Identifying Cases of Sleep Disorders through International Classification of Diseases (ICD) Codes in Administrative Data
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Résumé
OBJECTIVES: 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. 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. METHODS: A cohort of adult patients, with medical records reviewed by two independent board-certified sleep physicians from a sleep clinic in Calgary, Alberta between January 1, 2009 and December 31, 2011, was used as the reference standard. 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. 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). RESULTS: From 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. 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). 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%. 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 inpatient data yielded poor results in all tested ICD code combinations. CONCLUSION: 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. This may be a function of how sleep disorders are diagnosed and/or reported by physicians in inpatient and outpatient settings within medical records. Future work to optimize administrative data case definitions through data linkage are needed.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,003 |
| Science ouverte | 0,003 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle