Abstract
Study Objectives:
To determine whether adherence to continuous positive airway pressure (CPAP) in adults with uncomplicated obstructive sleep apnea differs by rural vs urban residential address.
Methods:
In this prospective cohort study, we recruited adults who initiated CPAP for uncomplicated obstructive sleep apnea that was diagnosed by a physician using sleep specialist-interpreted diagnostic testing. Participants were classified as urban (community size > 100,000) or rural (community size < 100,000) by translating residential postal code into geographic census area. The primary outcome was mean daily hours of CPAP use compared between rural and urban patients. Secondary outcomes included the proportion of patients who were adherent to CPAP, change in Epworth Sleepiness Scale score, change in EuroQOL-5D visual analog score, and Visit-Specific Satisfaction Instrument score. All outcomes were measured 3 months after CPAP initiation.
Results:
We enrolled 242 patients (100 rural) with a mean (standard deviation) age of 51 (13) years and a respiratory event index of 24 (18) events/h. The mean (95% confidence interval) CPAP use was 3.19 (2.8–3.58) hours/night and 35% were CPAP-adherent, with no difference between urban and rural patients. Among the 65% of patients who were using CPAP at 3 months, the mean CPAP use was 4.89 (4.51–5.28) hours/night and was not different between rural and urban patients. Improvement in the Epworth Sleepiness Scale score and patient satisfaction was similar between groups, but the EuroQOL-5D score improved to a greater extent in rural patients. Urban or rural residence was not associated with CPAP adherence according to multivariable regression analysis.
Conclusions:
Rural vs urban residence was not associated with differences in CPAP adherence among patients with uncomplicated OSA diagnosed by a physician using specialist-interpreted sleep diagnostic testing.
Citation:
Corrigan J, Tsai WH, Ip-Buting A, et al. Treatment outcomes among rural and urban patients with obstructive sleep apnea: a prospective cohort study. J Clin Sleep Med. 2022;18(4):1013–1020.
Keywords: continuous positive airway pressure, geographic factors, obstructive sleep apnea, rural health, treatment outcome
BRIEF SUMMARY
Current Knowledge/Study Rationale: Geography contributes to inequities in health care outcomes. However, no study has explored the impact of rural residence on treatment outcomes in patients with uncomplicated obstructive sleep apnea.
Study Impact: Rural compared with urban residence was not associated with differences in continuous positive airway pressure adherence among patients with uncomplicated obstructive sleep apnea diagnosed by a physician using specialist-interpreted sleep diagnostic testing.
INTRODUCTION
Obstructive sleep apnea (OSA) is a highly prevalent chronic disease affecting almost 1 billion people globally.1 Individuals with untreated OSA have a poorer quality of life and increased cardiometabolic and neurocognitive risk, and they make greater and more costly use of the health care system compared to the general population.2 Societal impacts include an increased risk of motor vehicle collisions, workplace accidents, and lost productivity.2,3 The costs of undiagnosed OSA because of comorbidity, lost productivity, and workplace or vehicle accidents is estimated at USD $149 billion.4 Treatment of OSA with continuous positive airway pressure (CPAP) improves health outcomes and is cost-effective.5
Rural residence has been associated with disparities in health outcomes for cardiovascular disease and cancer.6–9 Proposed contributors to inequities based on geography include differential access to health services, fewer trained providers, lower health literacy, and reluctance to seek care because of self-reliance or feelings of marginalization based on rural residence.10–14
Several studies have suggested that rural patients with OSA may experience barriers to care. Hirsch Allen et al15 identified an association between distance traveled for OSA care and OSA severity, and Spagnuolo and colleagues16 reported a higher rate of OSA symptoms without a diagnosis among rural patients with a longer distance to travel for specialist medical care. Recent studies have shown that despite a shift from traditional, laboratory-based to community-based ambulatory management pathways, patients from rural settings continue to experience long delays and poorly coordinated OSA care.17,18
Although the above studies highlight potential barriers to a diagnosis of OSA, to date there has been no evaluation of the impact of rural residence on OSA treatment outcomes. The primary objective of this study was to determine whether CPAP adherence differed between adults with uncomplicated OSA with rural vs urban residential address.
