Digital Device ID Targeting for Increasing Medications for Opioid Use Disorder: A Feasibility and Acceptability Study

以数字设备 ID 为目标增加阿片类药物使用障碍药物治疗：可行性和可接受性研究

• 批准号: 10288555
• 负责人: Sean Young
• 金额: $ 27.48万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10288555
• 关键词: AIDS/HIV problem; Address; Adopted; Advertisements; Automobile Driving; Big Data; COVID-19; COVID-19 pandemic; Caring; Centers for Disease Control and Prevention (U.S.); Collection; Common Data Element; Communication; Communities; Consent; Continuity of Patient Care; Data; Data Set; Devices; Enrollment; Ethics; European Union; FDA approved; Facebook; Feasibility Studies; Future; Geography; Global Positioning System; HIV; HIV risk; Health; Health Insurance Portability and Accountability Act; Helping to End Addiction Long-term; Individual; Industry; Infrastructure; Intervention; Interview; Laws; Learning; Location; Maps; Marketing; Mental Depression; Mental Health; Methods; Morbidity - disease rate; Movement; Neighborhoods; Outcome; Outcome Measure; Overdose; Participant; Patients; Pharmaceutical Preparations; Pharmacologic Substance; Prevention; Privacy; Problem Solving; Process; Research; Research Personnel; Risk Behaviors; Structure; Surveys; Target Populations; Technology; United States; United States National Institutes of Health; Visit; Visualization; Vulnerable Populations; acceptability and feasibility; comorbidity; data de-identification; data infrastructure; design; digital; follow-up; handheld mobile device; healing; high risk; impaired driving performance; implementation science; improved; innovation; insight; interest; mortality; novel; novel strategies; opioid use disorder; outreach; participant enrollment; prescription opioid; prevent; preventive intervention; recruit; substance use; substance use prevention; success; tool

Abstract There is a critical need to improve identification and sustained treatment of patients with opioid use disorder (OUD) to prevent drug overdose, comorbid substance use, impaired driving, and HIV/AIDS. This application seeks to study a novel way to solve that problem by adopting and applying a cutting-edge approach being used to increase consumer identification and engagement by top technology and marketing companies. This approach, called device ID targeting, has recently been replacing other digital communication outreach methods largely for privacy reasons-- to conform to stringent European Union privacy laws-- as it involves de- identified data. Device ID targeting is already being applied in health (but not yet OUD) settings. During the COVID-19 pandemic, our team and others (including the CDC) have already studied and found initial success applying these methods for targeted digital recruitment and outreach to those at high-risk for COVID-19. As a result of the COVID-19 pandemic and its effect on use of digital/remote tools, these approaches will soon be applied to OUD to assist in methods for identification, surveillance, and intervention among individuals with OUD. Importantly, device ID targeting allows access to large-scale neighborhood and mobility (GPS pings) data, which may add rich and granular data to improve OUD surveillance and interventions. This application seeks to study the feasibility and acceptability of using device ID targeting to increase identification and retention among participants with OUD who are not taking medications for opioid use disorder (MOUD), including studying participants' ethical questions with this approach. Specifically, we seek to 1) develop the infrastructure needed for a big data mapping tool that visualizes the relationship between longitudinal MOUD engagement and mobility data collected from device ID targeting, 2) explore the feasibility of using device ID targeting to identify and retain OUD patients, not on MOUD, and 3) explore the acceptability of using device ID targeting to identify and retain OUD patients, not in care. This study will collect pilot survey data with common data elements with the HEALing Communities and other HEAL Initiative studies, in order to converge with the outcome measures from the HEAL initiative and provide highly granular geographic/GPS movement data that can drive insights to improve delivery of MOUD interventions. The feasibility, acceptability, and novel digital data collected, will provide our team and other researchers with important data on whether and how to use device ID outreach approaches to improve the timing, location, and tailoring of digital OUD outreach interventions. This research will be the first to explore this novel and potentially highly impactful approach.

抽象的 迫切需要改善对阿片类药物使用的患者的识别和持续治疗 可防止药物过量，合并药物使用，驾驶受损和艾滋病毒/艾滋病的疾病（OUD）。这 应用程序旨在通过采用和应用尖端方法来研究一种新的方法来解决该问题 用于增加顶级技术和营销公司的消费者识别和参与度。 这种称为设备ID定位的方法最近正在取代其他数字通信外展 方法主要是出于隐私原因 - 符合严格的欧盟隐私法 - 因为它涉及 确定的数据。 设备ID定位已经在健康（但尚未）设置中应用。在19日期间 大流行，我们的团队和其他人（包括CDC）已经研究并发现了最初的成功应用 这些方法是针对性数字招聘和与高风险的Covid-19的方法。后果 COVID-19大流行及其对数字/远程工具使用的影响，这些方法将很快应用于 OUD协助有OUD的个体进行识别，监视和干预的方法。 重要的是，设备ID定位允许访问大型邻域和移动性（GPS PINGS）数据， 这可能会增加丰富和颗粒状的数据以改善OUD监视和干预措施。本申请寻求 研究使用设备ID靶向来增加识别和保留的可行性和可接受性 没有服用阿片类药物使用障碍药物（MOUD）的OUD的参与者，包括学习 参与者通过这种方法的道德问题。具体来说，我们寻求1）开发所需的基础架构 对于大数据映射工具，可视化纵向MOUD参与与 从设备ID目标收集的移动性数据，2）探索使用设备ID定位的可行性 并保留OUD患者，而不是在MOUD上，以及3）探索使用设备ID定位的可接受性 并保留OUD患者，而不是在护理中。 这项研究将收集与康复社区的常见数据元素一起收集试点调查数据， 其他Heal倡议研究，以融合Heal Heal Initiative和 提供高度颗粒状的地理/GPS运动数据，可以推动见解以改善MOUD的交付 干预措施。收集的可行性，可接受性和新颖的数字数据将为我们的团队和其他 具有重要数据的研究人员，有关是否以及如何使用设备ID外展方法来改进 数字OUD外展干预措施的时机，位置和裁缝。这项研究将是第一个探索这一研究的 新颖且潜在的高度影响力。