The hospitalization risks and costs of positive airway pressure were evaluated among patients with obstructive sleep apnea in a real-world setting.
To evaluate the clinical and economic impact of positive airway pressure (PAP) among patients with obstructive sleep apnea (OSA).
Retrospective claims-based analysis of OSA patients diagnosed with polysomnography (PSG) between January 1, 2005, and April 30, 2008.
Patients were required to have 2 or more claims for OSA diagnosis within 1 year after their first PSG test, and a minimum of 12 months’ baseline and 24 months’ follow-up continuous health plan enrollment. Patients with pulmonary disease or PAP use before the first PSG test were excluded. Outcomes included all-cause and sleep apnea—related hospitalization and healthcare costs. Multivariable analyses were performed to adjust for baseline characteristics.
Of the 15,424 patients identified, 90.7% used PAP and 9.3% did not. The PAP group had lower all-cause (19.0% vs 24.2%, P <.001) and sleep apnea—related (8.0% vs 11.3%, P <.001) hospitalization rates than the non-PAP group during the follow-up period. After adjusting for baseline characteristics, patients in the PAP group were less likely to have an all-cause (odds ratio [OR] 0.70; 95% confidence interval [CI] 0.61-0.80]) or sleep apnea—related (OR 0.69; 95% CI 0.58-0.83) hospitalization than non-PAP patients. PAP users on average incurred 10% lower all-cause costs than non-PAP patients ($705 per member per month vs $786 per member per month, P <.001) in multivariable analysis.
Among OSA patients in real-world practice, PAP users had significantly lower hospitalization risks and all-cause healthcare costs.
(Am J Manag Care. 2012;18(6):e225-e233)This study demonstrated that patients with obstructive sleep apnea (OSA) who initiated positive airway pressure (PAP) had clinically significant lower hospitalization risk and lower all-cause healthcare costs than patients who did not use PAP.
Obstructive sleep apnea (OSA) is a common breathing disorder characterized by the recurrence of partial or complete collapse of the soft palate and associated soft tissues of the upper airway during sleep.1 This results in oxygen deprivation from poor gas exchange, which leads to arousals from sleep and overall sleep fragmentation.2 Available population-based studies indicate that the prevalence of OSA ranges from 3% to 7% in adult men and 2% to 5% among adult women.3,4 Among middle-aged adults, the prevalence of OSA is 26% for men and 9% for women.5 The prevalence of OSA has been reported to increase with age at a steady rate, especially among men.3,6
The most common symptoms of OSA include daytime sleepiness, loud snoring, interrupted breathing, and choking-related awakenings.2,7,8 Recent epidemiologic studies have demonstrated that OSA is associated with cardiovascular disease,9 heart failure, coronary artery disease, cerebrovascular disease, diabetes mellitus,2,10,11 and hypertension.12-14 Additionally, OSA has also been identified as a primary independent risk factor in the development of hypertension15 and heart failure.16 Despite known health risks, current literature suggests that more than 80% of patients with moderate to severe OSA have not been clinically diagnosed.11,17
Two commonly accepted tests for OSA are in-laboratory polysomnography (PSG) and in-home testing facilitated by portable monitors.7 For more than 2 decades now, PSG has gained acceptance as the gold standard for the diagnosis of sleep-associated disordered breathing.18-21 The use of PSG is typically associated with supervised overnight laboratory testing to diagnose all cases of suspected OSA. In addition to the PSG diagnostic test, a variety of monitoring devices have been used to measure breathing disturbances during sleep in studies,22 and for the titration of continuous positive air pressure (CPAP) in the treatment of OSA.23 Commercial health plans and the Centers for Medicare & Medicaid Services include tests associated with breathing-affected sleep in their benefits package.24
Among the available treatments for OSA, positive air pressure(PAP) devices have become the acknowledged gold standard for treating patients with moderate to severe OSA.2,7,25 The most common form of PAP, CPAP, works through the application of positive pressure to the upper airway at a constant level to keep the pharyngeal airway open during sleep. The bilevel PAP, which provides 2 levels of pressure to maintain set airway pressures, is also commonly used to treat OSA, especially for patients who are intolerant of or unresponsive to initial fixed-pressure CPAP. The Agency for Healthcare Research and Quality in the United States has not developed guidelines for the treatment of OSA, but does promote those introduced by the United Kingdom’s National Institute of Health and Clinical Excellence, which recommended CPAP and bilevel PAP as technology-based treatment options for adults diagnosed with moderate or severe OSA.25 The Adult OSA Task Force of the American Academy of Sleep Medicine has also recommended the use of CPAP for the treatment of moderate to severe OSA patients and bilevel PAP in the management of OSA in CPAP-intolerant patients.7
