![]() ![]() Specifically, OSA has been associated with hypertension, heart failure, ischemic heart disease, arrhythmias, metabolic syndrome, pulmonary hypertension, stroke, and depression (5). People with daytime sleepiness have a tendency to fall asleep in inappropriate places at inappropriate times, and have poor concentration which impacts daily functioning, work productivity and can even cause motor-vehicle accidents (4). Sleep disorders can both be affected by disease and impact disease, with sleep deprivation and associated disorders having been shown to have large impacts on health (3). Despite the prevalence of sleep disorders, methodologies used for identifying such patients from administrative data are limited. The International Classification of Sleep Disorders 3rd Edition (ICSD-3)(2) has identified over 80 different types of sleep disorders, the most common of which include obstructive sleep apnea (OSA), insomnia and narcolepsy. It has been reported that 35 to 40% of the US adult population annually are affected by problems falling asleep or daytime sleepiness (1). ![]() Sleep disorders are common however, prevalence estimates of different sleep disorders vary. Future work to optimize administrative data case definitions through data linkage are needed. This may be a function of how sleep disorders are diagnosed and/or reported by physicians in inpatient and outpatient settings within medical records. Sleep disorders in administrative data can be identified mainly through physician claims data and with some being determined through outpatient/ambulatory care data ICD codes, however these are poorly coded within inpatient data sources. The inpatient data yielded poor results in all tested ICD code combinations. ICD codes from ED/ambulatory care data provided similar diagnostic performance when at least 2 codes appeared in a time period of 2 years prior and 1 year post sleep clinic visit: sensitivity 71.9%, specificity 54.6%, PPV 92.1%, and NPV 20.8%. The best definition for identifying a sleep disorder was an ICD code (from physician claims) 2 years prior and 1 year post sleep clinic visit: sensitivity 79.2%, specificity 28.4%, PPV 89.1%, and NPV 15.6%. The most frequently used ICD-9 codes were general codes of 307.4 (Nonorganic sleep disorder, unspecified), 780.5 (unspecified sleep disturbance) and ICD-10 codes of G47.8 (other sleep disorders), G47.9 (sleep disorder, unspecified). We linked the reference standard data and administrative data to examine the validity of different case definitions, calculating estimates of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).įrom a total of 1186 patients from the sleep clinic, 1045 (88.1%) were classified as sleep disorder positive, with 606 (51.1%) diagnosed with OSA, 407 (34.4%) with insomnia, and 59 (5.0%) with narcolepsy. We developed a general ICD-coded case definition for sleep disorders which included conditions of narcolepsy, insomnia, and OSA using: 1) physician claims data, 2) inpatient visit data, 3) emergency department (ED) and ambulatory care data. ![]() With no guidelines to inform the identification of cases of sleep disorders in administrative data, the objective of this study was to develop and validate a set of ICD-codes used to define sleep disorders including narcolepsy, insomnia, and obstructive sleep apnea (OSA) in administrative data.Ī cohort of adult patients, with medical records reviewed by two independent board-certified sleep physicians from a sleep clinic in Calgary, Alberta between Januand December 31, 2011, was used as the reference standard. Prevalence, and associated morbidity and mortality of chronic sleep disorders have been limited to small cohort studies, however, administrative data may be used to provide representation of larger population estimates of disease.
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