Agenda 2025

Industry benchmarks to measure the impact of payment integrity currently don't exist, making it challenging to optimize performance and areas of opportunity. Standards are extremely complicated due to varied member populations and an inconsistent approach to calculating metrics.

In this groundbreaking panel discussion, learn how a Working Group of payer and vendor SMEs have been collaborating over the last six months to develop a standard approach to calculating savings PMPM across LOB and audit programs. This session will share standard definitions and calculations, so attendees can understand how to calculate and compare their savings PMPM.

Learning Objectives:

• Learn about standard definitions and calculations for savings PMPM that apply to any type of plan, across LOB, region, and program audit
• Understand how to develop savings PMPM metrics that are comparable to a standard industry range
• Provide feedback on the approach to ensure benchmarks are applicable to your organization
• Access resources and expert guidance to support development of benchmarks 

Diagnosis codes and modifiers aren’t just billing details—they tell the story that determines how your claims are paid. When these elements don’t align, hospitals face denials, delays, and compliance risks. This session will break down how to accurately connect coding choices with billing practices to ensure claims reflect true clinical intent, reduce audit exposure, and secure appropriate reimbursement.

Learning Objectives:

• Recognize the most common coding and modifier missteps that lead to denials and learn how to avoid them through stronger documentation and coding practices.
• Implement strategies to bridge gaps between clinical, coding, and billing teams—ensuring consistent, compliant claims that tell the right story from documentation to payment.

As AI use rapidly expands across health plan operations, understanding how these technologies will be governed is essential. In this session, experts will take a deeper dive into the current state of AI governance frameworks and the legislative landscape shaping their use. Health plan leaders will gain timely insights into what’s happening now—and what’s coming next—in AI oversight, helping them prepare their organizations for compliance, accountability, and responsible innovation.

Learning Objectives: 

• Learn how to assess, document, and monitor AI models used in claims review, fraud detection, and payment integrity to ensure they meet accountability, explainability, and compliance standards.
• Gain actionable insights into current and pending legislation on AI use in healthcare, and understand what steps your organization should take now to align with evolving regulatory expectations and avoid audit risks.

As value-based care continues to reshape payment models, many health systems struggle to balance financial performance with care quality goals. This session will offer practical strategies to use denial data, coding insights, and care coordination metrics to strengthen value-based outcomes—without sacrificing revenue. This discussion will highlight how to engage teams, optimize processes, and identify sustainable financial opportunities within value-based contracts.

Learning Objectives:

• Learn how to use denial patterns and audit insights to improve documentation, coding accuracy, and contract performance.
• Gain strategies to foster physician buy-in and leadership collaboration, finding “win-win” solutions that support both revenue integrity and value-based care success.

Hospice care is meant to support patients in their final months of life, yet inappropriate or prolonged utilization continues to raise clinical, ethical, and payment integrity concerns. This session will provide critical insights into what constitutes appropriate hospice enrollment, how to identify red flags for overutilization, and strategies hospitals and health plans can use to ensure hospice services align with medical necessity.

Learning Objectives:

• Understand the clinical criteria for appropriate hospice enrollment and identify common patterns of misuse that may lead to unnecessary costs and compliance risks.
• Gain tools and best practices for conducting eligibility reviews, improving documentation scrutiny, and collaborating across teams to prevent improper payments while supporting appropriate patient care.

Denial management isn’t just about fighting back—it’s about understanding why denials happen and fixing the root causes upstream. This session will focus on how hospitals and health systems can use audit findings and denial data to identify coding gaps, documentation weaknesses, and process breakdowns that lead to preventable denials. Learn how to close these gaps through stronger internal collaboration across revenue cycle, coding, and clinical teams, while also using data-driven insights to foster more productive payer relationships.

Learning Objectives:

• Learn how to analyze denial patterns and audit results to uncover documentation, coding, and process issues—enabling proactive prevention rather than reactive rework.
• Discover best practices for improving internal workflows, fostering collaboration between clinical and revenue cycle teams, and ensuring that claims reflect accurate, defensible coding and clear clinical intent.

As the healthcare landscape evolves, the future of payment integrity depends on stronger, more transparent relationships between payers and providers. This session will explore how shifting from adversarial audits to aligned, data-driven collaboration can lead to more sustainable results. Using real case examples, we’ll discuss how leaders are redesigning their PI strategies to prioritize trust, accuracy, and efficiency.

RCM leaders are increasingly challenged by manual processes, fragmented systems, and staffing shortages that hinder efficiency and financial performance. This session delves into how healthcare organizations are leveraging automation and intelligent workflows to address these issues. By examining real-world scenarios, we'll explore strategies to reduce administrative burdens, enhance data accuracy, and improve overall revenue cycle operations.