Costs attributable to the diagnosis and treatment of moderate to severe OSA are estimated at $2 billion to $10 billion per year. This reflects only a small proportion of the overall estimated economic burden of the disease, which ranges from $65 billion to $165 billion after accounting for absenteeism, loss of productivity, and workplace and traffic accidents.8 Given the increased morbidity associated with OSA, it is plausible that undiagnosed or untreated OSA may have an economic burden on the healthcare system. Kapur et al reported that patients diagnosed with OSA have $1336 higher annual medical costs in the year prior to their diagnosis compared with matched controls, which could well represent an estimate of the medical costs of untreated OSA.26 A Canadian study compared OSA patients with matched controls over a 10-year prediagnosis period and found that patients with OSA used about twice as many healthcare services during the prediagnosis period as patients in the control group, adding to the evidence that patients with OSA are heavy users of healthcare services.27
Available evidence shows that CPAP and bilevel PAP therapy are safe.7,28 The economic impact of treating OSA patients with PAP, however, has not been well evaluated and documented. One small Swedish study, which compared hospitalizations before and after CPAP initiation among 88 OSA patients within a 2-year period, found that CPAP therapy reduced hospital admissions among OSA patients and resulted in reduced consumption of healthcare resources.29 To date, no study has used a large population sample to assess the clinical and economic effects of PAP in realworld practice. This study was designed to evaluate the impact of PAP on hospitalization risks and healthcare costs among patients with PSG-diagnosed OSA using a large health insurance administrative claims database.
This was a retrospective cohort study using patient-level administrative claims data from the HealthCore Integrated Research Database, which consists of 12 regional commercial health insurance plans spread across the northeastern, southeastern, mid-Atlantic, Midwestern, and western regions of the United States. At the time this study was conducted, the HealthCore Integrated Research Database included medical claims, pharmacy claims, eligibility files, and laboratory test results data for approximately 43 million health plan enrollees. All data used in this observational study were deidentified and accessed using protocols compliant with the regulations of the Health Insurance Portability and Accountability Act of 1996. Patient confidentiality was preserved and the anonymity of all patient data was safeguarded throughout the study.
Inclusion and Exclusion Criteria
Patients between 18 and 64 years old with a medical claim for a PSG diagnostic test (Current Procedural Terminology [CPT] codes of 95806-95811) between January 1, 2005, and April 30, 2008, were identified. Patients were required to have 2 or more claims with a diagnosis code for OSA (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code of 327.23) within 1 year after their first PSG test date. Patients older than 65 years were excluded from this study to avoid confounding due to potential dual coverage, with Medicare as an additional insurer. To make sure that patients were newly treated with PAP, subjects who had claims indicating the use of PAP (Healthcare Common Procedure Coding System [HCPCS] codes of E0601, E0470, or E0471), PAP-related supplies (HCPCS codes of A7027- A7039, A7045, or A7046), or PAP management (CPT code of 94660) prior to the first PSG test date were excluded. To avoid confounding by other primary respiratory conditions, patients with asthma (ICD-9 493.xx), chronic bronchitis (ICD-9 491.xx), emphysema (ICD-9 492.xx), extrinsic allergic alveolitis (ICD-9 495.xx), cystic fibrosis (ICD-9 277.0x), other alveolar and parietoalveolar pneumonopathy (ICD-9 516.xx), other sleep apnea (ICD-9 327.2x except 327.23), and pneumoconioses and other lung disease due to external agents (ICD-9 500.xx-506.xx) were also excluded due to the potential contradiction and compromise for the evaluation of the effectiveness of PAP use among OSA patients ().
