patients with sleep disorders (Banno and Kryger, 2004; Tachibana et al., 2005). In many health care systems and communities, waiting lists may be as long as 10 weeks (Rodsutti et al., 2004), with even longer waiting times in certain systems such as Veterans Affairs Medical Centers (Sharafkhaneh et al., 2004). Although this is not a problem that is unique to the field, long wait lists cause significant delays in diagnosing and treating individuals (Banno and Kryger, 2004). This is of particular concern for individuals with sleep disorders that lead to increased chance of injury. For example, undiagnosed severe OSA can lead to death or serious harm of self or others due to crashes (George, 2001). Further, long wait times contribute to high no-show rates that in turn increases the length of the wait-lists (Callahan and Redmon, 1987; Olivares, 1990). This also may decrease market share (Christl, 1973; Antle and Reid, 1988). It has been estimated that sleep apnea alone, a diagnosis that necessitates polysomnography to meet current criteria set out by third-party payers, annually requires at least 2,310 polysomnograms per 100,000 population to address the demand for diagnosis and treatment (Flemons et al., 2004). However, on average, only 427 polysomnograms per 100,000 population are performed each year in the United States, a level far below the need. In fact, 32 states annually perform less than 500 polysomnograms (Tachibana et al., 2005). Only Maryland annually performs more than 1,000. This large geographic variability in levels of sleep services is not explained by Medicare reimbursement rates, race, or distribution of OSA risk factors in these areas (Tachibana et al., 2005). Further, such geographical variability suggests the need for more standardized approaches for diagnosis and disease management.
Limitations in providing overnight diagnostic sleep laboratory services are attributed to a number of factors. Direct costs associated with having a polysomnogram performed (Chapter 4) are high. In addition, there are high expenses to sleep laboratories, including costs related to the initial investment in equipment (hardware and software) and information technology needed to manage large amounts of digital data. There are considerable personnel costs related to dedicating one to two trained technicians to each patient for a 10- to 12-hour period (for orientation, hookup, and minute-by-minute monitoring) and for scoring of studies (2 to 3 hours per study), overhead for space (which traditionally has used in-patient hospital space and more recently has used space in upscale hotels that contract with health care organizations to provide rooms or floors that serve as “community-based sleep laboratories”), and costs related to consumable supplies used for monitoring. Most insurers require sleep laboratories to be supervised by physicians or other clinicians certified by the American Academy of Sleep Medicine. In addition, many patients are reluctant to undergo somewhat intrusive monitoring and to spend one or more nights away from home. The latter is of special concern to individuals with home care (of their chil-