New MATRA Technology Enabling Better Information to Improve from Opioid Use Disorder

Technology
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Q2i, a provider of technology that improves patient care by enabling better information exchange between patients and their healthcare teams, today announced that its Opioid Addiction Recovery Support application (OARS) now includes an exclusive feature – MATRA – that enables healthcare teams to identify various trends in the behavior of patients who are in recovery from Opioid Use Disorder (OUD) and dynamically predict the likelihood of dropout and/or relapse throughout the continuum of care.

Q2i developed MATRA – Medication Assisted Treatment Recovery Assessment – in conjunction with psychiatrists, clinicians, and data scientists from the University of Massachusetts and Tufts University. MATRA utilizes the data that OARS generates, including patient data, and data generated by machine learning and artificial intelligence, to accurately predict how successful patients will be in their recovery from OUD. This data was previously either unavailable or problematic to obtain.

OARS comprises a healthcare team portal and a patient mobile application. It improves the success of Medication-Assisted Treatment (MAT) programs by providing real-time insight, analytics and trend analysis, and improved connection and support between healthcare teams and their patients.

The MATRA functionality within OARS evaluates each patient’s risk of program dropout and relapse, in real time, based on patient- and healthcare team-supplied data and machine data. This brings high-risk patients to the attention of the healthcare team at the earliest possible time, and enables the team to intervene as soon as possible, and ultimately improve patient outcomes.

“The MATRA/OARS solution gives us the tools we need to really understand whether relapse can be predicted,” said Dr. Katherine Fitzgerald, Primary Care Physician at a Suboxone/Recovery Clinic in Gardner, MA, who has been using OARS for over a year. “With the Q2i OARS/MATRA solution, we’ll be able to help more patients achieve a full recovery from OUD.”

“Improving recovery outcomes for OUD requires deeper insight into the patient’s challenges,” said Tony McNamara, CTO of Q2i. “Through data mining, analytics and machine learning, OARS improves a healthcare team’s ability to track patient progress while simultaneously providing quicker recognition of risk signs that cannot be discerned otherwise, enabling earlier intervention.”

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