A cost-effectiveness analysis of alternative at-home or in-laboratory technologies for the diagnosis of obstructive sleep apnea syndrome

Background. Obstructive sleep apnea syndrome (OSAS) is a common disorder that affects 2% to 9% of the population. Health care policy makers have noted increased referrals for sleep studies. Objective. In this article, the authors conduct a cost-effectiveness analysis to determine the optimal technology for the diagnosis of OSAS using polysomnography (PSG) or partial sleep monitoring (PSM). Design. The target population was a hypothetical cohort of patients suspected of having OSAS. A 2-level decision tree was formulated that reflects all possible steps of OSAS diagnosis and therapy. The method represents a comprehensive strategy to determine which of the 2 systems - PSG or PSM - has cost advantages. The financial and operational aspects of OSAS diagnosis and therapy were analyzed. A sensitivity analysis was performed over all uncertain parameters (i.e., diagnostic agreement, data loss, and referral to therapy). Results. Unattended at-home sleep monitoring was the most expensive method. The combination of 1:2 PSG and attended PSM strategy was the optimal strategy with respect to financing and operations. Compared to the PSG-only strategy, this combination may lead to a 10% reduction of the annual expenditure. Conclusion. This study provides proof of concept (under a wide range of sensitivity assumptions) that the cost of sleep study techniques can be modeled. It rejects the assumption that at-home portable sleep monitoring is cost advantageous. The combination of PSG and attended PSM OSAS is the most cost-effective approach to sleep evaluation.