p.1647-1655
Hauptverfasser: Gruschow, Siobhan M., Yerys, Benjamin E., Power, Thomas J., Durbin, Dennis R., Curry, Allison E.
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container_end_page 1655
container_issue 13
container_start_page 1647
container_title Journal of attention disorders
container_volume 23
creator Gruschow, Siobhan M.
Yerys, Benjamin E.
Power, Thomas J.
Durbin, Dennis R.
Curry, Allison E.
description Objective: To validate an electronic health record (EHR)–based algorithm to classify ADHD status of pediatric patients. Method: As 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. Results: Depending 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]. Conclusion: EHR-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.
doi_str_mv 10.1177/1087054716672337
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