SOAR: Smartphones for Opioid Addiction Recovery

SOAR：用于阿片类药物成瘾康复的智能手机

• 批准号: 10652500
• 负责人: PAUL W GLIMCHER
• 金额: $ 101.12万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 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/10652500
• 关键词: Algorithms; American; Basic Science; Buprenorphine; Cellular Phone; Clinical; Clinical Trials; Clinical Trials Network; Conduct Clinical Trials; Contracts; Cost Analysis; Cost Measures; Criminal Justice; Data; Data Analyses; Dose; Dropout; Effectiveness; Event; Eye; Feasibility Studies; Future; Goals; Health; Health Care Costs; Health Care Sector; Health Personnel; 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; Policy Maker; 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; behavior prediction; buprenorphine treatment; cohort; cost; cost effective; cost effectiveness; cost-effectiveness evaluation; drug testing; economic evaluation; illicit opioid; improved; inner city; instrument; methadone treatment; migration; opioid misuse; opioid use; opioid use disorder; prediction algorithm; response; safety net; stakeholder perspectives; tool; treatment as usual; usability; user-friendly; willingness

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.

项目概要 超过 200 万美国人患有阿片类药物使用障碍 (OUD)，另有 900 万人滥用阿片类药物。 存在阿片类药物成瘾的治疗方法，但当受试者在治疗期间使用非法阿片类药物时，疗效会受到影响 治疗。治疗期间的重复使用率可能很高，因此减少治疗期间非法阿片类药物的使用 最近成为 NIDA 的一项主要政策目标。重复使用率的提高不仅会影响处理效果， 但这种行为预示着，并且可能导致治疗中断。在NIDA基础科学R01的支持下， 我们开发了一套易于使用的仪器，可以预测阿片类药物的重复使用事件，其准确度约为 任何现有的工具。我们开发的 5 分钟电池可指示患者重复使用的数字概率 在接下来的 7-10 天内使用非法阿片类药物。在试点队列中，我们成功地将这种电池迁移到商业 智能手机平台，并展示了 100% 的保留率和 >85% 的合规性（中位合规性 > 95%） 使用期限长达4个月。在对大部分无家可归的 MOUD 患者进行的一项调查中，我们发现 85% 的患者已经 拥有适合使用该平台作为治疗一部分的智能手机和数据合同。在一项调查中 的 OUD 治疗医生，我们发现我们的系统及其提供的重用预测都非常好 实施后是理想且可用的。最后，我们在对 CTN-0051 数据的重新分析中发现，动态 这种剂量可以降低复发率。我们在这个中型临床试验中的主要目标是测试 假设临床医生使用我们移动系统的输出来调整丁丙诺啡和美沙酮 与照常提供护理的医生相比，阿片类药物的重复使用率较低。我们的次要目标是 检查该解决方案对临床医生的可用性和可取性，着眼于可用性和大规模 部署。我们的第三个也是最后一个目标是从多个方面衡量该解决方案的成本效益 观点。如果我们成功了，就有可能采用基于算法和测量的方法 使用美沙酮和丁丙诺啡进行 OUD 治疗，可降低重复使用率和复发率 OUD 患者。