The index date for patients using PAP (PAP group) was defined as the date of the first medical claim for PAP use. For patients not using PAP (non-PAP group), an index date was randomly assigned through Monte Carlo simulation based on the length of time between the PSG test and the initiation of PAP for corresponding PAP users. After simulation, a minimum of 36 months (12 months before the index date and 24 months after the index date) of continuous eligibility was required for both groups to ensure an adequate follow-up period for economic and clinical evaluation.
The main outcomes of interest were all-cause and sleep apnea— related hospitalization and direct costs over a 24-month postindex period. The all-cause hospitalization referred to inpatient admission with any cause of diagnosis, whereas the sleep apnea–related hospitalization referred to any inpatient admission with a sleep apnea diagnosis (ICD-9 327.23, 780.53, 780.57, or 780.51). Hospitalization risk was defined as the probability of having 1 or more hospitalizations during the follow-up period. Annualized hospital admission rates were used to assess the number of admissions per 1000 persons per year. The total all-cause costs were defined as the sum of medical and pharmacy costs associated with any condition from the claims data. Sleep apnea—related costs referred to costs associated with the treatment of sleep apnea incurred from inpatient, emergency department, and outpatient services, which were a subset of the all-cause costs. Costs were calculated on a per member per month (PMPM) basis, using the allowable amount reimbursed by health plans.
Baseline or the preindex period was defined as the 12 months prior to the index date (not including the index date) whereas the follow-up or postindex period was defined as 24 months after the index date (including the index date). Patients’ characteristics including age, sex, health plan type, and geographic region were compared between the 2 cohorts. Patients’ comorbid conditions were measured using the Deyo-Charlson Comorbidity Index (DCI) and specific sleep apnea—related comorbid conditions during the 12-month baseline period. The DCI consists of 19 diagnoses identified by ICD-9-CM codes, with a weight from 1 to 6 identified for each diagnosis.30 The final score consists of a sum of weighted values for the present comorbidities, and higher scores indicate greater comorbidity burden. In addition, baseline allcause and sleep apnea—related hospitalization and direct costs were captured.
All study measures were compared between the PAP group and the non-PAP group. Descriptive statistics on outcomes comparison included means (±SD) for continuous variables and frequencies (%) for categorical variables. The statistical significance of differences between the 2 groups was assessed using Student t tests for continuous variables, x2 tests for categorical variables, and Wilcoxon-Mann-Whitney tests for cost data. Demographic and clinical characteristics showing significant difference at baseline were included as covariates and controlled in the multivariable models. Multivariable logistic regression models were conducted to compare hospitalization risk between the PAP group and non-PAP group after adjusting for demographic and clinical characteristics at baseline. As all-cause costs follow a gamma distribution and sleep apnea—related costs follow the negative binomial distribution, generalized linear models (GLMs) with corresponding distributions were performed for the 2 outcomes, respectively, while controlling for baseline demographic and clinical characteristics. GLMs take on the following standard model form: Y = g (β0 + β1X1 + β2X2 + β3X3 + e). As in the linear model, Y is a vector of outcomes (ie, all-cause costs, sleep apnea–related costs assessed in our model). The Xs are linearly associated covariates (such as age and sex included in our model). The βs are regression coefficients, and e reflects the error variability that cannot be accounted for by the predictors. The inverse function of g(…) is the link function; it is chosen on the basis of the assumed distribution of the Y variable (ie, gamma, negative binomial distribution used in our model). All statistical analyses were conducted with SAS statistical software, version 9.1 (SAS Institute Inc, Cary, North Carolina). Statistical significance was examined using an alpha level of .05.
