Using Artificial Intelligence To Monitor Medication Adherence in Opioid Replacement Therapy

This study uses an artificial intelligence platform to automatically confirm medication ingestion. The Health Insurance Portability and Accountability Act (HIPAA)-compliant platform can be downloaded as an 'app' onto any smartphone to automate directly observed therapy (Automated DOT®). Real-time patient adherence data are encrypted and automatically sent to a centralized web-based dashboard for use by healthcare professionals or research staff. Unlike Facetime® or Skype®, the system relies on computer vision algorithms to confirm the process of medication administration; no human review is necessary. The purpose of this study is to evaluate the feasibility and acceptability, and measure the accuracy, of the AiCure platform ("platform") in patients being treated for opioid dependence with Zubsolv® over the course of 12 weeks. The following aims will be tested: 1) to assess the feasibility and acceptability to both participants and study staff in using AiCure to monitor medication adherence; 2) to evaluate the acceptability of using AiCure to optimize care pathways; and 3) to measure the reliability and validity of AiCure in detecting interruptions in treatment. To assess feasibility and acceptability of the platform, we will measure rates of physician satisfaction and user acceptance. Optimization of care pathways will be measured by assessing the sustainability of AiCure use over 12 weeks (retention rates) and measuring illicit opioid use (urine drug screens) compared to historical data. Reliability and validity of AiCure will be measured by comparing AiCure adherence against pharmacokinetic data. All participants will be requested to take each of their prescribed doses using the app. Participants will be able to download the app onto their own smartphone or will be provisioned a device at the start of the study. The data captured during the medication ingestion process will be automatically encrypted and stored on the participant smartphone and uploaded wireless