Intelligent Mid-Revenue Cycle
Unifying Medical Necessity & Revenue Integrity
Experience Dragonfly at The HFMA Annual Conference
Dragonfly gives health system leaders real-time, AI-powered insight into patient acuity and level of care- so your teams make more defensible decisions, reduce denials, and move patients through the right level of care with confidence. See it live at the HFMA Annual Conference.

Speaking Session
AI-Powered Mid-Revenue Cycle Optimization:
Enhancing Data-Driven Decisions and Financial Integrity
- Tuesday, June 9
- 3:00 pm ET
- Maryland A: Rooms 1-3
This session cuts through the AI hype to explore how health systems can responsibly leverage AI, advanced analytics, and data-driven insights to modernize revenue cycle operations and drive measurable financial and clinical outcomes.
Attendees will gain practical strategies for implementing AI-powered solutions across utilization review, denial prevention, and revenue integrity to improve efficiency, strengthen payer relationships, and reduce avoidable denials.
strategies for Implementing AI-driven Solutions to Improve Revenue Integrity and Clinical Efficiency
Sarah Knodel
Senior Vice President, Revenue Cycle, Baylor Scott and White Health
Michelle Greame
AVP of Revenue Integrity, Inova Health System
Kathleen Quill Noyes
Senior Director of Revenue Cycle, Summit Healthcare Regional Medical Center
Sharon Kelley
Founder & Principal, Kelley Advisory Group
Xsolis Booth Activities – Booth #255
Connect with Xsolis to discover how Together We Are Redefining Healthcare.
Xsolis is the trusted leader in mid-revenue cycle intelligence, chosen by hospitals and health systems for over a decade. Your strategic partner for transformation, Xsolis delivers a proven platform powered by insights and enabled by 13+ years of responsible AI experience.
Our advanced intelligence through Dragonfly provides immediate, objective validation of patient acuity to accelerate medical necessity decisions, optimize Length of Stay (LOS), and proactively minimize financial exposure for both provider and payer.