Patients’ Characteristics at Baseline
A total of 425,990 members with a medical claim for PSG diagnostic test were identified during the study period. Within this cohort, 15,424 OSA patients satisfied all the study criteria and were included (Appendix); 90.7% (n = 13,983) used PAP and 9.3% (n = 1441) did not during the study period. The presents the baseline demographic and clinical characteristics of all patients by study groups. The mean age of the study population was 48 years, and nearly 70% of the individuals were male. Significantly greater proportions of patients were covered by preferred provider organization insurance plans in both the PAP (70.6%) and the non-PAP
(71.8%) groups. Approximately 53% of the patients were from the West and Midwest regions of the United States; higher proportions of PAP users were found in Midwest (41.1%) and Southeast/Mid-Atlantic (31.7%).
In the baseline period, the mean DCI was 0.47 ± 1.01 for all study patients, indicating an overall relatively low comorbidity profile. The 3 most frequently occurring comorbidities were hypertension (57.8%), dyslipidemia (51.6%), and type 2 diabetes (17.9%). The differences in the DCI values between the 2 groups were statistically significant, and PAP users appeared to have an overall higher burden of disease than non- PAP patients at baseline (0.48 vs 0.39, P <.001). Compared with the non-PAP group, the PAP group had a higher proportion of patients with congestive heart failure (2.5% vs 1.5%, P = .019), hypertension (58.8% vs 48.1%, P <.001), type 2 diabetes mellitus (18.4% vs 13.3%, P <.001), dyslipidemia (52% vs 47.3%, P <.001), and obesity (14.9% vs 12.8%, P =.033) at baseline.
We evaluated the distribution of different types of PAP devices and numbers of PSG diagnostic tests used for the study patients. The most commonly used PAP was CPAP (93.2%), followed by bilevel respiratory assist devices without backup rate features (6.5%) and bilevel respiratory assist devices with backup rate features (0.3%). On average, PAP users received their PAP devices 50 days after the date of their first PSG test. Compared with PAP users, the proportion of non-PAP patients who had 2 or more PSG tests at baseline was lower (80.1% vs 66.5%, P <.001).
Hospitalization Risk and Healthcare Costs During Follow-up Period
PAP users were observed to be sicker than the non-PAP patients at baseline, yet they had more favorable outcomes after the treatment was initiated. The all-cause hospitalization rate was 19.0% for PAP users and 24.2% for non-PAP patients during the 24-month postindex period (P <.001), as shown in . Similarly, the PAP group had a statistically lower percentage of patients with attributable sleep apnea—related hospitalization during the follow-up period compared with the non-PAP group (8.0% vs 11.3%, P <.001). After adjusting for baseline demographic and clinical characteristics, PAP users had significantly lower risks of an all-cause hospitalization (odds ratio [OR] 0.70; 95% confidence interval [CI] 0.61-0.80) and sleep apnea—related hospitalization (OR 0.69; 95% CI 0.58-0.83) than those who did not use PAP, as shown in .
The reduced risk of hospitalization also coincided with the significantly lower annual hospital admission rate for the PAP group compared with the non-PAP group during the follow-up period (144 hospitalizations per 1000 persons vs 177per 1000 persons, P = .003), as shown in . Similarly, the PAP group had significantly fewer sleep apnea—related hospitalizations per year than the non-PAP group during the follow-up period (47 per 1000 persons vs 64 per 1000 persons, P = .002).
