Abstract

Partnership pairs Siftwell’s AI-powered population health analytics with Sober Sidekick’s relapse prevention platform to help Medicaid managed care plans identify and reduce high-cost, relapse-driven utilization.

Author: Siftwell and Sober Sidekick

Sober Sidekick, the peer recovery support platform operated by Empathy Health Technologies, Inc., and Siftwell Analytics, the AI-powered population health analytics company serving community-oriented health plans, today announced a non-exclusive market collaboration designed to help Medicaid managed care organizations identify and reduce wasted high-cost spending and relapse-driven utilization among members with substance use disorder (SUD).

Under the collaboration, Siftwell’s applied analytics platform will surface the data insights managed care plans need to identify members at risk of costly, avoidable utilization, while Sober Sidekick’s relapse prevention platform delivers the direct member-facing intervention that addresses the relapse events driving that spending. Together, the two companies aim to give payers a combined data-to-intervention pathway: identify who is at risk, and act on it. As part of their joint market engagement, Sober Sidekick and Siftwell plan to give health plans a direct look at how the two solutions work together to quantify avoidable SUD-related costs, target the right members, and generate meaningful savings for plan partners.

“Sober Sidekick’s approach immediately stood out to me,” said Trey Sutten, CEO and co-founder of Siftwell. “Insight only matters when it changes what happens next for a member, and our platforms solve two halves of the same problem for the health plans we both serve. Siftwell tells plans where the risk and opportunity is, and Sober Sidekick gives them a way to act on it directly with members. Bringing that combination to Association for Community Affiliated Plans (ACAP) member plans is a natural next step.”

“Managed care plans are under constant pressure to reduce avoidable cost while improving outcomes for their most vulnerable members, and relapse-driven utilization is one of the largest, least-addressed drivers of that spend,” said Chris Thompson, CEO of Empathy Health Technologies and Sober Sidekick. “Pairing our platform with Siftwell’s analytics gives plans a much clearer line from insight to intervention, and we’re looking forward to showing that to payers together at ACAP.”

The two companies plan to continue building out the collaboration following ACAP, including joint go-to-market activity with shared managed care and Medicaid plan targets.

About Sober Sidekick

Sober Sidekick is a peer recovery support platform operated by Empathy Health Technologies, Inc., which also operates Empathy Health Solutions PC, a licensed telehealth clinical entity. Sober Sidekick has been downloaded more than 1.4 million times and supports over 100,000 monthly active members. Independent analysis by Charm Economics and the Validation Institute has found the platform associated with a 48.2% reduction in relapse and $4,442 in per-member-per-year (PMPY) savings, with a 2.19x total cost of care (TCOC) multiplier reported by ASPE/HHS. Learn more at sobersidekick.com.

About Siftwell Analytics

Founded in 2022 by managed care veterans, Siftwell Analytics is an AI-powered predictive analytics platform built for community health plans and managed care organizations. Siftwell combines a plan’s internal data with external clinical, social, and environmental signals, then applies explainable, advanced analytics to tell frontline teams who to reach, why, and what to do. That intelligence powers four priorities for health plans: population health and cost of care, care quality and gap closure, growth and retention, and readiness for H.R. 1, the federal Medicaid reforms taking effect in 2027. Siftwell is headquartered in Charlotte, North Carolina. Learn more at siftwell.ai.

Media Contacts

Jeff Goe
Chief Growth Officer, Empathy Health Technologies, Inc.
jeff@sobersidekick.com

Madi Ballou
Director of Marketing, Siftwell
madi@siftwell.ai