Phare UM

Sessions & takeaways

Recordings and the key takeaways from each session.

Wednesday, Oct 21

Home Game Advantage: Phare UM

Led by Mark & Jen

Master the UM story: customer problem, value proposition, differentiation and proof

Key takeaways

  • Connected and proactive UM model: Phare UM combines clinical judgment, workflow orchestration, human experts and payer intelligence, and learns from every case.
  • The competitive advantage: R1's differentiated approach to AI-driven UM:
    • Technology plus clinical experts versus technology first
    • Clinical, financial and payer data versus clinical data only
    • Payer-specific versus payer-agnostic
    • Recommendations combine clinical judgment with denial likelihood
  • Utilization management sees both sides of the risk: Phare Intelligence shows what the record supports, and Payer Atlas shows where the payer might push back. Clinical appropriateness alone doesn't remove denial risk.
  • Remember going forward: Phare UM runs InterQual or MCG based on payer preference, backed by 20+ years of UM experience. Results: 40% fewer UR reviews at 98% accuracy and 50% shorter peer-to-peer calls.
Wednesday, Oct 21

Film Room: UM Pitch Dissection

Led by Liza & Melissa

Watch and break down a UM pitch—what to land, how to tell the story and the moves worth borrowing

Key takeaways

  • This session evaluated an actual client conversation and highlighted repeatable sales plays.
  • UM is not embedded in Epic, but it's fully two-way. Results write back to Epic, and Epic's blueprint would block auto-resolution.
  • Once triggered, it returns a status recommendation within 4 minutes of a bed request, as long as a physician note and sufficient clinical documentation exist.
  • Anchor on three metrics: efficiency, compliant observation-to-inpatient conversion, and fewer medical necessity denials.
  • Use the ROI calculator for estimates only; it doesn't set pricing. Approximately $31/discharge for technology-only and $79/discharge for technology + full services, noting pricing is still being refined.