During the 24-month follow-up period, unadjusted allcause costs were about $840 PMPM for both the PAP and non-PAP groups. PAP users had higher sleep apnea—related costs than the non-PAP patients ($181 PMPM vs $151 PMPM, P <.001) over time because of the additional costs associated with the PAP devices and related supplies (approximately $89 PMPM during the follow-up period). Results from the multivariable analyses showed that sleep apnea—related costs were higher for PAP users versus non-PAP patients (adjusted $172 PMPM vs $148 PMPM, P <.001); however, PAP users on average incurred about 10% lower total allcause costs than non-PAP patients (adjusted $705 PMPM vs $786 PMPM, P <.001) after controlling for demographics and baseline characteristics, as shown in .
The cost of diagnosing and treating OSA is estimated at about $2 billion to $10 billion per year.8 This estimate is likely to grow along with the increasing obesity and aging in the population, both of which are considered independent risk factors for the development of OSA.2,26 Currently there is no cure for OSA, and no pharmacologic treatment has been approved for this condition. PAP has been demonstrated to be an effective treatment for OSA patients, and increased knowledge about the economic consequences associated with the use of PAP could be an important consideration in the initiation and promotion of PAP therapy.
Our findings indicate that there were greater proportions of PAP users than non-PAP patients in the Midwest and Southeast/Mid-Atlantic region. In acknowledgment of these differences, regional variations were controlled for in the multivariable model for this study. The reasons for such variation were interesting but were not the focus of this study. Other baseline demographic and clinical characteristics that were found to be significantly different between the 2 groups were also included in the models.
Consistent with previous research,29 the findings of this study suggested that PAP treatment was associated with lower hospital admission in patients with OSA. This study showed a lower average annual rate of 33 per 1000 persons for all-cause hospitalization and 17 per 1000 persons for sleep apnea—related hospitalizations for PAP users compared with non-PAP patients. In addition, OSA patients on PAP therapy were about 30% less likely to have an allcause and sleep apnea–related hospital admission during the 24-month follow-up period compared with those who did not use PAP, which was independent of age, sex, type of health plan, geographic region, specific comorbid conditions (including congestive heart failure, hypertension, type 2 diabetes mellitus, and obesity), antidepressant medication use, time from PSG test to index date, and baseline outcome measures.
Furthermore, patients in the PAP group were found to have lower all-cause costs of $81 PMPM compared with those in the non-PAP group (P <.001). The all-cause cost savings among PAP users was driven by lower use of non—sleep apnea related healthcare services. Previous studies observed that PAP therapy had a direct effect on both the incidence and prevalence of major chronic conditions,9,31,32 which drive more than 75% of America’s healthcare costs.33 While PAP users had adjusted sleep apnea—related costs in the multivariate model that were $24 higher PMPM than those of the non-PAP patients, it was expected as PAP treatment is initiated. When taking out the treatment costs, our descriptive analysis showed that the PAP group had lower sleep apnea–related costs that were not associated with the PAP devices and related supplies ($92 vs $151). Further study is needed to identify and quantify the specific sources of reduced utilization and costs.
While this study did not take treatment adherence into account due to unavailability in the data source, it did observe significant clinical and economic benefits for OSA patients who initiated PAP therapy.34,35 Better treatment adherence has been found to be associated with decreased healthcare resource utilization and costs for many chronic diseases such as diabetes,36,37 hypertenstion,37 multiple sclerosis,38 and cardiovascular disease.39 With proper clinical management40,41 and technical improvements in PAP therapy,42 adherence to CPAP would be improved and has been shown to be as high as 80% for OSA patients.43,44 Therefore, both the clinical
and economic benefits observed in the current study could be greater if the full benefit of PAP could be obtained through optimal treatment adherence.
Obstructive sleep apnea is a substantially underdiagnosed and undertreated chronic disease in the United States, and an estimated 80% to 85% of patients have not been identified.5,8 Underdiagnosis and undertreatment have negative clinical and economic consequences. Prior studies have demonstrated that patients with underdiagnosed or undertreated OSA have higher healthcare costs, longer hospital stays, and more physician visits than those without OSA.26,45,46 If underdiagnosed or undertreated OSA patients received appropriate diagnosis along with treatment in a timely manner, PAP therapy could potentially reduce healthcare costs and acute severe events (hospitalization), potentially leading to better quality of life in the long term.
