ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2020
Multisite validation of a simple electronic health record algorithm for identifying diagnosed obstructive sleep apnea.
Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Concordance Between Self-Report and Electronic Medical Record Diagnoses of Insomnia and Sleep Apnea: Lessons From the Airborne Hazards and Open Burn Pit Registry.Medical care · 2026Article
- Associations of Chronic Insomnia, Longitudinal Cognitive Outcomes, Amyloid-PET, and White Matter Changes in Cognitively Normal Older Adults.Neurology · 2025Article
- Bariatric Surgery and Incident Development of Obesity-Related Comorbidities.JAMA network open · 2025Article
- Comorbidities that modulate temporal risk for incident hypertension among patients with obstructive sleep apnea.Clinical hypertension · 2025Article
- Racial and ethnic differences in the receipt of continuous positive airway pressure treatment for obstructive sleep apnea.Sleep medicine · 2024Article
- Positive Airway Pressure, Mortality, and Cardiovascular Risk in Older Adults With Sleep Apnea.JAMA network open · 2024Article
- Prevalence of obstructive sleep apnea with hidradenitis suppurativa: a matched case-control study.Archives of dermatological research · 2024Article
- Identifying clusters of patient comorbidities associated with obstructive sleep apnea using electronic health records.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024Article
- Infants hospitalized with lower respiratory tract infections during the first two years of life have increased risk of pediatric obstructive sleep apnea.Pediatric pulmonology · 2024Article
- Long-term clinical outcomes of bariatric surgery in adults with severe obesity: A population-based retrospective cohort study.PloS one · 2024Article
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- Effectiveness and Safety of Rivaroxaban Versus Warfarin among Nonvalvular Atrial Fibrillation Patients with Concomitant Obstructive Sleep Apnea.TH open : companion journal to thrombosis and haemostasis · 2023Article
- Sleep and affective disorders in relation to Parkinson's disease risk among older women from the Women's Health Initiative.Journal of affective disorders · 2022Observational
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- Article
- Characterizing sleep disorders in an autism-specific collection of electronic health records.Sleep medicine · 2022Article
- Use and limitations of databases and big data in sleep-disordered breathing research.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022Article
- Sleepiness in Cognitively Unimpaired Older Adults Is Associated With CSF Biomarkers of Inflammation and Axonal Integrity.Frontiers in aging neuroscience · 2022Article
- Article
- Towards Validating the Effectiveness of Obstructive Sleep Apnea Classification from Electronic Health Records Using Machine Learning.Healthcare (Basel, Switzerland) · 2021Article
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Funding
Abstract
STUDY
objectivesWe 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.
methodsRetrospective 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.
resultsThe 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.
conclusionsA 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.
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