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 |
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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. |
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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.</description><identifier>ISSN: 1087-0547</identifier><identifier>EISSN: 1557-1246</identifier><identifier>DOI: 10.1177/1087054716672337</identifier><identifier>PMID: 28112025</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><ispartof>Journal of attention disorders, 2019-11, Vol.23 (13), p.1647-1655</ispartof><rights>The Author(s) 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c434t-dbec072e5632d7ec687552ce411a06c2e5ace4b18ba83f63e0e721f5808be05b3</citedby><cites>FETCH-LOGICAL-c434t-dbec072e5632d7ec687552ce411a06c2e5ace4b18ba83f63e0e721f5808be05b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/1087054716672337$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/1087054716672337$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>230,314,777,781,882,21800,27905,27906,43602,43603</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28112025$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gruschow, Siobhan M.</creatorcontrib><creatorcontrib>Yerys, Benjamin E.</creatorcontrib><creatorcontrib>Power, Thomas J.</creatorcontrib><creatorcontrib>Durbin, Dennis R.</creatorcontrib><creatorcontrib>Curry, Allison E.</creatorcontrib><title>Validation of the Use of Electronic Health Records for Classification of ADHD Status</title><title>Journal of attention disorders</title><addtitle>J Atten Disord</addtitle><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]. 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title | Validation of the Use of Electronic Health Records for Classification of ADHD Status |
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