LEVERAGING PREDICTIVE ANALYTICS WITHIN SOCIAL NETWORKS TO MAXIMIZE DRUG ANDALCOHOL TREATMENT EFFICACY AND RELAPSE PREVENTION

PROJECT SUMMARY/ABSTRACT Sober Grid™ has developed a smartphone-based mobile application currently in use by over 120,000 individuals worldwide who are in, or seeking, recovery from drug and alcohol addiction. The “Grid”, as it is known, is a mobile-based, social recovery community providing rapid context- specific peer support, efficient help seeking, motivational enhancement exercises, and member ratings of support content – all aimed to prevent relapse. The overarching goal of this phase II project is to extend the current capabilities of the Sober Grid app to achieve a comprehensive social recovery support app featuring intelligent, context appropriate resource matching and 24/7 rapid response peer-coaching that is effective in reducing disordered substance use and is cost effective. We hypothesize that providing this functionality to high-risk members will be acceptable, feasible, increase access to and engagement with resources, and have a positive effect in increasing time to relapse and days of consecutive abstinence. The company’s priority commercial goal is to leverage the insights gained from its large database of information and behaviors recorded in its existing addiction recovery-focused social network, combined with its recently completed SBIR phase I work, to identify users at risk for relapse and deliver tailored lay and professional peer support, telehealth, and provider interventions prompted by near real-time automated risk indicators built into an Enhanced Sober Grid (ESG) solution. The specific goals of this proposed phase II project include: (1) implementing the relapse risk scoring algorithm successfully developed in phase I in a production environment, (2) developing a ML resource relevancy matching algorithm, and (3) using this system to pilot test the feasibility and acceptability as well as to estimate the effect on abstinence of providing peer-coaching and resource information to a national sample of Sober Grid members in recovery from non- alcohol/nicotine substances who are predicted to be at high risk for relapse. We will accomplish our objectives by: (Aim 1) Implementing an accurate, near real-time production risk prediction system; (Aim 2) Developing an enhanced, in-app substance-addiction recovery resource locator; and, (Aim 3) Determining the feasibility, acceptability and estimating the effect size of the proposed ESG among high relapse-risk participants in recovery from opioid, stimulant, or cannabis use. The expected impact of this project is to substantially enhance Sober Gridandapos;s ability to deliver effective and timely interventions to the right individuals, at the right time – including those high-need and underserved populations that would otherwise lack access to care and draw considerable resources from the healthcare system. This capability holds the promise to reduce drug and alcohol relapse and the associated negative health impacts at both an individual and societal level while reducing the total cost of providing treatment services.PROJECT NARRATIVE Sober Grid is combining near real-time risk prediction with automated phone-app messaging, peer-coaching, and resource visibility and transparency in order to dramatically improve support for recovery from substance abuse. The strategy is to provide continuously available responsive connection and support with simple and familiar ways to search, filter, sort, identify, and review/rate resource options in order to lower overall relapse rates within the population, enabling Sober Grid users to achieve improved health outcomes and institutional payers to reduce the total cost of achieving those outcomes. Over time, the innovations resulting from this project will significantly reduce costs for individuals, public and private payers, the healthcare system, and society at large.