METHODS
Study design
We conducted a prospective cohort study to determine whether treatment adherence and patient-reported outcomes differed by rural vs urban residential address among patients initiating CPAP for uncomplicated OSA. The University of Calgary Conjoint Health Research Ethics Board approved this study (ethics identifier REB16-2230). Further details are available in the study protocol.19
Study setting
The study was conducted in Alberta, Canada, where individuals with suspected OSA typically present to a primary care physician and subsequently follow 1 of 2 main pathways: referral to a sleep specialist or referral to a community-based respiratory home care provider. Respiratory home care providers are private facilities staffed by registered respiratory therapists who administer home sleep apnea tests (HSATs) for OSA diagnosis, dispense positive airway pressure (PAP) equipment, and provide clinical follow-up of PAP therapy. HSATs are administered under the guidance of a board-certified or board-eligible sleep physician as the medical director and interpreted by sleep medicine specialists. The referring physician makes management decisions, which may include initiation of therapy or referral to a sleep specialist. The specialist referral pathway may include HSAT or polysomnography (PSG) at the discretion of the specialist, followed by initiation of therapy. In both pathways, respiratory home care providers dispense CPAP, but patients may also obtain CPAP devices secondhand or through online purchase so that the cost is typically lower; however, the support for therapy is also less.
PSG is provided through a mix of public and private facilities, and HSAT is typically provided to patients at no cost by private or public sleep laboratories or by respiratory home care providers. The costs of fixed or autotitrating CPAP therapy are paid through private insurance or out of pocket by the patient; government assistance programs cover the costs of therapy for patients who are financially disadvantaged. This model of care is similar to that of most Canadian provinces.17
Study participants
We recruited adults (age ≥ 18 years) who were initiating CPAP through a respiratory home care provider for a new diagnosis of OSA made by a physician using HSAT or PSG. Patients were excluded if they met 1 of the following criteria that precluded safe initiation of therapy in a community setting: presence of another form of sleep-disordered breathing such as central sleep apnea or hypoventilation, initiation of PAP therapies aside from CPAP, previous or current use of PAP therapy or oxygen, or failure to provide consent.
Patients were classified as rural or urban using the residential postal code at the time of CPAP initiation. Postal codes were translated into census geographic areas using the Statistics Canada Postal Code Conversion File Plus, version 7C (Statistics Canada, Ottawa, Canada).20 The Postal Code Conversion File Plus is a digital file that correlates a 6-character postal code with Statistics Canada’s standard geographic areas to determine the degree of metropolitan influence and enable accurate urban-rural classification. Using Statistics Canada’s definition of a large urban center (population > 100,000),21 patients with postal codes that were assigned a Community Size Classification of 1, 2, or 3 were classified as urban and those assigned a 4 or 5 were classified as rural.
We also classified patients as following either a community-based or a sleep facility pathway depending on whether the patient was directly managed by a sleep specialist or underwent PSG.
Study procedure
Patients were recruited from respiratory home care providers that met provincial accreditation standards for diagnostic testing. Home care providers were invited to participate through a provincial home care association, and 3 providers with multiple sites across Alberta agreed to participate. Home care provider staff identified potentially eligible patients at the time of CPAP initiation, discussed the study, and provided recruitment materials, including consent forms. There was no financial incentive given to the home care providers for recruitment or to patients for participation.
We obtained the following study data from each participant’s respiratory home care provider: patient demographics including postal code, self-reported comorbidities, sleep diagnostic testing results (HSAT and PSG), and CPAP machine downloads revealing nightly use, residual OSA, and mask leaks. Each participant also completed 4 study questionnaires: the Epworth Sleepiness Scale (ESS; baseline and 3 months), the EuroQOL-5D 3-level ranking instrument (EQ-5D-3L; baseline and 3 months), and the Visit-Specific Satisfaction Instrument (VSQ-9; 3 months) and a questionnaire developed by the investigators that captured patient-reported wait times for OSA care and patient-borne costs.
