The primary purpose of the proposed study is to validate our previously developed predictive model for adults with obstructive sleep apnea using (i) clinical data from multiple large academic centers, (ii) a longer follow-up period, and (iii) an extended definition of outcomes of interest. The TOH sleep database was created as a part of the project: "Validation of provincial health administrative data algorithms to identify patients with obstructive sleep apnea (OSA): Feasibility project". Protocol ID: 20170591-01H (AMENDMENT APPROVED on December 19, 2018) to be used for future clinical, research, educational and quality improvement purposes.
The primary purpose of the proposed study is to validate the previously developed predictive model by the investigators for adults with obstructive sleep apnea using (i) clinical data from multiple large academic centers, (ii) a longer follow-up period, and (iii) an extended definition of outcomes of interest. From clinical and quality improvement perspective the TOH database will be used for description, evaluation, monitoring and/or educational purposes. For example, using this database the investigators will be able (i) to describe characteristics of individuals who underwent a diagnostic sleep study at the TOH between 2015 and 2017 to understand better clinical and health care utilization needs as well as to educate sleep fellows and technologists; and (ii) to evaluate the quality of the triaging process in the sleep clinic. This database will be used to: (i) examine risk factors for long-term adverse health consequences (e.g. cardio-vascular diseases, diabetes, depression, dementia, depression and cancer) among individuals referred for diagnostic sleep testing in order to identify high risk groups that are potential targets for education and treatment, (ii) develop health interventions in order to improve the quality of care and management strategies available for adults with chronic diseases that are comorbid with obstructive airway diseases and sleep-related disorders, (iii) evaluate the cost-effectiveness of the developed health interventions, e.g. screening for obstructive sleep apnea (OSA), evaluation of home versus laboratory-based diagnosis of OSA, and education strategies, (iv) develop key messages for different stakeholder groups (health care providers, patients and their relatives, provincial sleep and lung associations, public health managers, the respiratory vendor among others) related to diagnosis, education and treatment of patients with respiratory and sleep-related problems.
Study Type
OBSERVATIONAL
Enrollment
5,155
Different sleep disorders will be considered as an exposure. The data elements included in the database: demographics, date of the sleep study, study type, all available polysomnography indices, symptoms, sleep schedule, comorbidities, medications, social history, electrocardiography, positive airway pressure treatment related variables.
The Ottawa Hospital
Ottawa, Ontario, Canada
Long-term adverse health consequences
The primary outcome will be time from the index date (diagnostic sleep study) to the composite outcome of interest which include: cardio-vascular diseases, diabetes, depression, dementia, and cancer as well as chronic lung diseases and all-cause mortality. Conditions of interested will be defined from provincial health administrative data using validated algorithms that have utilized ICD-9 and ICD-10 codes as well as billing codes for outpatients visits, and procedural codes. Please see ICES Data Dictionary for details: https://www.ices.on.ca/Data-and-Privacy/ICES-data/Data-dictionary.
Time frame: Through study completion, up to 10 years
Health care utilization
All-cause mortality, all-cause hospitalizations, emergency department visits and associated costs will be defined from provincial health administrative data. Registered Persons Database will be used to define mortality. Hospitalizations and emergency department visits will be defined using: Discharge Abstract Database (all hospital admission and discharge data), National Ambulatory Care Reporting System (emergency department visits). Please see ICES Data Dictionary for details: https://www.ices.on.ca/Data-and-Privacy/ICES-data/Data-dictionary. Total healthcare expenditures will be calculated using the ICES person-level health utilization costing algorithms.
Time frame: Through study completion, up to 10 years
Motor vehicle crashes
Different definitions of motor vehicle crashes will be considered. Motor vehicle crashes requiring hospital or emergency department visit: the investigators will identify traffic emergencies characterized as a crash using the International Classification of Diseases codes 10th Revision (V20-V69). The investigators will include emergency department visits involving crashes in which the patient was the driver of the motor vehicle and exclude emergency department visits involving crashes in which the patient was a passenger or pedestrian.
Time frame: Through study completion, up to 10 years
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