The introduction of the TEAM (Transforming Episode Accountability Model) Mandate signals more than just a policy update—it’s a structural overhaul of how risk is measured, reported, and reimbursed in value-based care.For risk-bearing organizations and hospital systems, the implications are vast. From redefining diagnosis clusters to enhancing the role of encounter-level validation, TEAM is poised to reshape the DNA of risk adjustment models.
Let’s explore how this mandate changes the game—and how healthcare leaders can stay ahead of the curve.

TEAM Mandate – A Catalyst for Risk Model Evolution

The TEAM Mandate isn't an isolated policy. It’s part of CMS’s broader shift toward data-rich, episode-based reimbursement models. Unlike traditional risk adjustment frameworks that used retrospective data, TEAM pushes for proactive, real-time risk scoring.

Key Shifts Introduced by TEAM:

• From beneficiary-centric to episode-centric risk capture

• From historical lookbacks to encounter-specific validation

• From periodic HCC submissions to continuous risk tracking

• From general attribution to condition-based episode bundling

Implications for Risk Adjustment Models

Here’s a step-by-step playbook:

• 1. Reweighted HCC Scoring Algorithms
  HCC codes are reprioritized based on clinical severity, episode context, and SDoH relevance
  Chronic conditions are scored differently based on frequency and timing within an episode
• 2. Dynamic Risk Windows
  Risk scoring is no longer tied to annual submission cycles
  TEAM mandates rolling episodes with real-time risk evaluation
• 3. Increased Weight on Social Determinants
  New CMS risk models incorporate factors like housing insecurity, food access, and caregiver support
  Organizations must integrate SDoH data into their risk pipelines
• 4. Narrower Risk Attribution
  Risk is now attributed at the condition-specific bundle level
  Attribution errors could result in missed reimbursements or duplicate penalties

Strategic Impacts on Payers, Providers, and ACOs

Stakeholder	Impact Area	Action Needed
Hospitals	Revenue Forecasting	Revise actuarial models with TEAM logic
Payers	Risk Stratification	Build real-time data sync with provider EHRs
ACOs	Attribution Models	Redefine care management around bundle boundaries
RCM Teams	Claims Review	Implement predictive risk analytics at point-of-service
Compliance Officers	Audit Preparedness	Strengthen documentation audits for encounter-level validation

The TEAM-Driven Future of Risk Capture

TEAM transforms risk adjustment from a compliance requirement into a strategic asset. The mandate compels systems to:

• Adopt AI-driven risk engines that can update risk profiles in real time

• Align clinical workflows with bundle-specific documentation protocols

• Capture non-traditional data streams like patient-reported outcomes and SDoH indicators

• Train physicians on documentation strategies that meet TEAM logic

SolvEdge Insight – Leading the Shift to Dynamic Risk Adjustment

SolvEdge’s analytics and compliance platforms are built for TEAM-readiness. Our solutions support:

• Intelligent, encounter-aware risk scoring aligned with TEAM algorithms

• Seamless integration with EHR systems to extract real-time clinical inputs

• Embedded SDoH mapping for a complete patient risk profile

• Predictive risk trending for revenue forecasting and compliance checks

Preparing for the Future: Action Plan for Risk Model Leaders

Here’s a strategic roadmap to prepare your organization:

• Run a Gap Analysis of Current Risk Models vs. TEAM Parameters

• Upgrade Data Pipelines to Enable Real-Time Risk Capture

• ntegrate SDoH and PRO Data into Your Risk Algorithms

• Collaborate Across Finance, Compliance, and Clinical Teams

• Adopt Predictive Risk Scoring Tools with TEAM Logic Built-In

From Compliance to Competitive Strategy

The TEAM Mandate doesn’t just raise the bar on compliance—it shifts how risk is defined, attributed, and monetized. For healthcare leaders, this is a chance to evolve from reactive coding to proactive risk leadership. The winners in this new landscape will be those who embrace real-time, data-rich, episode-aware risk modeling—and who move quickly to operationalize it.