Project Motivate: A digital motivation and prediction platform to improve treatment retention and reduce relapse in opioid use disorder

Project Motivate：一个数字动机和预测平台，可提高治疗保留率并减少阿片类药物使用障碍的复发

• 批准号: 10013066
• 负责人: Jeremy Guttman
• 金额: $ 25.15万
• 依托单位: BIOMOTIVATE, LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10013066
• 关键词: Accidents; Algorithms; American; Applications Grants; Beds; Behavioral; Caring; Cellular Phone; Cessation of life; Chest; Clinic; Clinical; Computer Vision Systems; Computer software; Data; Data Collection; Data Reporting; Disadvantaged; Dropout; Early treatment; Emergency response; Ensure; Epidemic; Family; Feedback; Future; General Population; Goals; Health; Health Personnel; Heart Rate; Heroin; Image; Imaging technology; Individual; Inpatients; Intervention; Intuition; Machine Learning; Medical; Medical Care Costs; Methodology; Methods; Modeling; Monitor; Moods; Motion; Motivation; Municipalities; Overdose; Participant; Patient Self-Report; Patients; Pattern; Pharmaceutical Preparations; Phase; Physiologic Monitoring; Physiological; Predictive Analytics; Prescription drug overdose; Productivity; Professional counselor; Program Development; Provider; Public Health; Recording of previous events; Regulatory Pathway; Relapse; Reporting; Research; Research Personnel; Residential Treatment; Risk; Running; Sleep; Small Business Innovation Research Grant; Source; Stress; Surveys; Symptoms; System; Technology; Testing; Time; United States; Visualization software; Weather; Workplace; Wrist; base; clinical decision support; cost; cost effective; craving; dashboard; data visualization; digital; early onset; experience; heart rate variability; improved; mHealth; machine learning algorithm; meetings; member; motivational intervention; novel; novel strategies; opioid epidemic; opioid overdose; opioid use disorder; overdose death; patient engagement; personalized intervention; prediction algorithm; predictive modeling; premature; prevent; prototype; recidivism; relapse risk; response; sensor; sleep quality; tool; treatment program; user-friendly; validation studies; wearable device

PROJECT SUMMARY/ABSTRACT The opioid crisis is the deadliest drug epidemic in American history and new approaches are needed. One novel approach includes predicting likelihood of opioid use disorder (OUD) treatment retention by assessing someone’s risk of early departure from treatment. Current methods to improve treatment retention rely on providers using their intuition to identify when an individual is at risk of leaving treatment early in order to intervene, which often happens too late. Mobile health and machine learning predictive analytics offer a new opportunity to personalize OUD treatment, improve retention in OUD care, and mitigate the risk of relapse and overdose episodes. Project Motivate will combine physiological and behavioral data from disparate sources in order to predict when an individual is at risk of early departure from OUD treatment. This data will be displayed in a user-friendly manner so that providers can more effectively support patients to remain in treatment with timely intervention and responses.

项目摘要/摘要 阿片类药物危机是美国历史上最致命的药物流行，新的方法是 需要的。一种新的方法包括预测阿片使用障碍的可能性(OUD) 通过评估某人提前停止治疗的风险来保持治疗。当前 改善治疗保留率的方法依赖于提供者使用他们的直觉来识别何时 个人面临着提前离开治疗以进行干预的风险，这种情况往往发生得太晚了。 移动健康和机器学习预测分析提供了个性化的新机会 OUD治疗，改善OUD护理中的保留率，并降低复发和过量用药的风险 剧集。项目激励将结合来自完全不同的 消息来源，以便预测一个人何时有提前离开OUD治疗的风险。 这些数据将以用户友好的方式显示，以便提供商能够更有效地 及时干预和应对，支持患者继续接受治疗。