Baseline questionnaires were administered electronically using the Research Electronic Data Capture platform22,23 hosted at the University of Calgary or on paper if patients preferred. Three months after initiation of CPAP, patients received an email link to the Research Electronic Data Capture questionnaires. If patients did not complete the questionnaires, then they received weekly email reminders for 4 weeks followed by a mailed paper copy with a postage-paid envelope and a telephone call from a research assistant to ensure receipt and/or to complete the questionnaires by phone.
Analysis
The primary outcome was the mean daily number of hours of CPAP use from machine downloads, measured in the last 4 weeks of the 3-month study period and compared between rural and urban patients. Secondary outcomes were also compared between rural and urban patients and included the proportion of patients who were CPAP-adherent (≥ 4 hours of CPAP use on 70% of nights),24 change in ESS from baseline to 3 months, change in EQ-5D-3L overall score from baseline to 3 months, and Visit-Specific Satisfaction Instrument score at 3 months. The published protocol (see study design section) specified a comparison of outcomes between the community-based and sleep facility pathway; however, because of the small number of participants following the sleep facility pathway this analysis was not possible.
Study outcomes were analyzed using t tests or Mann-Whitney U tests for continuous variables as appropriate. Chi-square tests were used to compare the proportion of patients who were CPAP-adherent. Multiple linear regression models were constructed to evaluate the association between urban vs rural residence and hours of nightly CPAP use, using the following independent variables based on literature review and expert consensus: age, sex, body mass index, education level, median household income, respiratory event index from HSAT, baseline ESS, change in ESS, baseline EQ-5D-3L visual analog score, change in EQ-5D-3L visual analog score, Visit-Specific Satisfaction Instrument score, distance (in kilometers) to CPAP provider, time (in days) from referral for sleep testing to test completion, and time (in days) from referral for sleep testing to CPAP initiation. We constructed additional models that included comorbidities and medications and also constructed models without potential causal variables such as change scores for patient-reported outcomes and distance traveled for appointments. Multivariable logistic regression models were constructed to evaluate the relationship between urban vs rural residence and proportion of patients who were CPAP-adherent using the same independent variables. A per protocol analysis of the primary outcome was conducted using data from patients who were still using CPAP at 3 months.
Using the minimally clinically important difference in CPAP adherence of 0.5 hours with a standard deviation of 1 hour,25 200 participants (100 per group) were required to detect a difference between rural and urban patients with 90% power and a 2-sided type I error rate of 0.025. Statistical analyses were performed using STATA version 11 (2019; StataCorp LLC, College Station, TX). P values < .05 were considered statistically significant.
RESULTS
Between December 2018 and November 2020, 253 patients were recruited, of whom 242 were included in the analysis (Figure 1). Table 1 summarizes baseline patient characteristics, and the distribution of patients and locations of the 29 respiratory home care provider sites is depicted in Figure 2. There were 101 women. The mean (standard deviation) age was 51 (13) years, and the mean body mass index was 34 (10) kg/m2. The mean respiratory event index was 24 (18) events/h, and the mean oxygen saturation was 91% (2.5%). Twenty patients (8%) followed the specialist pathway; of these patients, 7 underwent PSG. One hundred patients had a rural residential address. This group had lower median household income, more delays for diagnosis and treatment, and a longer driving distance to obtain OSA treatment (Table 1).
Figure 1. Patient flow.
CPAP = continuous positive airway pressure.
Table 1.
