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SOAR: Smartphones for Opioid Addiction Recovery

SOAR：用于阿片类药物成瘾康复的智能手机

基本信息

批准号：
10468772
负责人：
PAUL W GLIMCHER
金额：
$ 101.09万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-15 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10468772
关键词：
Algorithms American Basic Science Behavior Buprenorphine Caring Cellular Phone Clinical Clinical Trials Clinical Trials Network Conduct Clinical Trials Contracts Cost Measures Criminal Justice Data Data Analyses Dose Dropout Economics Effectiveness Event Eye Feasibility Studies Future Goals Health Care Costs Health Care Sector Health Personnel Health Policy Homelessness Hospitals Intervention Measurement Measures Methadone Methodology National Institute of Drug Abuse Nurses Opiate Addiction Opioid Outcome Output Patients Pharmaceutical Preparations Physicians Pilot Projects Policies Population Probability Productivity Professional counselor Provider Psychiatry Publishing Quality-Adjusted Life Years Randomized Recovery Relapse Resources Salivary Site Societies Surveys System Testing Time Treatment Effectiveness arm base buprenorphine treatment cohort cost cost effective cost effectiveness cost-effectiveness evaluation drug testing economic evaluation illicit opioid improved inner city instrument methadone treatment opioid misuse opioid use opioid use disorder prediction algorithm response safety net stakeholder perspectives tool treatment as usual usability user-friendly willingness

项目摘要

PROJECT SUMMARY Over 2 million Americans suffer from Opioid Use Disorder (OUD) and another 9 million misuse opioids. Treatments for opioid addiction exist, but effectiveness is compromised when subjects use illicit opiates during treatment. Reuse rates during treatment can be high, and reducing illicit opiate use during treatment has thus recently become a major NIDA policy goal. Elevated reuse rates not only compromise treatment effectiveness, but this behavior predicts, and likely drives, treatment dropout. With the support of a NIDA basic science R01, we developed a set of easy-to-use instruments that predict opioid reuse events with about twice the accuracy of any existing tool. The 5-minute battery we developed indicates the numerical probability that a patient will reuse illicit opiates within the next 7-10 days. In a pilot cohort, we successfully migrated this battery to a commercial smartphone platform, and demonstrated 100% retention and >85% compliance (median compliance > 95%) over a use period of up to 4 months. In a survey of our largely homeless MOUD patients we found that 85% already had smartphones and data contracts appropriate for using this platform as a part of their treatment. In a survey of OUD treatment physicians, we found that our system and the reuse prediction it provides, was both highly desirable and usable as implemented. Finally, we found in a reanalysis of data from CTN-0051 that dynamic dosing of this very kind reduces relapse rates. Our primary goal in this mid-scale clinical trial is to test the hypothesis that clinicians who use the output of our mobile system to adjust buprenorphine and methadone dosing achieve lower opiate reuse rates than physicians who provide care-as-usual. Our secondary goal is to examine the usability and desirability of this solution for clinicians with an eye to usability and large-scale deployment. Our third and final goal is to measure the cost-effectiveness of this solution from multiple perspectives. If we are successful it will be possible to employ an algorithmic and measurement-based approach to OUD treatment with methadone and buprenorphine which reduces reuse rates and relapse rates amongst OUD patients.

项目总结