Description

Healthcare reimbursement is undergoing a fundamental shift as payment models move from fee-for-service toward value-based care. In this session, Danielle McDermott Bagnell explains how this transformation changes the role of documentation, coding, and data integrity across the healthcare ecosystem. Attendees will learn how clinical documentation improvement (CDI) supports risk adjustment and how Hierarchical Condition Categories (HCCs) translate clinical documentation into risk scores that influence reimbursement, quality reporting, and population health management. The webinar begins with a clear comparison of fee-for-service and value-based care models and explains why accurate documentation and diagnosis coding are essential as healthcare organizations increasingly tie reimbursement to patient complexity, outcomes, and total cost of care.

The session also explores the expanding responsibilities of CDI programs in value-based environments, including supporting compliant ICD-10-CM documentation, improving chronic condition continuity of care, and strengthening risk adjustment accuracy. Participants will gain insight into how documentation and coded data drive care coordination, population health programs, quality performance, and payer payment models. Through practical examples and discussion of CDI workflows such as prospective reviews, concurrent documentation improvement, and analytics-driven audits, attendees will better understand how compliant documentation and coding form the foundation for accurate risk adjustment and sustainable value-based care strategies.
 

Learning Objectives/Agenda:

• Explain the differences between fee-for-service reimbursement and value-based care models and why healthcare payment is shifting toward value-based arrangements.
• Describe how clinical documentation improvement (CDI) supports accurate diagnosis coding, risk adjustment, and value-based reimbursement.
• Identify how Hierarchical Condition Categories (HCCs) translate documented diagnoses into risk scores used in programs such as Medicare Advantage and other value-based payment models.
• Review key documentation requirements needed to support compliant HCC reporting, including clinical support, MEAT criteria, and ICD-10-CM coding guideline considerations.
• Discuss how documentation and coded data influence quality measurement, population health management, care coordination, and payer reimbursement strategies in value-based care.
• Examine how CDI workflows such as prospective reviews, concurrent documentation improvement, and retrospective audits help improve documentation accuracy and reduce compliance risk.
• Understand the regulatory and audit environment surrounding risk adjustment, including RADV audits, OIG oversight, and False Claims Act risk related to documentation and coding practices.
   

Why is this topic timely/important?

As healthcare reimbursement continues shifting toward value-based care, accurate clinical documentation and diagnosis coding have become essential to capturing patient complexity and supporting fair reimbursement. Risk adjustment models such as HCCs rely on clear, compliant documentation to translate clinical care into data that drives payment, quality performance, and population health strategies. Understanding the connection between CDI, coding, and value-based payment is critical for healthcare professionals navigating evolving payment models and increasing regulatory oversight.
 

Who would benefit from this topic?

• Medical coders and risk adjustment coders seeking to strengthen their understanding of HCC capture and documentation support in value-based care models.
• Clinical documentation improvement (CDI) specialists responsible for ensuring documentation accurately reflects patient complexity and supports compliant coding.
• Auditors and compliance professionals involved in validating diagnosis coding, clinical support, and risk adjustment data accuracy.
• Healthcare administrators and value-based care leaders working to understand how documentation and coding data influence reimbursement, quality performance, and population health initiatives.
• Providers and clinical staff who document patient care and want to better understand how their documentation affects risk scores, quality reporting, and payment models.
• Health information management (HIM) professionals and data analysts responsible for evaluating documentation quality, coding accuracy, and risk adjustment performance.