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Winning under CMS TEAM: Building the learning health system to realize success in VBC today and tomorrow

by Kayla Grieme, Benjamin Goldsteen and Shankara Ettigi

  • The mandatory CMS TEAM program requires over 700 hospitals to manage the total cost and quality of five high-volume surgical episodes. Success requires moving past retrospective reporting to enable proactive, data-driven intervention.
  • Many providers lack a unified, AI-enabled data foundation, making it difficult to establish a single source of truth across clinical and claims data and to embed predictive insights into care workflows.
  • Implementing these value-based care capabilities drives significant financial and quality outcomes, guided by value-based care experts. Health systems can realize typical results, including a 15% reduction in SNF costs and a 12% reduction in readmissions.

Starting January 1, 2026, over 700 hospitals across the United States faced a new reality in value-based care. The Centers for Medicare and Medicaid Services (CMS) Transforming Episode Accountability Model (TEAM) mandated select organizations manage total cost and quality across five high-volume surgical episodes, from admission through 30 days post-discharge.

The financial stakes are substantial: analysis of data released by the American College of Surgeons shows that top-performing health systems could capture $4M-$30M annually in shared savings, while unprepared organizations risk $10M+ in repayments over the program's five-year term.

Yet here's the challenge most hospitals aren't ready to face: traditional analytics infrastructure cannot support proactive clinical decision-making that TEAM demands nor does it adequately prepare them for eventual down-side risk (mandatory for most participants starting in year 2). Success requires moving beyond monthly dashboards and quarterly reviews to a foundation of data intelligence that enables intervention before episodes begin to exceed cost targets.

Understanding TEAM's Data Complexity

TEAM represents a significant milestone in advancing CMS’ bundles programs by focusing on higher-cost specialty episodes of care. While Complete Joint Replacement (CJR) and Bundled Payments for Care Improvement (BPCI) Advanced typically focused on a few procedure types, TEAM mandates bundled payments for surgical procedures across five episode categories: 

  • Lower Extremity Joint Replacement
  • Coronary Artery Bypass Graft (CABG)
  • Surgical Hip and Femur Fracture Treatment
  • Spinal Fusion
  • Major Bowel Procedures

Each episode creates a 30-day accountability window extending across multiple care settings, from the operating room to skilled nursing facilities (SNF), home health agencies, and outpatient follow-up.

This complexity creates unprecedented data integration challenges. Hospitals must simultaneously track hospital EHR data, claims covering Part A and Part B services, post-acute care data across SNFs and home health, social determinants impacting costs and quality, and provider performance metrics across hundreds of surgeons and specialists.

The traditional approach of waiting 6-9 months for claims to run out means hospitals only discover their performance after it's too late to intervene. Industry data underscores the urgency: two-thirds of hospitals will lose revenue under TEAM based on current spending patterns, with individual episodes varying from $3,000 gains to $5,500 losses per case. The difference between winners and losers isn't volume, it's the operational capabilities enabled by intelligent data foundations.

The Modern Data Architecture for TEAM

Building the Intelligent Data Foundation

Health systems succeeding in value-contracting models like TEAM share common data infrastructure characteristics:

  • Unified Data Platform: A single source of truth integrating clinical, claims, and operational data across the enterprise and unaffiliated community health providers. Rather than maintaining separate data marts for quality, finance, and operations, leading organizations consolidate onto cloud-native data lakehouse architectures that support both structured and unstructured data at scale.
  • AI/ML Integration: Predictive models continuously learning from outcomes to improve risk stratification, intervention recommendations, and complication prediction. These models must be operationalized and deployed into production (with monitoring and retraining) rather than one-off experiments.
  • Embedded Workflows: Clinical insights delivered within existing tools rather than standalone portals. Whether through EHR integration, discharge planning systems, or care coordination platforms (portals), intelligence must meet users in their daily workflows.
  • Scalable Architecture: Infrastructure that can handle expanding episode categories as CMS extends TEAM. Building on modern cloud platforms ensures systems can scale without infrastructure rewrites.

