Provider Types and Outcomes in Obstructive Sleep Apnea Case Finding and Treatment

Obstructive sleep apnea (OSA) is associated with excessive daytime sleepiness, decreased quality of life, myocardial infarction (1, 2), heart failure (3), stroke (4, 5), and cognitive decline (6, 7). Continuous positive airway pressure (CPAP) improves quality of life and symptoms among persons with OSA and excessive daytime sleepiness (8). Although CPAP has not been shown in randomized trials to reduce myocardial infarctions, stroke, or death (912) among patients with OSA, it decreases blood pressure and is associated with reduced risk for motor vehicle accidents (13). As patients and providers gain awareness of OSA, and as prevalence of obesity (a major risk factor for OSA) increases (14), health care systems need to develop strategies to address the increasing demand for sleep services. The traditional evaluation and care model relies on primary care providers to refer patients with suspected OSA to a sleep specialist physician (SSP). The process often includes consultation, in-laboratory diagnostic polysomnography (PSG), CPAP initiation and titration PSG for persons with OSA, and SSP follow-up of treatment adherence and efficacy. This traditional model may be expensive and inefficient. New OSA care models have been proposed and implemented, including home sleep testing for diagnostic purposes (15, 16), followed by treatment with an autotitrating CPAP device (17), which has internal algorithms that adjust pressure to keep the airway open during sleep. These models reduce PSG-associated costs and logistical barriers but typically still include SSP consultation and follow-up. Given recent data indicating a decreasing supply of SSPs (18), other models have been proposed that would reduce reliance on SSPs by including providers not specifically trained as SSPs (nonsleep specialists [NSSs]), such as nurses or primary care physicians, to provide the majority of OSA diagnosis and treatment. Although studies testing some of these new models have been conducted, systematic reviews of studies focusing on who should deliver care are lacking. In this article, we expand on 1 aspect of a larger evidence report conducted for the Department of Veterans Affairs Evidence-based Synthesis Program (protocol registered in PROSPERO [CRD42016036810]) (19) by assessing the comparative effectiveness and harms of new OSA evaluation and treatment models comparing different provider types. Specifically, we evaluated case finding and care by NSSs versus SSPs for patients with suspected or diagnosed OSA. Methods Data Sources and Searches We searched Ovid MEDLINE and CINAHL for articles published from January 2000 through July 2017. Our search was limited to studies that enrolled adults and were published in English. The search for studies of NSSs versus SSPs included the Medical Subject Headings terms sleep apnea syndromes; sleep apnea, obstructive; and health personnel (Appendix Table 1). We obtained additional articles by hand-searching reference lists of relevant studies. Appendix Table 1. Search Strategies Study Selection Abstracts and full-text reports were independently reviewed by 2 trained investigators and research associates. Full-text reports of studies identified as potentially eligible after abstract review were obtained for further review. We included randomized or controlled clinical trials and observational studies that reported results in adults with suspected or diagnosed OSA and were conducted in geographic settings likely to have similar populations and sleep medicine resources (United States, Canada, Europe, Australia, and New Zealand). We adopted a broad definition of care models but required that the study include a comparison of providers with different qualifications (for example, primary care physician vs. SSP). We did not include studies that compared home sleep testing with sleep laboratory testing if all test results were interpreted by SSPs. We excluded studies evaluating the role of dentists or anesthesiologists and studies in which the goal of the intervention was not OSA care. We also excluded studies if they did not report our outcomes of interest or were dissertations, conference abstracts, case reports, narrative reviews, editorials, or commentaries. Reasons for exclusion of a study at full-text review were noted, and disagreements were resolved by a third reviewer. Data Abstraction and Quality Assessment Study characteristics and outcomes were extracted by one investigator and verified by a second. Our outcomes of interest included patient-centered outcomes (mortality, access to care, quality of life, patient satisfaction, adherence, symptom scores, and adverse events) and intermediate or resource-related outcomes (resource use, costs, time to initiation of treatment, and case finding). Two trained investigators rated the risk of bias of individual studies over all outcomes as low, medium, or high. For randomized controlled trials (RCTs), we based risk-of-bias ratings on the following criteria: allocation sequence generation, allocation concealment, blinding, incomplete outcome data, and selective outcome reporting (20). For observational studies, we rated risk of bias using criteria from the Agency for Healthcare Research and Quality Methods Guide (21). We assessed strength of evidence as high, moderate, low, or insufficient, based on the following domains: study limitations (low, moderate, or high, based on the quality or risk of bias of individual studies), consistency (consistent, inconsistent, or unknown or not applicable), directness (direct or indirect), and precision (precise or imprecise) (22). Strength of evidence was rated by one methodologist and verified by a second. Discrepancies were resolved by discussion. Data Synthesis and Analysis We described and qualitatively compared findings of included studies. Analyses were performed in Comprehensive Meta-Analysis, version 3 (Biostat), using random-effects models to calculate mean differences with corresponding 95% CIs. Role of the Funding Source The Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Quality Enhancement Research Initiative assigned the topic and reviewed the original protocol but was not involved in data collection, analysis, or manuscript preparation or submission. Results Search results are shown in Figure 1. Our search identified 12 studies that were eligible for inclusion. Figure 1. Evidence search and selection. * An additional 23 studies on autotitrating positive airway pressure vs. continuous positive airway pressure were included in the full evidence report only. Case Finding in Adults With Suspected OSA We identified 4 observational studies on case finding in adults with suspected OSA (2326). Study characteristics are summarized in Appendix Table 2, with additional information provided in Supplement Table 1. Two studies received government funding, 1 received both government and respiratory society funding, and 1 did not report a funding source. Each study took a different approach to case finding. Two were rated as having high risk of bias (23, 25), and 2 were rated as having medium risk of bias (24, 26). Although populations, interventions, comparators, and settings differed across studies, outcomes were similar and results suggested good agreement between SSPs and NSSs (Supplement Tables 2 and 3). Supplement. Supplementary Material Appendix Table 2. Summary of Study Characteristics In a single-site study in the United States, a nurse practitioner experienced in sleep medicine and supervised by an SSP reviewed electronic health records of patients referred for evaluation of OSA (23). The goal was risk stratification and determination of eligibility for an unattended sleep study. If information from the health records was inadequate, a clinic visit with an SSP was scheduled. The health record review (nurse practitioner evaluation) found adequate information for 115 patients, whereas 90 had a clinic visit (SSP evaluation). A community-based study in the United States included 191 patients with at least 4 hours of interpretable recording time from a portable sleep monitoring device (24). The classification of disease severity that was based on the ApneaHypopnea Index value generated by the monitoring device software was compared with the classification that was based on an independent review of the monitoring device output by a board-certified SSP. In the third study, conducted in Spain, 88 patients with suspected OSA were evaluated by 2 providers: a respiratory physician who was trained in sleep medicine and used results from respiratory polygraphy, and an SSP who used results from PSG (26). Both evaluations took place within 1 month. Each of these studies reported on classification of OSA severity (none to severe). Two reported coefficients of 0.75 (24) and 0.71 (26), indicating good agreement. The third study only reported that the final diagnoses of severity did not statistically significantly differ between groups (23). We found low-strength evidence that classification of OSA severity was similar (Table 1). One of the studies also reported agreement on the ApneaHypopnea Index (<10, 10 to 29, or 30 events per hour), with a coefficient of 0.65 (26). Table 1. Strength of Evidence The fourth study, also done in Spain, compared the ability of a primary care pulmonologist (described as having basic knowledge of sleep medicine) and an SSP to identify the most suitable diagnostic test for individual patients (25). Ninety-six patients were included. A coefficient of 0.74 was reported for agreement on the diagnostic test prescribed. No studies assessed patient satisfaction with care, but 1 study evaluated patient-reported clinical improvement (23). The percentage who perceived clinical improvement at 30-day follow-up was similar (P= 0.76) among patients who were evaluated by chart review and those who required a clinic visit. Many of our other outcomes of interest were not r