Introduction Health disparities adversely affect people based on characteristics that are historically linked to discrimination or exclusion. There is limited research on understanding consequences of health disparities in the diagnosis and treatment of obstructive sleep apnea (OSA). This retrospective study sought to investigate health disparities affecting OSA patients using real-world data. Methods A national sample of administrative claims data from OSA patients who had a claim for a sleep test (home sleep test or polysomnography) was used. Gender, insurance payer, race/ethnicity, and 3-digit zip code were characterized from the claims data at the time of the first sleep test to describe differences across patients. Results The sample included about 2 million patients with 44.9% female, an average age 51.0 years, and an insurance payer breakdown of 74% commercial, 18% Medicaid, and 8% Medicare Advantage. There were a number of challenges that made it difficult to draw conclusions about the impact of health disparities in this data. The source of gender data was unknown; therefore, we do not know if it represents identified gender or biological sex. Race/ethnicity data was listed as “unknown” for 89% of commercial patients, 18% of Medicaid patients, and 36% of Medicare Advantage patients. Data reporting did not allow for details on multiple races or separation of race and ethnicity. Using 3-digit zip codes proved to be unreliable for drawing conclusions about a patient’s residence and access to care as 3-digit zip code areas are heterogenous and could cover a small section of a major city, a large rural portion of a state, or both. Lastly, ICD-10 Z codes, which describe social determinants of health (SDOH), appear to be underutilized. Conclusion Currently, using administrative claims as a real-world data source to assess health disparities is difficult due to data incompleteness, lack of adequate data definitions, and data aggregations made to protect patient privacy. Strategies to increase usability of claims data for investigating health disparities may include improvements in payer data reporting, increased utilization of SDOH Z codes, and linking to other more patient-centric data sources. Analyzing large samples of real-world data may help identify disparities and improve care for all patients. Support (if any)

Introduction Insomnia and anxiety are highly comorbid both with depression and with obstructive sleep apnea (OSA). This retrospective study sought to characterize patients with these conditions among a national sample of individuals with depression and comorbid OSA. Methods A national sample of administrative claims data of OSA patients was used for this analysis. Included patients either had two healthcare encounters or one hospitalization with a depression ICD-10 diagnosis code the year prior to OSA diagnosis and before initiation on positive airway pressure (PAP) therapy for treatment of OSA. Anxiety, insomnia, and other comorbidities were identified by the presence of at least one ICD-10 code associated with healthcare encounters in the year prior to starting PAP therapy. Age, sex, and insurance coverage were characterized at the time of the first OSA diagnostic sleep test. Healthcare resource utilization was assessed for the year prior to starting PAP therapy. Results 36,668 patients with depression and comorbid OSA were included. 56% had comorbid anxiety, 28% had comorbid insomnia, and 35% had neither anxiety nor insomnia. Compared to those without anxiety or insomnia, patients with anxiety or insomnia were more commonly female (64% vs 57%) and had a higher prevalence of asthma (25% vs 20%), psychotic (14% vs 7%) and other mood disorders (24% vs. 14%), fibromyalgia (11% vs 7%) and GERD (43% vs 33%). Relative to individuals with insomnia or anxiety, patients without insomnia or anxiety experienced fewer ER visits, all-cause hospitalizations, depression-related hospitalizations, specialist visits, and self-harm events in the year prior to PAP initiation. Relative to patients with comorbid insomnia, those with comorbid anxiety demonstrated slightly higher healthcare resource use in the year prior to PAP initiation. Conclusion Anxiety and insomnia are prevalent comorbidities in patients with depression and obstructive sleep apnea, with more than half of patients suffering comorbid anxiety and a quarter of patients having comorbid insomnia. Future research should examine comprehensive patient care strategies that can be used in patients with comorbid anxiety or insomnia to encourage healthy sleep behaviors and successful acclimation to OSA treatment. Support (if any) ResMed

Introduction Patients diagnosed with obstructive sleep apnea (OSA) and prescribed positive airway pressure (PAP) therapy for treatment may have differences in experience based on insurance provider, sex, age, or comorbidity status. This retrospective, real-world analysis investigated the factors that impact the patient’s OSA journey from initial sleep test to starting PAP therapy. Methods De-identified US administrative claims data for patients with OSA who had a claim for a sleep test were used for this analysis. Age, sex, and insurance coverage were characterized at the time of the first sleep test. Comorbidity status was evaluated in the year prior to the sleep test by assessing ICD-9/10 codes associated with healthcare encounters. This protocol was submitted to an Institutional Review Board and was determined to be exempt from oversight. Results In a population of 1,912,381 patients, 46.6% were female with mean age of 51.0 years. Insurance coverage was 70.6% commercial, 19.9% Medicaid, and 9.5% Medicare Advantage. Four comorbid cohorts were evaluated including those with hypertension (52.2%), type 2 diabetes (21.7%), COPD (9.7%), and atrial fibrillation (5.9%). Time from sleep test to receiving a PAP device was 7 days longer for females than males (median 49 days vs 42 days). Regardless of type of sleep test (polysomnography (PSG), home sleep test (HST)), those with commercial insurance received a device faster (median 41 days, Medicaid 61 days, Medicare Advantage 50 days). In comparison to those without the respective comorbidity, COPD was the only group with a noticeable increase in time from sleep test to device (median 54 days for those with COPD vs. 43 days for those without). No noticeable differences were observed across age categories. For those that had a titration, it occurred a median of 23 days after PSG or 34 days after HST. Consequently, the two fastest pathways were PSG with split night titration and HST without titration. Conclusion This retrospective study identified the length of time it takes in a real-world setting for patients to get a PAP device after a sleep test. Depending on demographic factors this time can vary from 1-2 months, delaying the start of OSA treatment. Support (If Any) ResMed

