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

基本信息

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
项目类别：
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

项目摘要

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.

抽象的迫切需要改进对阿片类药物使用患者的识别和持续治疗疾病（OUD），以预防药物过量、共病药物使用、驾驶不便和艾滋病毒/艾滋病。这应用程序旨在通过采用和应用尖端方法来研究解决该问题的新方法顶级技术和营销公司用于提高消费者识别度和参与度。这种称为设备 ID 定位的方法最近已取代其他数字通信推广方法主要是出于隐私原因——遵守严格的欧盟隐私法——因为它涉及到识别的数据。设备 ID 定位已应用于健康（但尚未 OUD）设置。在新冠肺炎 (COVID-19) 疫情期间大流行期间，我们的团队和其他人（包括疾病预防控制中心）已经研究并取得了初步成功这些方法可用于有针对性的数字招聘和向 COVID-19 高危人群进行外展。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 协助制定 OUD 患者的识别、监测和干预方法。重要的是，设备 ID 定位允许访问大规模社区和移动性 (GPS ping) 数据，这可以添加丰富且精细的数据来改进 OUD 监测和干预。该应用程序旨在研究使用设备 ID 定位来提高识别率和保留率的可行性和可接受性患有 OUD 且未服用阿片类药物使用障碍 (MOUD) 药物的参与者，包括学习参与者通过这种方法提出的道德问题。具体来说，我们寻求 1) 开发所需的基础设施用于可视化纵向 MOUD 参与度和从设备 ID 定位收集的移动数据，2) 探索使用设备 ID 定位来识别的可行性并保留 OUD 患者，而不是 MOUD，以及 3) 探索使用设备 ID 定位来识别患者的可接受性并保留 OUD 患者，而不是接受护理。本研究将收集具有与 HEALing 社区相同的数据元素的试点调查数据，其他 HEAL 倡议研究，以便与 HEAL 倡议的成果衡量标准相一致，提供高度精细的地理/GPS 移动数据，可推动洞察以改进 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人员提供帮助研究人员拥有关于是否以及如何使用设备 ID 推广方法来改善数字 OUD 外展干预措施的时间、地点和定制。这项研究将是第一个探索这一问题的研究新颖且可能具有高度影响力的方法。