The findings of the study should be interpreted with caution as administrative claims data are primarily collected for the purpose of reimbursement, not research, and are thereby subject to inherent study design limitations. The database used for this analysis included patients from a wide geographic expanse of the United States, allowing for generalization of the results to commercially insured populations at the national level but not to Medicaid, uninsured, or other populations. The accuracy OSA diagnosis codes on medical claims was not validated, and diagnosis codes could be incorrectly coded or missing. In this study, however, the requirement for 2 or more diagnoses minimized the likelihood of false-positive coding errors. Claims data do not typically include the full range of measures, which could lead to additional confounding in the results; however, the important available covariates were controlled for in our multivariable models. This study focused on assessing direct healthcare costs and hospitalization risks, and indirect costs or quality-of-life issues associated with OSA were not considered. Obstructive sleep apnea has relatively higher indirect costs than a number of other chronic illnesses,8 suggesting that the marginal benefit of treating new patients could be higher.
This study demonstrated that newly diagnosed OSA patients who initiated PAP therapy had clinically significant lower hospitalization risk and lower all-cause healthcare costs compared with patients who did not use PAP. To the best of our knowledge, this is the first study that compared the economic outcomes of OSA patients who used PAP devices with those of OSA patients who did not. Findings from this study offer tangible data to payers, providers, and patients on the effectiveness of PAP on both clinical and economic outcomes. These findings can be used by health plans in educating patients and physicians about selecting appropriate treatment of OSA. Further research in this area needs to focus on identifying additional and specific sources of cost savings associated with PAP treatment.Acknowledgments
Bernard B. Tulsi, MSc, provided writing and other editorial support for this manuscript.
Author Affiliations: HealthCore, Inc (QC, HT, JS), Wilmington, DE.
Funding Source: ResMed Corp, San Diego, CA.
Author Disclosures: All authors report employment with HealthCore, Inc, the research subsidiary of WellPoint. The authors report no relationship with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (QC, HT, JS); acquisition of data (QC, HT); analysis and interpretation of data (QC, HT, JS); drafting of the manuscript (QC, JS); critical revision of the manuscript for important intellectual content (QC, HT, JS); statistical analysis (QC); obtaining funding (QC, HT); and supervision (HT).
Address correspondence to: Qian Cai, MS, MSPH, HealthCore, Inc, 800 Delaware Ave, 5th Fl, Wilmington, DE 19801-1366. E-mail: email@example.com. Punjabi NM. The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc. 2008;5(2):136-143.
2. Kapur VK. Obstructive sleep apnea: diagnosis, epidemiology, and economics. Respir Care. 2010;55(9):1155-1167. on sleep apnea in men, I: prevalence and severity. Am J Respir Crit Care Med. 1998;157(1):144-148.
4. Young T, Peppard PE, Gottlieb DJ. Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med. 2002;165(9):1217-1239.
5. Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S. The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med. 1993;328(17):1230-1235.
6. Bixler EO, Vgontzas AN, Lin HM, et al. Prevalence of sleep-disordered breathing in women: effects of gender. Am J Respir Crit Care Med. 2001; 163(3, pt 1):608-613.
7. Epstein LJ, Kristo D, Strollo PJ Jr, et al; Adult Obstructive Sleep Apnea Task Force of the American Academy of Sleep Medicine. Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults. J Clin Sleep Med. 2009;5(3):263-276.
8. Harvard Medical School Division of Sleep Medicine. The Price of Fatigue: The Surprising Economic Costs of Unmanaged Sleep Apnea. http://sleep.med.harvard.edu/what-we-do/public-policy-research. Accessed June 1, 2011.
