Obstructive sleep apnoea (OSA) causes difficulty breathing whilst asleep and make people tired and feeling sleepy during the day. To help them breathe whilst asleep, people with moderate-to-severe OSA wear a device on their mouth which applies positive airway pressure (PAP) and facilitates breathing. Information is needed on the patients who receive PAP devices as treatment for their OSA, and how this impacts their access to healthcare (e.g.: hospital appointments). In this study, we aim to research people with OSA who are or are not treated with PAP devices. The number of people with OSA will be estimated and they will be described in several ways using information stored in their electronic healthcare records: 1) demographics, smoking status, concurrent diseases, and diagnostic tests and the treatments that they received, 2) health care resource use (HCRU) in primary and secondary care and cause of death. The study will also investigate whether 1) the HCRU and the associated cost and mortality differ between OSA patients who treated with PAP devices and those who did not receive PAP devices as treatment, 2) the HCRU and the associated cost differ prior to and after PAP treatment. The rationale for the study is that it will provide knowledge on the burden of this disease that could be used to improve patient care and to better manage the care pathway of these patients within the National Health Service.
Obstructive sleep apnoea (OSA) is a chronic condition characterized by repetitive episodes of upper airway collapse during sleep. Positive airway pressure (PAP) as continuous PAP (CPAP), autotitrating PAP (APAP) or bi-level PAP are standard of care for moderate-to-severe OSA. The aim of the study is to better understand OSA patients treated with PAP.
The incidence of patients with OSA will be estimated in a study population of adults from the Clinical Practice Research Datalink (CPRD) linked to Hospital Episode Statistics (HES). A primary objective is to describe the study population in terms of baseline demographics, prior comorbidities, diagnostic test, and treatments pathways. A secondary objective is to further focus on a subset of OSA patients who treated with CPAP/APAP, in terms of healthcare resource use (HCRU) in primary and secondary care and to compare these 1) OSA patients with and without a CPAP/APAP treatment and 2) prior to and post CPAP/APAP initiation in OSA patients with CPAP/APAP treatment. Mortality, cause of death, and survival time in follow-up period will also be compared in OSA patients with and without a CPAP/APAP treatment. Moreover, waiting time for a sleep clinic visit, time from sleep clinic visit to OSA diagnosis, and time from OSA diagnosis to initiation of a CPAP/APAP treatment will be described.
Frequencies and percentages for categorical variables and means, standard deviations, medians, interquartile ranges, and min and max for continuous variables will be reported. HCRU will be described as number of visits or admissions per patient-year. To compare the groups, Chi-square tests for categorical variables, Student’s t-tests or Wilcoxon rank sum tests will be used. The association between CPAP/APAP treatment and the HCRU and the associated costs post-PAP treatment will be tested using generalized linear regression adjusting for confounding factors.
Incidence of OSA; age at OSA diagnosis in years and patient number by decade (age bands); gender; Index of multiple deprivation (IMD); smoking status; weight; body mass index (BMI); Charlson Comorbidity Index (CCI); comorbidities (top 10 recorded diagnoses); OSA-related comorbidities (hypertension, ischaemic heart disease, atrial fibrillation or other arrhythmias, cerebrovascular accident/stroke, depression, anxiety, gastric ulceration, gastroesophageal reflux, chronic liver disease, asthma, COPD, diabetes mellitus, dyslipidemia, gout, obesity, chronic kidney disease and dialysis, pancreatic cancer, lung cancer, colorectal cancer, melanoma); pulse oximetry diagnosis; home sleep study (Limited Sleep Study); full polysomnography; Epworth Sleepiness Scale (ESS) score; Berlin questionnaire; CPAP; APAP; frequency of sleep clinic visits after PAP initiation; primary care (practitioner (GP)/ other allied healthcare professional visits and telephone consultations) and associated & costs; GP prescribing costs; outpatient hospital visits and associated cost; top 5 common visited outpatient departments; inpatient hospitalisation (and length of stay) and associated cost; top 5 common primary diagnosis of inpatient admissions; accident and emergency (A&E) visits and associated cost; all-cause mortality; cause of death; survival time; waiting time for a sleep clinic visit; time from sleep clinic visit to diagnosis of OSA; time from OSA diagnosis to initiation of PAP treatment. For more detail on data source and time points, please see Appendix 1.
Craig Currie - Chief Investigator - Pharmatelligence Limited t/a Human Data Sciences
Ellen Hubbuck - Corresponding Applicant - Pharmatelligence Limited t/a Human Data Sciences
Asad Ali - Collaborator - University Hospitals Coventry & Warwickshire NHS Trust
Bethan Jones - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Daniela Ehrsam-Tosi - Collaborator - ResMed Schweiz GmbH
Fatemeh Saberi Hosnijeh - Collaborator - Harvey Walsh Ltd
Gus Sagoo - Collaborator - ResMed (UK) Limited
Kimberly Sterling - Collaborator - ResMed Inc.
Melike Deger Wehr - Collaborator - ResMed Germany Inc
Naomi Alpert - Collaborator - ResMed Inc.
Nick Denholm - Collaborator - Harvey Walsh Ltd
Stephen Boult - Collaborator - Harvey Walsh Ltd
Will McConnell - Collaborator - ResMed Inc.
Gillian Hall - Collaborator - Gillian Hall Epidemiology Ltd
Mark McCormack - Collaborator - Harvey Walsh Ltd
Myriam Alexander - Collaborator - Harvey Walsh Ltd
Sue Beecroft - Collaborator - Harvey Walsh Ltd
Xiaocong Marston - Collaborator - Harvey Walsh Ltd
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation