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Identifying Obstructive Sleep Apnea in Administrative Data: A Study of Diagnostic Accuracy.
Anesthesiology
August 2015
From the Department of Anesthesiology, University of Ottawa, Department of Anesthesiology, The Ottawa Hospital, and Institute for Clinical Evaluative Sciences at uOttawa, Ottawa, Ontario, Canada (D.I.M.); Sunnybrook Health Sciences Centre, Institute for Clinical Evaluative Sciences, and University of Toronto, Toronto, Ontario, Canada (A.G.); Li Ka Shing Knowledge Institute of St. Michael's Hospital, Department of Anesthesia and Pain Management, Toronto General Hospital, Department of Anesthesia and Institute of Health Policy Management and Evaluation, University of Toronto, and Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada (D.W.); Department of Anesthesiology, University of Ottawa, and Department of Anesthesiology, The Ottawa Hospital, Ottawa, Ontario, Canada (G.L.B.); Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, and Kelowna General Hospital, Kelowna, British Columbia, Canada (N.B.); and Department of Medicine, University of Ottawa, and Institute for Clinical Evaluative Sciences at uOttawa, Ottawa, Ontario, Canada (C.v.W.).
Background: Health administrative (HA) databases are increasingly used to identify surgical patients with obstructive sleep apnea (OSA) for research purposes, primarily using diagnostic codes. Such means to identify patients with OSA are not validated. The authors determined the accuracy of case-ascertainment algorithms for identifying patients with OSA with the use of HA data.
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