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HFMA and KAHPAM logos in front of the Salinas, KS skyline

KS HFMA & KAHPAM Spring Conference

April 16, 2026
Event Location

PMMC Event Attendees

Attending the event? Let’s make it count. Book a meeting with one of our experts at the event to discover strategies that strengthen contracts, recover revenue, and drive performance. 

Talk To Our Team

Greg Kay

SVP, Revenue Strategy
See Bio
Carter Loesch, PMMC Headshot

Carter Loesch

Director, Revenue Strategy
See Bio

Presentation 1:

Topic Title: 2026 Recovery Trends & Best Practices

Speakers: Greg Kay & Carter Loesch

Course Description: Learn the latest trends in denials and underpayments, top denial codes, top underpayment issues, which analytics lead to actionable results, and best practices in recovering variances. This presentation is updated quarterly with new information and details to show your attendees the most up to date information

Course Objectives:

  • Develop an efficient denial management process by staying updated on insurance policies, addressing root causes, and using technology to automate and streamline reimbursements.
  • Optimizing staff ratios by defining roles, streamlining workflows, and balancing internal teams with outsourced vendors to maximize efficiency and impact.
  • Learn key strategies to reduce denial rates, align revenue cycle departments, and improve financial outcomes while boosting efficiency.

 

Presentation 2:

Topic Title: Data-Driven Deal Making: How Analytics Strengthens Payor Contract Negotiations

Speakers: Greg Kay & Carter Loesch

Course Description: Learn the most up to date strategies for Managed Care and Revenue Cycle to collaborate and gain better insight into payer contract performance and ultimately negotiate more favorable contracts. This presentation is packed with best practices and actionable best practices.

Course Objectives:

  • The basics of contract modeling with the data and metrics you need to have in place
  • New strategies for contract modeling driven by analytics, including real-world “what if” scenarios
  • How to model the newly published competitor rate data