9. Peker Y, Hedner J, Norum J, Kraiczi H, Carlson J. Increased incidence of cardiovascular disease in middle-aged men with obstructive sleep apnea: a 7-year follow-up. Am J Respir Crit Care Med. 2002;166(2): 159-165.
10. Pagel JF. Obstructive sleep apnea (OSA) in primary care: evidencebased practice. J Am Board Fam Med. 2007;20(4):392-398.
11. Young T, Evans L, Finn L, Palta M. Estimation of the clinically diagnosed proportion of sleep apnea syndrome in middle-aged men and women. Sleep. 1997;20:705-706.
12. Nieto FJ, Young TB, Lind BK, et al. Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study: Sleep Heart Health Study [published correction appears in JAMA. 2002;288(16):1985]. JAMA. 2000;283(14):1829-1836.
13. Richert A, Ansarin K, Baran AS. Sleep apnea and hypertension:
pathophysiologic mechanisms. Semin Nephrol. 2002;22(1):71-77.
14. Smith R, Ronald J, Delaive K, Walld R, Manfreda J, Kryger MH. What are obstructive sleep apnea patients being treated for prior to this diagnosis? Chest. 2002;121(1):164-172.
15. Chobanian AV, Bakris GL, Black HR, et al; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention,
Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report [published correction appears in JAMA. 2003;290(2):197]. JAMA. 2003;289(19):2560-2572.
16. Gottlieb DJ, Yenokyan G, Newman AB, et al. Prospective study of obstructive sleep apnea and incident coronary heart disease and heart failure: the sleep heart health study. Circulation. 2010;122(4):352-360.
17. Horstmann S, Hess CW, Bassetti C, Gugger M, Mathis J. Sleepiness- related accidents in sleep apnea patients. Sleep. 2000;23(3): 383-389.
18. Indications and standards for cardiopulmonary sleep studies. American Thoracic Society. Medical Section of the American Lung Association. Am Rev Respir Dis. 1989;139(2):559-568.
19. Practice parameters for the use of portable recording in the assessment of obstructive sleep apnea. Standards of Practice Committee of the American Sleep Disorders Association. Sleep. 1994;17(4):372-377.
20. Practice parameters for the indications for polysomnography and related procedures. Polysomnography Task Force, American Sleep Disorders Association Standards of Practice Committee. Sleep. 1997;20(6):406-422.
21. Calleja JM, Esnaola S, Rubio R, Duran J. Comparison of a cardiorespiratory device versus polysomnography for diagnosis of sleep apnoea. Eur Respir J. 2002;20(6):1505-1510.
22. Redline S, Tosteson T, Boucher MA, Millman RP. Measurement of sleep-related breathing disturbances in epidemiologic studies. Assessment of the validity and reproducibility of a portable monitoring device. Chest. 1991;100(5):1281-1286.
23. Montserrat JM, Alarcón A, Lloberes P, Ballester E, Fornas C, Rodriguez- Roisin R. Adequacy of prescribing nasal continuous positive airway pressure therapy for the sleep apnoea/hypopnoea syndrome on the basis of night time respiratory recording variables. Thorax. 1995;50(9):969-971.
24. Chediak AD. Why CMS approved home sleep testing for CPAP coverage. J Clin Sleep Med. 2008;4(1):16-18.
25. National Institute of Health and Clinical Excellence. Continuous Positive Airway Pressure for the Treatment of Obstructive Sleep Apnoea/Hypopnoea Syndrome. Issue date: March 2008. Review date: November 2010. NICE technology appraisal guidance 139. http://www.nice.org.uk/nicemedia/pdf/TA139Guidance.pdf. Accessed April 15, 2011.
26. Kapur V, Blough DK, Sandblom RE, et al. The medical cost of undiagnosed sleep apnea. Sleep. 1999;22(6):749-755.
27. Ronald J, Delaive K, Roos L, Manfreda J, Bahammam A, Kryger MH. Health care utilization in the 10 years prior to diagnosis in obstructive sleep apnea syndrome patients. Sleep. 1999;22(2):225-229.