Introduction Real-world evidence focused on women with obstructive sleep apnea (OSA) is lacking. This retrospective study aimed to characterize and evaluate the impact of age on female patients with OSA and their journey through OSA diagnosis and treatment. Methods De-identified US administrative claims data for patients with OSA who had a claim for a sleep test were used for this analysis. Age and insurance coverage were characterized at the time of the first sleep test. Comorbidity status was evaluated in the year prior to the sleep test by assessing ICD-9/10 codes associated with healthcare encounters. This protocol was submitted to an Institutional Review Board and was determined to be exempt from oversight. Results The study included 883,902 female OSA patients; mean age of 51.7 years; and 64.9% commercial, 24.7% Medicaid, and 10.3% Medicare Advantage insurance coverage. The most prevalent comorbidities were hypertension (54.9%), hyperlipidemia (46.5%), GERD (31.5%), type 2 diabetes (25.1%), depression (23.2%), and asthma (22.0%). When stratifying by age, the prevalence of all comorbidities increased with age except for affective disorders. Depression and anxiety decreased with age. In terms of the type of sleep test used to diagnose OSA, 58.8% had an in-lab polysomnography (PSG), 38.9% had a home sleep test (HST), and 2.3% had both a PSG and HST. About half (56.6%) of patients received a positive airway pressure (PAP) device in the year after being diagnosed. When stratifying the results by age, in-lab PSG testing was more prevalent in those over 65, while the percentage of those receiving a PAP device increased then slightly decreased with age (18-44y: 47.6%, 45-54y: 58.1%, 55-64y: 62.1%, 65-69y: 61.1%, >70y: 58.8%). Conclusion This retrospective study characterized the start of the women’s journey with OSA; describing the rates of sleep testing and PAP treatment from a sample of real-world data. These results begin to build an understanding of these patients and their journey to treatment, helping to raise awareness of undiagnosed OSA in women. Further research should be conducted to identify potential real-world impact of adherence to PAP on health outcomes. Support (If Any) ResMed

Introduction Previous studies have shown that treatment of obstructive sleep apnea (OSA) with positive airway pressure (PAP) therapy in patients with OSA and comorbid depression may improve response to antidepressant medication therapy. At the same time, scant evidence has examined the impact of medication and PAP adherence in patients with OSA and comorbid depression. Patients that adhere to one therapy may be more likely to adhere to other therapies or healthy behaviors in a so-called “healthy user effect.” This retrospective study investigated the association between antidepressant medication adherence and PAP therapy adherence in patients with newly diagnosed OSA and comorbid depression. Methods Our data source was a national sample of administrative claims data linked to objective PAP therapy usage. Included patients either had two healthcare encounters or one hospitalization with a depression ICD-10 diagnosis code the year prior to being diagnosed with OSA and initiated on PAP therapy. Adherence to antidepressant medication was defined as ≥80% of proportion of days covered (PDC), and non-adherence was defined as < 80% PDC within a 180-day exposure window during the year prior to starting PAP therapy. Adherence to PAP therapy was categorized as consistently adherent, intermediately adherent, or not adherent based on objective usage over 2 years. Results 36,668 patients with OSA and comorbid depression were included. 27% were classified as consistently adherent, 45% intermediately adherent, and 28% non-adherent to PAP therapy. 68.6% of patients used antidepressant medication in the year prior to PAP initiation. 67.7% used a selective serotonin reuptake inhibitor, 43.8% atypical antidepressants, 32.1% serotonin and norepinephrine reuptake inhibitor, 10.7% tricyclic antidepressant, and 0.1% monoamine oxidase inhibitor. Relative to patients not adherent to antidepressant medication (22.2% consistently adherent, 43.8% intermediately adherent, 33.9% not adherent), those adherent to antidepressant medication in the year prior were also more adherent to PAP therapy over 2 years (29.2% consistently adherent, 45.2% intermediately adherent, 25.6% not adherent). Conclusion Patients that were adherent to antidepressant medication in the year prior to starting PAP therapy have slightly better adherence to PAP therapy over 2 years. In real-world studies, medication adherence may be an important confounder to adjust for when comparing patient outcomes. Support (if any)