Key takeaways:
- The risk adjustment landscape is undergoing dynamic change as reimbursement policy, oversight, and technology continue to evolve.
- Clinical documentation and encounters integrity play an outsized role in supporting traceable, evidence-based HCC submissions.
- Leading managed care organizations are experimenting with AI and advanced data structures to improve payment accuracy and cost of care visibility.
- An effective risk adjustment program requires coordinated capabilities across member and provider engagement, data and technology, core operations, and adjacent functions (e.g., care management, quality).
Understand the opportunities to strengthen accuracy, compliance, and member care
Risk adjustment, along with reinsurance and risk corridors, was designed to stabilize health plan participation and account for the health complexity of enrolled populations. Originally introduced by the Centers for Medicare and Medicaid Services (CMS) for Medicare Advantage, risk adjustment now extends to Affordable Care Act (Exchange) plans and select states with Managed Medicaid, all with the goal of aligning payments more closely with the expected cost of care.
But the perception has shifted. Regulators and the public increasingly view risk adjustment as a revenue-driven activity and a focal point for potential non-compliance under the False Claims Act.
For regulators, payers, and providers, having an effective, contemporary risk adjustment capability is critical to economic sustainability in today's market. While advancements continue to be made, including how organizations capture and interpret the relationship between risk and health outcomes, staying ahead of changes in reimbursement and regulation is a must.
The changing risk landscape for payers and providers
Risk adjustment is in a period of rapid, visible change. CMS-HCC risk model v28 is now fully implemented. Risk adjustment data validation (RADV) oversight has been revamped in both schedule and methodology. The 2027 Rate Announcement goes further, excluding diagnoses from unlinked chart review records and audio-only telehealth encounters from risk score calculations. These rules reinforce the expectation that risk-adjustable diagnoses should be tied to documented, face-to-face clinical services.
Layer on top of that the advancements in data interoperability, predictive analytics, and AI, and it’s clear: the way organizations identify, document, and submit risk is being fundamentally reshaped.
The result? Greater regulatory and media scrutiny of coding practices, in-home assessments, and audit outcomes. For payers and providers, it’s time to reassess long-standing approaches and capabilities to meet heightened standards for accuracy, transparency, and affordability.
For all stakeholders, having an effective, contemporary risk adjustment capability is critical to economic sustainability in today's world.
The opportunities in risk adjustment
Leading organizations are no longer treating risk adjustment as a back-office function. They’re reimagining it as a strategic capability that drives clinician and member engagement, improves cost of care visibility, and delivers greater insight into health plan member health.
Are you ready to adapt?
Risk-bearing organizations that strategically embed AI into their risk adjustment programs will be best positioned. Here are some key considerations to take your program to the next level.
- How are you applying AI agents to mature core activities to accelerate outcomes?
- How confident are you in the signals from predictive models and natural language processing to raise suspecting conditions that inform a member’s potential cost of care?
- How are you evaluating the expectations and needs of specific provider types in your network to tailor AI-enabled workflows and engagement strategies?
- How well does your organization understand the impact of upstream processes and systems on the integrity of the data feeding your AI and analytics models?
- How regularly does your organization assess the accuracy of AI-generated insights and reconcile their impact on encounter submissions and risk adjustment factor score projections?
Key components of an effective risk adjustment program
An effective risk adjustment program (RAF) integrates clinical accuracy, sound analytics, and operational discipline. Successful programs typically span three core areas: prospective operations, retrospective (chart) operations, and the data and technology foundation that supports both.
Prospective operations
Prospective operations focus on engaging members and providers to document conditions accurately and in accordance with regulatory requirements at the point of care.
Retrospective (chart) operations
Retrospective operations involve acquiring and reconciling member clinical charts, claims data, suspecting analytics, and documentation guidelines to assess whether risk-adjustable conditions submitted for payment are valid and accurate.
The risk adjustment foundation
The effectiveness of both prospective and retrospective operations depends on a reliable data and analytics foundation. Data used for risk adjustment should be clinically valid, actuarially sound, and traceable from source to submission.
PwC helps organizations across the risk adjustment lifecycle, from strategy and analytics to operational execution, provider enablement, payment reconciliation, and audit preparation.
Raffy Salcedo, Manager, PwC US and Ruchira Parikh, Senior Associate, PwC US also contributed to this article.
