Predictive Analytics and Peer-Driven Intervention for Guideline-based Care for Sleep Apnea

Obstructive sleep apnea (OSA) is a prevalent condition that affects 7 to 12% of the US population and is characterized by repetitive collapse of the upper airway during sleep. Continuous positive airway pressure (CPAP) has been shown to be highly effective in the treatment of OSA, however, adherence is poor with up to 54% of patients being non-adherent to CPAP therapy by Medicare criteria, which has been attributed to inadequate patient education and support for CPAP therapy. Poor treatment adherence in patients with OSA can lead to adverse health consequences, poor quality of life, and patient dissatisfaction. Poor treatment adherence may be due to lack of sufficient patient education, time delays in delivery of care, lack of adequate healthcare coordination, or difficulty accessing various healthcare providers across a front desk which serves as a "healthcare bottle-neck". Better efficiency in healthcare delivery, with greater connectivity through knowledgeable and trained peer volunteers and cheap cell-phones integrated by a smart telephone exchange may alleviate some of the care and communication burden faced by the healthcare system. Specifically, such community health education volunteers ("peer-buddies") who are experienced in managing their OSA may be able to impart knowledge and confidence to a recently diagnosed patient in a much more personalized manner than that of a group therapy session.