Baseline characteristics of study participants.
| Total Cohort (n = 242) | Urban Residence (n = 142) | Rural Residence (n = 100) | |
|---|---|---|---|
| Age, y | 51 (13) | 51 (13) | 50 (13) |
| Female sex, n (%) | 101 (42) | 64 (45) | 37 (37) |
| Body mass index, kg/m2 | 34 (10) | 34 (9) | 34 (10) |
| Community pathway, n (%) | 220 (92%) | 126 (90%) | 95 (95%) |
| Comorbidity, n (%) | |||
| Diabetes | 21 (9) | 13 (9) | 8 (8) |
| Hypertension | 85 (35) | 50 (35) | 35 (35) |
| Cardiovascular disease | 53 (22) | 35 (25) | 18 (18) |
| Congestive heart failure | 16 (7) | 8 (6) | 8 (8) |
| COPD | 40 (17) | 26 (18) | 14 (14) |
| Chronic pain | 8 (3) | 7 (5) | 1 (1) |
| Mental health | 91 (38) | 55 (39) | 36 (36) |
| Questionnaire data | |||
| Median household income, CAD*,† | 98,652 (32,474) | 103,740 (36,291) | 91,355 (24,422) |
| Education (beyond high school), n (%) | 176 (73) | 100 (70) | 76 (76) |
| CPAP coverage, n (%)‡ | |||
| Government-funded program | 10 (7) | 8 (9) | 2 (4) |
| Private insurance | 97 (69) | 59 (64) | 38 (78) |
| Self-pay | 34 (24) | 25 (27) | 9 (18) |
| ESS score | 9.5 (5.4) | 9.5 (5.3) | 9.4 (5.5) |
| EQ-5D-3L visual analog score | 70 (16) | 68 (18) | 71 (14) |
| Driving distance to CPAP provider, km† | 43 (85) | 19 (49) | 77 (110) |
| Time to diagnosis, d† | 27 (44) | 20 (27) | 37 (58) |
| Time to treatment, d† | 72 (68) | 62 (61) | 85 (76) |
| HSAT | |||
| Respiratory event index, events/h | 24 (18) | 23 (17) | 26 (19) |
| Mean SpO2, % | 91 (2.5) | 91 (2.5) | 91 (2.5) |
| Time with SpO2 < 90%, % | 36 (30) | 38 (30) | 34 (30) |
Results are presented as mean (SD) unless otherwise indicated. *Aggregate data based on Postal Code Conversion File—individual household income data not available. †P < .05 for difference between urban and rural groups. ‡Partial or complete coverage by government or private insurance (data available for 142 patients). CAD = Canadian dollars, COPD = chronic obstructive pulmonary disease, CPAP = continuous positive airway pressure, EQ-5D-3L = EuroQOL-5D 3-level visual analog score, ESS = Epworth Sleepiness Scale, HSAT = home sleep apnea test, SD = standard deviation, SpO2 = oxygen saturation measured by pulse oximetry.
Figure 2. Distribution of patients and respiratory home care providers.
Gray line demarcates Alberta provincial borders. Black squares represent respiratory home care providers and red dots represent patients. Insets depict magnified distribution of providers and patients in Calgary (lower left) and Edmonton (upper right).
Treatment outcomes
Adherence to CPAP and patient-reported outcomes are presented in Table 2. There was no statistically significant difference in the primary outcome of mean (95% confidence interval) hours of CPAP use between urban and rural patients with respect to hours of CPAP use (3.25 [2.74–3.75] vs 3.08 [2.46–3.69] hours; mean difference, 0.17 [–0.62 to 0.96] hours; P = .68). Although all patients initiated CPAP, 61% of rural patients and 68% of urban patients were using CPAP at 3 months. After excluding those who were not using CPAP, we found that mean (95% confidence interval) adherence was 4.8 (4.29–5.3) hours in the urban group and 5.04 (4.42–5.66) hours in the rural group (mean difference, –0.24 [–1.04 to 0.55]; P = .55). The proportion of patients who were CPAP-adherent was similar in both groups (36% vs 34%; P = .76).
Table 2.
