The Positive Airway Pressure (PAP) therapy is the most capable therapy against Obstruction Sleep Apnea (OSA). PAP therapy prevents the narrowing and collapsing of the soft tissues of the upper airway. A patient diagnosed with OSA is expected to use their CPAP machines every night for at least more than 4h for experiencing any clinical improvement. However, for the last two decades, trials were carried out to improve compliance and understand factors impacting compliance, but there were not enough conclusive results. With the advent of big data analytic and real-time monitoring, new opportunities open up to tackle this compliance issue. This paper's significant contribution is a novel framework that blends multiple external verification and validation carried out by different healthcare stakeholders. We provide a systematic verification and validation process to push towards explainable data analytic and automatic learning processes. We also present a complete mHealth solution that includes two mobile applications. The first application is for delivering tailored interventions directly to the patients. The second application is bound to different healthcare stakeholders for the verification and validation process.