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

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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.