Study outcomes at 3 months.
| Total Cohort | Urban Residence | Rural Residence | P | |
|---|---|---|---|---|
| CPAP use, h | ||||
| All patients | 3.19 (2.8–3.58), n = 242 | 3.25 (2.74–3.75), n = 142 | 3.08 (2.46–3.69), n = 100 | .67 |
| CPAP use > 0 | 4.89 (4.51–5.28), n = 157 | 4.80 (4.29–5.3), n = 96 | 5.04 (4.42–5.66), n = 61 | .55 |
| Adherent, n (%) | 85 (35), n = 242 | 51 (36), n = 142 | 34 (34), n = 100 | .76 |
| Change in ESS | –2.5 (–3.2 to –1.8), n = 136 | –2.3 (–3.2 to –1.4), n = 90 | –2.8 (–4 to –1.7), n = 46 | .47 |
| Change in EQ-5D-3L | 1.3 (–1.1 to 3.7), n = 137 | –0.5 (–3.7 to 2.8), n = 89 | 4.6 (1.5–7.6), n = 48 | .04 |
| VSQ-9 total score | 38 (37–39), n = 130 | 38 (37–39), n = 86 | 38 (36–40), n = 44 | .90 |
Results are presented as mean (95% CI) unless otherwise indicated. CI = confidence interval, CPAP = continuous positive airway pressure, EQ-5D-3L = EuroQOL-5D 3-level visual analog score, ESS = Epworth Sleepiness Scale score, VSQ-9 = Visit-Specific Satisfaction Instrument.
Follow-up questionnaires were available for 138 patients. There was a clinically important improvement in ESS, with no significant difference between rural and urban patients. The EQ-5D-3L visual analog scale improved to a greater degree among rural patients (mean [95% confidence interval] difference, 5.08 [0.16–10]; P = .04). Patient satisfaction was high and not significantly different between groups. Patients who responded to follow-up questionnaires were older (aged 53 (13) vs 48 (13) years; P = .0018) and had higher hours of CPAP use at 3 months (3.8 [3.29–4.32] vs 2.34 [1.77–2.91] hours; P = .0002) than those who did not respond. There was no difference in CPAP adherence between rural and urban patients when they were stratified by questionnaire response.
Regression analysis revealed that rural vs urban residence was not associated with CPAP adherence in models that included potential confounders. Lower baseline ESS and greater change in ESS were associated with CPAP adherence, in terms of both hours of use and proportion using for ≥ 4 hours on 70% of nights (Table 3). Time to diagnosis was also associated with being adherent to CPAP. In expanded models that included comorbidities and medications, similar results were obtained except that the proportion of patients who were adherent to CPAP was associated with increased age and absence of self-reported antihypertensive use. In models that excluded potential causal variables, there was no significant relationship between urban or rural residence and CPAP adherence.
Table 3.
Regression analysis.
| CPAP Use (Hours/Night) | Adherent to CPAP (Yes/No) | |||
|---|---|---|---|---|
| Coefficient | P | Odds Ratio | P | |
| Rural residence | 0.68 (–0.62 to 1.98) | .304 | 1.28 (0.44–3.73) | .657 |
| Female sex | –0.289 (–1.43 to 0.85) | .614 | 0.59 (0.23–1.48) | .258 |
| Age (years) | 0.03 (–0.01 to 0.08) | .151 | 1.04 (0.99–1.08) | .086 |
| Body mass index (kg/m2) | 0.06 (–0.02 to 0.13) | .123 | 1.04 (0.98–1.11) | .182 |
| Education beyond high school | 0.05 (–0.26 to 0.36) | .753 | 0.99 (0.76–1.28) | .933 |
| Median household income | 0 (–0.00001 to 0.00002) | .548 | 1 (1–1) | .363 |
| Respiratory event index | 0.003 (–0.03 to 0.03) | .825 | 0.99 (0.97–1.02) | .488 |
| Baseline ESS | –0.2 (–0.33 to –0.05) | .007 | 0.84 (0.73–0.96) | .012 |
| Change in ESS | 0.29 (0.12–0.47) | .001 | 1.26 (1.07–1.49) | .005 |
| Baseline EQ-5D-3L | 0.007 (–0.03 to 0.05) | .716 | 1 (0.97–1.04) | .901 |
| Change in EQ-5D-3L | 0.009 (–0.03 to 0.05) | .697 | 1 (0.96–1.04) | .942 |
| VSQ-9 score | 0.006 (–0.08 to 0.09) | .892 | 0.99 (0.92–1.07) | .856 |
| Distance to CPAP provider (km) | 0.0003 (–0.006 to 0.007) | .928 | 1 (1–1.01) | .313 |
| Time to diagnosis (days) | –0.02 (–0.03 to 0.0009) | .063 | 0.97 (0.95–0.99) | .01 |
| Time to treatment (days) | 0.0006 (–0.01 to 0.01) | .919 | 1 (0.99–1.01) | .796 |
Results are presented as mean (95% CI). n = 114. CI = confidence interval. CPAP = continuous positive airway pressure, ESS = Epworth Sleepiness Scale score, EQ-5D-3L = EuroQOL-5D 3-level visual analog score, VSQ-9 = Visit-Specific Satisfaction Instrument.
