Remotely Observed Methadone Evaluation (ROME)

远程观察美沙酮评估 (ROME)

• 批准号: 10483876
• 负责人: Steffani R Bailey
• 金额: $ 26.79万
• 依托单位: SONARA HEALTH INC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10483876
• 关键词: Accountability; Address; Adherence; Affect; American; Bar Codes; Buprenorphine; Caring; Centers for Disease Control and Prevention (U.S.); Certification; Clinic; Clinic Visits; Communicable Diseases; Complex; Computer software; Consumption; Data; Detection; Dose; Ecological momentary assessment; Educational Background; Emergency department visit; Evaluation; Event; FDA approved; Face; Feedback; Future; Geography; Greek; HIV/HCV; Harm Reduction; Health Care Sector; Health Sciences; Health Services Accessibility; Healthcare; Home; Hospitalization; Hospitals; Hour; Image; Incidence; Individual; Interview; Label; Licensing; Location; Machine Learning; Measures; Methadone; Methods; Naltrexone; Needle Sharing; Neonatal Abstinence Syndrome; Opiate Addiction; Opioid; Oregon; Overdose; Patient Care; Patients; Performance; Persons; Pharmaceutical Preparations; Phase; Physicians; Positioning Attribute; Prevention; Privacy; Productivity; Provider; Quality of Care; Regimen; Regulation; Relapse; Research; Resources; Rural; Rural Community; Safety; Savings; Small Business Innovation Research Grant; Societies; Testing; Time; Training; Travel; United States; Universities; Vial device; Video Recording; Visit; authority; automated algorithm; barrier to care; chronic pain patient; clinical decision-making; commercial application; commercialization; cost; design; effective therapy; efficacy evaluation; feasibility testing; illicit drug use; improved; indicated prevention; insight; machine learning algorithm; methadone treatment; mortality; opioid treatment program; opioid use disorder; opioid user; overdose death; overdose risk; prescription opioid; product development; rural area; sensor; social; socioeconomics; telehealth; usability; web app; webinar; willingness

Abstract – Three million Americans and 16 million individuals worldwide have had or currently suffer from opioid use disorder (OUD). OUD afflicts individuals from all socioeconomic and educational backgrounds with devastating consequences, including a rising incidence of neonatal abstinence syndrome and the spread of infectious diseases, i.e., HIV and hepatitis C, associated with syringe sharing. The most recent provisional data from the Centers for Disease Control and Prevention (CDC) indicate that approximately 81,230 drug overdose deaths occurred in the United States in the 12 months leading up to May 2020—the largest annual number of drug overdoses ever recorded. In 2019, hospitals estimated an annual cost of OUD of $787B to society, $93B to taxpayers, and $89B to the healthcare sector. Medications for opioid use disorder (e.g., methadone, buprenorphine, or naltrexone) are central to the treatment of OUD. Methadone, a proven and effective opioid medication for treating OUD, extends retention in care, reduces mortality, and inhibits illicit drug use. However, methadone treatment is limited to federally certified Opioid Treatment Programs (OTPs), which must meet complex regulatory requirements for certification. The regulations require new patients to take their dose in person six days per week and limit the locations where patients may receive methadone. Finding an OTP can be challenging, especially for those in rural areas as only 3% of OTPs are rurally located. The greatest barriers that keep individuals with OUD from receiving treatment include 1) Availability; 2) Accessibility (i.e., daily visits for directly observed dosing); 3) Acceptability (i.e., need for detox for other non-methadone treatment options); and 4) Privacy. To address these barriers, Elpidatec has developed Elpida, an OTP-specific, mobile- and desktop-friendly web-application that combines video, tamper-evident barcode labels, facial recognition, and machine learning (ML) to enable accelerated take-home methadone regimens while maintaining safety and diversion prevention. Elpida enhances patient access to treatment, aligns with OTP workflow, and improves physician assessment and management of OUD patients, providing previously inaccessible patient information via real-time, ecological momentary assessments (EMAs). In this project, Elpidatec will complete feasibility testing, iterative product development, and market fit testing of Elpida in partnership with Adapt Oregon, a rural OTP, and Oregon Health and Science University. The Phase I SBIR application has three aims: 1) Conduct feasibility testing of the minimum viable product (MVP) with patient- and clinician-facing web- applications and evaluate tracking performance; 2) Develop and integrate key ML-enhanced features such as facial recognition and methadone vial position tracking for automated dosing event interpretation; and 3) Assess the demand and acceptability of Elpida among providers and patients. Insights gathered in Phase I will inform actionable improvements and the design of EMA constructs to be executed in Phase II. In Phase II, Elpidatec will also examine efficacy measures (e.g., treatment retention, relapse rates) via larger scale testing.

摘要-- 300万美国人和全球1600万人曾经或目前患有阿片类药物使用 疾病（OUD）。OUD折磨着来自所有社会经济和教育背景的人， 后果，包括新生儿禁欲综合症发病率上升和传染性疾病的传播， 疾病，即，艾滋病毒和丙型肝炎，与共用注射器有关。最新的临时数据来自 疾病控制和预防中心（CDC）表示，大约有81，230例药物过量死亡 在2020年5月之前的12个月里，美国发生了最大的年度毒品数量 有史以来最严重的吸毒过量2019年，医院估计OUD每年给社会带来的成本为7870亿美元， 纳税人，以及890亿美元的医疗保健部门。阿片类药物使用障碍的药物（例如，美沙酮， 丁丙诺啡或纳洛酮）是治疗OUD的核心。美沙酮，一种被证明有效的阿片类药物 治疗OUD的药物，延长护理保留期，降低死亡率，并抑制非法药物使用。然而，在这方面， 美沙酮治疗仅限于联邦认证的阿片类药物治疗计划（OTP），必须符合 复杂的认证法规要求。该规定要求新的病人服用他们的剂量 此外，当局亦会限制美沙酮的使用时间，包括每星期六天，以及限制病人接受美沙酮的地点。找到OTP可以 这是一个挑战，特别是对农村地区的人来说，因为只有3%的OTP位于农村。的最大障碍 使患有OUD的个体不能接受治疗的因素包括1）可获得性; 2）可获得性（即，日访问量 对于直接观察的剂量）; 3）可接受性（即，其他非美沙酮治疗方案的戒毒需要）; （4）隐私。为了解决这些障碍，Elpidatec开发了Elpida，这是一种特定于OTP的移动的， 桌面友好的网络应用程序，结合了视频，防篡改条形码标签，面部识别， 和机器学习（ML），以实现加速带回家的美沙酮方案，同时保持 安全和预防转移。尔必达增强了患者获得治疗的机会，与OTP工作流程保持一致， 改善了医生对OUD患者的评估和管理， 通过实时生态瞬时评估（EMAs）获取信息。在这个项目中，Elpidatec将完成 与Adapt合作进行可行性测试、迭代产品开发和市场适应性测试 俄勒冈州，一个农村OTP，和俄勒冈州健康与科学大学。第一阶段SBIR应用程序有三个目标： 1)通过面向患者和临床医生的网络对最小可行产品（MVP）进行可行性测试， 应用程序和评估跟踪性能; 2）开发和集成关键的ML增强功能，例如 面部识别和美沙酮小瓶位置跟踪，用于自动化给药事件解释;以及3）评估 提供者和患者对尔必达的需求和可接受性。在第一阶段收集的见解将告知 可操作的改进和EMA结构的设计将在第二阶段执行。在第二阶段，Elpidatec 还将检查功效测量（例如，治疗保留率、复发率）。