Multisite validation of a simple electronic health record algorithm for identifying diagnosed obstructive sleep apnea.

Algorithms Electronic Health Records Humans International Classification of Diseases Retrospective Studies Sleep Apnea, Obstructive / diagnosis
case-identification algorithm diagnostic codes electronic health record obstructive sleep apnea phenotype

Journal

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
ISSN: 1550-9397
Titre abrégé: J Clin Sleep Med
Pays: United States
ID NLM: 101231977

Informations de publication

Date de publication:
15 02 2020
Historique:
pubmed: 30 1 2020
medline: 24 6 2021
entrez: 30 1 2020
Statut: ppublish

Résumé

We examined the performance of a simple algorithm to accurately distinguish cases of diagnosed obstructive sleep apnea (OSA) and noncases using the electronic health record (EHR) across six health systems in the United States. Retrospective analysis of EHR data was performed. The algorithm defined cases as individuals with ≥ 2 instances of specific International Classification of Diseases (ICD)-9 and/or ICD-10 diagnostic codes (327.20, 327.23, 327.29, 780.51, 780.53, 780.57, G4730, G4733 and G4739) related to sleep apnea on separate dates in their EHR. Noncases were defined by the absence of these codes. Using chart reviews on 120 cases and 100 noncases at each site (n = 1,320 total), positive predictive value (PPV) and negative predictive value (NPV) were calculated. The algorithm showed excellent performance across sites, with a PPV (95% confidence interval) of 97.1 (95.6, 98.2) and NPV of 95.5 (93.5, 97.0). Similar performance was seen at each site, with all NPV and PPV estimates ≥ 90% apart from a somewhat lower PPV of 87.5 (80.2, 92.8) at one site. A modified algorithm of ≥ 3 instances improved PPV to 94.9 (88.5, 98.3) at this site, but excluded an additional 18.3% of cases. Thus, performance may be further improved by requiring additional codes, but this reduces the number of determinate cases. A simple EHR-based case-identification algorithm for diagnosed OSA showed excellent predictive characteristics in a multisite sample from the United States. Future analyses should be performed to understand the effect of undiagnosed disease in EHR-defined noncases. This algorithm has wide-ranging applications for EHR-based OSA research.

Identifiants

DOI: 10.5664/jcsm.8160 PMID: 31992429 PMC: PMC7053021
pubmed: 31992429
doi: 10.5664/jcsm.8160
pmc: PMC7053021
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

175-183

Subventions

Organisme : NHLBI NIH HHS
ID : P01 HL094307
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL134015
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2020 American Academy of Sleep Medicine.

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Auteurs

Brendan T Keenan (BT)

Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Co-lead authors.

H Lester Kirchner (HL)

Biomedical and Translational Informatics, Geisinger, Danville, Pennsylvania.
Co-lead authors.

Olivia J Veatch (OJ)

Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Sleep Disorders Division, Vanderbilt University Medical Center, Nashville, Tennessee.

Kenneth M Borthwick (KM)

Biomedical and Translational Informatics, Geisinger, Danville, Pennsylvania.

Vicki A Davenport (VA)

Biomedical and Translational Informatics, Geisinger, Danville, Pennsylvania.

John C Feemster (JC)

Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota.

Maged Gendy (M)

Center for Circadian and Sleep Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.

Thomas R Gossard (TR)

Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota.

Frances M Pack (FM)

Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.

Laura Sirikulvadhana (L)

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California.

Luke N Teigen (LN)

Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota.

Paul C Timm (PC)

Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota.

Beth A Malow (BA)

Sleep Disorders Division, Vanderbilt University Medical Center, Nashville, Tennessee.

Timothy I Morgenthaler (TI)

Center for Sleep Medicine, Mayo Clinic, Rochester, Minnesota.

Phyllis C Zee (PC)

Center for Circadian and Sleep Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois.

Allan I Pack (AI)

Division of Sleep Medicine/Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.

Janet D Robishaw (JD)

Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida.
Joint senior authors.

Stephen F Derose (SF)

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California.
Joint senior authors.

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Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Multisite validation of a simple electronic...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Collecte de données › Documents › Dossiers médicaux › Systèmes informatisés de dossiers médicaux › Dossiers médicaux électroniques › Multisite validation of a simple electronic...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Multisite validation of a simple electronic...
questionsmedicales.fr › Sciences de l'information › Sources d'information › Services d'information › Documentation › Vocabulaire contrôlé › Classification internationale des maladies › Multisite validation of a simple electronic...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études rétrospectives › Multisite validation of a simple electronic...
questionsmedicales.fr › Maladies du système nerveux › Syndromes d'apnées du sommeil › Syndrome d'apnées obstructives du sommeil › Multisite validation of a simple electronic...