DISCUSSION
The results of this study reveal that in uncomplicated patients with OSA, urban vs rural residence was not associated with differences in CPAP use or adherence to therapy. Sleepiness and patient satisfaction with care were similar between groups after 3 months of therapy, but patients from rural settings experienced greater improvements in health-related quality of life. This is the first study to explore the impact of rural residence on treatment outcomes for OSA and suggests that clinical pathways incorporating sleep specialist–interpreted diagnostic sleep studies for uncomplicated OSA result in similar treatment outcomes in both urban and rural populations.
Adherence to CPAP was associated with daytime sleepiness at baseline and after therapy, which is consistent with previous reports.26,27 We also found that a shorter wait time for care was associated with CPAP adherence, as has been shown previously in a more complex patient population.28 Notably, residential geography was not associated with adherence to therapy. Together, these findings suggest that the drivers of CPAP adherence are similar among rural and urban adults.
This study builds on prior work suggesting that individuals who must travel for specialty sleep care face barriers to diagnosis, leading to underrecognition of OSA and more severe disease at presentation. In a study of 1,275 patients referred with suspected OSA, Hirsch Allen et al15 found that travel distance to an academic tertiary sleep disorders clinic in British Columbia, measured using postal codes, was associated with OSA severity after adjustment for several important covariates. Spagnuolo and colleagues16 used self-reported data from 6,575 adults living in rural settings, capturing OSA symptoms, OSA diagnosis, and travel distance for medical or surgical specialty care, to determine that the prevalence of OSA symptoms in the absence of an OSA diagnosis was related to travel distance. However, they did not find a difference in diagnosis rates overall, suggesting a decreased use of health services in more remote communities. Underdiagnosis or delays in OSA diagnosis in rural communities are important considerations in the design of service delivery models for OSA to mitigate the significant health and societal costs of untreated disease.3,4 However, our results suggest that once a diagnosis is made with appropriate specialist involvement, treatment outcomes are similar. As such, delivery models that facilitate establishing a diagnosis may mitigate outcome disparities based on geography.
The optimal involvement of sleep specialists in clinical pathways for uncomplicated patients has been explored in several studies. Pamidi et al29 showed that 30-day CPAP adherence was higher among patients who had been assessed by a sleep specialist before PSG than those who were referred for testing by non–sleep physicians, although after adjustment for demographic factors this difference was no longer significant. Two studies comparing care in facilities accredited by the American Academy of Sleep Medicine against care in unaccredited facilities revealed an association between accreditation and several measures of health care quality, including PAP adherence and patient satisfaction.30,31 In contrast, several randomized trials have indicated noninferiority of primary care management of uncomplicated OSA with appropriate education and support from sleep specialists.32–35 This model for OSA care also aligns with patient preference for chronic disease management within a primary care setting, especially among patients in rural areas who may be less likely to obtain care in larger centers.14,18
Sleep specialist capacity is also limited in rural settings, supporting the need for alternative ways to deliver OSA care that are supported by but not necessarily led by specialists.17,18 Several examples of integrated care delivery models for OSA have been proposed, many of which could be applied in rural settings.36–38 In this study, sleep specialists were primarily involved in the interpretation of HSAT, with only a minority of patients (8%) undergoing diagnostic testing or clinical assessment in a specialty care setting. The relatively small number of patients following the specialist pathway could suggest that guidance from specialist-interpreted sleep diagnostic testing may be adequate for non–sleep specialists to manage uncomplicated OSA.