28. Kushida CA, Littner MR, Hirshkowitz M, et al; American Academy of Sleep Medicine. Practice parameters for the use of continuous and bilevel positive airway pressure devices to treat adult patients with sleep-related breathing disorders. Sleep. 2006;29(3):375-380.
29. Peker Y, Hedner J, Johansson A, Bende M. Reduced hospitalization with cardiovascular and pulmonary disease in obstructive sleep apnea patients on nasal CPAP treatment. Sleep. 1997;20(8):645-653.
30. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613-619.
31. Babu AR, Herdegen J, Fogelfeld L, Shott S, Mazzone T. Type 2 diabetes, glycemic control, and continuous positive airway pressure in obstructive sleep apnea. Arch Intern Med. 2005;165(4):447-452.
32. Goncalves MA, Guilleminault C, Ramos E, Palha A, Paiva T. Erectile dysfunction, obstructive sleep apnea syndrome and nasal CPAP treatment. Sleep Med. 2005;6(4):333-339.
33. Centers for Disease Control and Prevention. Chronic Diseases. The Power to Prevent, The Call to Control: At A Glance 2009. http://www.cdc.gov/chronicdisease/resources/publications/AAG/chronic.htm. Accessed July 2, 2011.
34. Engleman HM, Martin SE, Douglas NJ. Compliance with CPAP therapy in patients with the sleep apnoea/hypopnoea syndrome. Thorax. 1994;49(3):263-266.
35. Hoy CJ, Vennelle M, Kingshott RN, Engleman HM, Douglas NJ. Can intensive support improve continuous positive airway pressure use in patients with the sleep apnea/hypopnea syndrome? Am J Respir Crit Care Med. 1999;159(4, pt 1):1096-1100.
36. Cramer JA. A systematic review of adherence with medications for diabetes. Diabetes Care. 2004;27(5):1218-1224.
37. Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care. 2005;43(6):521-530.
38. Tan H, Cai Q, Agarwal S, Stephenson JJ, Kamat S. Impact of adherence to disease-modifying therapies on clinical and economic outcomes among patients with multiple sclerosis. Adv Ther. 2011;28(1): 51-61.
39. Pittman DG, Chen W, Bowlin SJ, Foody JM. Adherence to statins, subsequent healthcare costs, and cardiovascular hospitalizations. Am J Cardiol. 2011;107(11):1662-1666.
40. Chervin RD, Theut S, Bassetti C, Aldrich MS. Compliance with nasal CPAP can be improved by simple interventions. Sleep. 1997;20(4): 284-289.
41. Stepnowsky CJ Jr, Bardwell WA, Moore PJ, Ancoli-Israel S, Dimsdale JE. Psychologic correlates of compliance with continuous positive airway pressure. Sleep. 2002;25(7):758-762.
42. Massie CA, Hart RW, Peralez K, Richards GN. Effects of humidification on nasal symptoms and compliance in sleep apnea patients using continuous positive airway pressure. Chest. 1999;116(2):403-408.
43. Pepin JL, Krieger J, Rodenstein D, et al. Effective compliance during the first 3 months of continuous positive airway pressure: a European prospective study of 121 patients. Am J Respir Crit Care Med. 1999;160(4):1124-1129.
44. Sin DD, Mayers I, Man GC, Pawluk L. Long-term compliance rates to continuous positive airway pressure in obstructive sleep apnea: a population-based study. Chest. 2002;121(2):430-435.
45. Bahammam A, Delaive K, Ronald J, Manfreda J, Roos L, Kryger MH. Health care utilization in males with obstructive sleep apnea syndrome two years after diagnosis and treatment. Sleep. 1999;22(6): 740-747.
46. Bahammam AS, Tate R, Manfreda J, Kryger MH. Upper airway resistance syndrome: effect of nasal dilation, sleep stage, and sleep position. Sleep. 1999;22:592-598.