An integrated health-economic analysis of diagnostic and therapeutic strategies in the treatment of moderate-to-severe obstructive sleep apnea

Abstract

Study objectives: Obstructive sleep apnea (OSA) is a common disorder associated with substantially increased cardiovascular risks, reduced quality of life, and increased risk of motor vehicle collisions due to daytime sleepiness. This study evaluates the cost-effectiveness of three commonly used diagnostic strategies (full-night polysomnography, split-night polysomnography, unattended portable home-monitoring) in conjunction with continuous positive airway pressure (CPAP) therapy in patients with moderate-to-severe OSA.

Design: A Markov model was created to compare costs and effectiveness of different diagnostic and therapeutic strategies over a 10-year interval and the expected lifetime of the patient. The primary measure of cost-effectiveness was incremental cost per quality-adjusted life year (QALY) gained.

Patients or participants: Baseline computations were performed for a hypothetical average cohort of 50-year-old males with a 50% pretest probability of having moderate-to-severe OSA (apnea-hypopnea index [AHI] ≥ 15 events per hour).

Measurements and results: For a patient with moderate-to-severe OSA, CPAP therapy has an incremental cost-effectiveness ratio (ICER) of $15,915 per QALY gained for the lifetime horizon. Over the lifetime horizon in a population with 50% prevalence of OSA, full-night polysomnography in conjunction with CPAP therapy is the most economically efficient strategy at any willingness-to-pay greater than $17,131 per-QALY gained because it dominates all other strategies in comparative analysis.

Conclusions: Full-night polysomnography (PSG) is cost-effective and is the preferred diagnostic strategy for adults suspected to have moderate-to-severe OSA when all diagnostic options are available. Split-night PSG and unattended home monitoring can be considered cost-effective alternatives when full-night PSG is not available.

Keywords: Markov model; Sleep apnea; comparative effectiveness; continuous positive airway pressure; health-economics; obstructive.

Figure 1

Simplified illustration of the decision tree structure (diagnosis and titration only). The small square represents the decision to implement a strategy of using a specific diagnostic technology. Circles represent chance events. FN-PSG, Full-night polysomnography; SN-PSG, Split-night polysomnography; UPHM, Unattended Home Monitoring; TN, True Negative; FN, False Negative; TP, True Positive; FP, False Positive.

Figure 2

Schematic of the Markov component of the model. Patients are initially distributed based on their diagnosis. Each month, patients can either die, stay in the existing state, or transition into one of the other health states as indicated by the arrows.

Figure 3

Expected life-years, quality-adjusted life years, lifetime risk of MI, stroke, and death from motor vehicle crash (MVC), and expected lifetime number of MVC, varying CPAP therapy compliance (50-year-old male cohort).

Figure 4

Incremental cost-effectiveness of different diagnostic strategies for 3 different levels of OSA prevalence (pretest probability) (50-year-old male cohort).