Adherence to therapy in the entire study cohort was low, with 35% of patients meeting the prespecified definition of adherence and approximately one-third discontinuing CPAP before 3 months. These findings were not different between groups, but they reflect poorer adherence than prior reports evaluating models of OSA care in rigorous research settings or in sleep specialty clinic referral populations.31,33–35 However, our results are consistent with published adherence data among patients initiating CPAP in real-world settings.39 Whereas others have shown higher 90-day CPAP use in large cohorts, these data were obtained from those with > 1 hour of CPAP use.40 Similar results were observed in our study among the two-thirds of patients who continued CPAP at 3 months (4.89 hours/night); notably, our goal was to identify differences between urban and rural patients, and none were observed. The regression analysis revealed that CPAP use was associated with both baseline sleepiness and improvement in sleepiness with CPAP use. Notwithstanding the potential benefits from lower levels of CPAP use,41 these results could be used to develop interventions aimed at improving initial acceptance and use of CPAP among symptomatic patients.
This study has important limitations. First, the observational nature of this study raises the possibility of unmeasured confounding. We tried to mitigate this risk by capturing a broad range of potential confounders in our analysis, including sociodemographic characteristics and comorbidity. However, the exposure of interest (rural vs urban residence) precluded the use of a randomized study design. Second, enrollment at the time of CPAP initiation introduced selection bias because patients with suspected OSA who did not initiate CPAP were systematically excluded. This limitation is especially relevant because sleep care is mostly privately funded in Alberta; the study findings thus cannot be extended to individuals who did not access sleep testing or initiate CPAP through a respiratory home care provider for financial, medical, or other sociodemographic reasons. Although we included patients who required government assistance for CPAP funding, we acknowledge the importance of future studies examining the entire spectrum of OSA care to fully characterize health disparities. Third, the response rate for follow-up questionnaires was low (57%) and lower among rural patients compared to urban patients. Patients with poorer experiences with care may be less likely to complete a study questionnaire; because response rates were lower in the rural group, the reported results may overestimate patient-reported outcomes in this group. Notably, we analyzed PAP adherence data for the entire cohort regardless of questionnaire response rate and found that lower adherence among those who did not complete questionnaires did not differ by rural or urban status. Finally, this study was performed in uncomplicated patients who were largely managed in community-based settings; thus, the findings cannot be extrapolated to models of care that involve more medically complex patients.
In conclusion, the outcomes of CPAP therapy are similar among urban and rural patients with uncomplicated OSA that is diagnosed using sleep specialist-interpreted diagnostic testing. The findings of this study can be used to support high-quality OSA care across the geographic continuum.
DISCLOSURE STATEMENT
All authors agree to be accountable for all aspects of the work and approve of the submitted manuscript. Work for this study was performed at the University of Calgary, Calgary, Canada. This study was funded by The Lung Association, Alberta & Northwest Territories, and the Alberta Health Services Respiratory Health Strategic Clinical Network. The authors report no conflicts of interest.
ACKNOWLEDGMENTS
The authors acknowledge the respiratory home care providers who supported recruitment and data collection for this study.
ABBREVIATIONS
- CPAP
continuous positive airway pressure
- EQ-5D-3L
EuroQOL-5D 3-level ranking instrument
- ESS
Epworth Sleepiness Scale
- HSAT
home sleep apnea test
- OSA
obstructive sleep apnea
- PAP
positive airway pressure
- PSG
polysomnography
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