The Critical Capabilities Matrix Enabled by Modern Data Architecture

Once a foundational data integration infrastructure is in place, health systems will need to consider implementing data-driven capabilities that enable proactive episode management:

Clinical

Next Best Action Decision Support

Proactive Care Gap Closure

Patient Deterioration Alerts

Operational

Advanced Risk Capture and Stratification

Site of Care Planning

 

Coordinated Post-Acute Care Pathways

Program Management

High-Value Provider Network Intelligence

Ongoing QI/PI Opportunity Identification

Predictive Performance Gap Alerts

Next Best Action Decision Support

Clinicians will face hundreds of daily decisions impacting episode utilization and quality. Intelligent decision support must deliver personalized recommendations at the point of care, identifying clinical or socioeconomic risk factors for complications and suggesting specific interventions to realize the best outcomes for the patient. This requires integrating clinical and community data into machine learning models that continuously learn from outcomes that can be embedded directly into clinical workflows through EHR integration, not as separate reports clinicians must seek out.

Coordinated Post-Acute Care Pathways

Post-acute care represents the largest spending driver outside hospital walls, with SNF and home health costs varying by 300-400% for clinically similar patients. Proactive monitoring and outreach are necessary to continuously update SNF performance benchmarking, discharge planning decision support that shows cost and quality data, post-discharge monitoring with readmission risk alerts, and bi-directional data exchange that enables PAC partners to see episode cost status.

High-Value Provider Network Intelligence

Variation in clinician partner performance directly impacts episode costs and quality. Systems must provide continuously updated provider-level analytics, peer benchmarking capabilities enabling clinician teams to compare performance, best practice identification features showing specific process differences between top and bottom performers, and referral pattern optimization. This requires complex attribution logic accounting for case mix and patient risk, with automated provider scorecards refreshing with each completed episode.

Real-World Impact: From Data to Dollars

To understand the financial impact TEAMs new episode bundles could have on your system, consider a composite example drawn from health systems we've supported in bundle programs:

A 500-bed academic medical center with approximately 725 TEAM episodes annually implemented a modern data foundation over six months, consolidating EHR, claims, and PAC data into a unified cloud platform with up-to-date episode dashboards, predictive models flagging high-risk episodes at admission, next best action recommendations integrated into discharge workflows, and SNF scorecards updated weekly.

The results reflected typical patterns from effective bundle management: 

  • 15% reduction in SNF costs through data-driven discharge planning, 
  • 8% improvement in risk capture completeness through automated alerts, and
  • 12% reduction in readmissions via predictive models that identify at-risk patients, resulting in a significant positive financial impact compared with baseline projections.

Key metrics driving success included:

  • episode cost trends versus spend targets updated daily
  • quality composite score performance with gap closure rates
  • provider-level benchmarking across surgeons, 
  • high-risk episode identification with intervention success rates,
  • PAC facility performance tracking.

Getting Started: Your Action Plan

Immediate Actions (Next 30-60 Days)

  • Establish Governance
    • Who is the executive sponsor?
    • How will success be measured beyond financial reconciliation?
    • How will initiatives be approved and recommendations be approved (e.g. Track selection)?
    • How will Governance oversee, mitigate, and intervene when outcomes or initiatives underperform?
  • Establish Program Management
    • How will patient cohorts be defined and measured?
    • How will initiative implementations be tracked?
    • How will initiative benefits be measured?
    • How will outcomes for cohorts and initiative impact be reported?
    • How can Program Management identify and mitigate performance and outcomes risks early?

Build Cross-Functional Teams: TEAM success requires collaboration across clinical leadership, IT, finance, and analytics (traditionally independent domains). Appropriate representation is needed from each at the governance level and, often, within initiatives to successfully design and implement value programs.

Assess Current State:

  • Can you identify all active TEAM episodes prior to when a patient presents to the OR?
  • Do you know what’s driving your hospital’s overall spend above target and/or why individual physicians’ cases beat targets while others exceed targets?
  • Can clinicians access episode data in their workflows?
  • Do you have predictive models identifying high-risk episodes? If you answered "no" to any of these, you have critical gaps impacting financial performance right now.

Prioritize Use Cases:

Based on industry benchmarking, start with risk capture (highest ROI, fastest implementation), post-acute care optimization (largest cost driver), and next best action decision support (enables all other capabilities to scale). These three typically deliver 60-70% of achievable savings in Year 1. How does your health system’s utilization and outcomes in these areas compare to the highest-performing health systems?

Strategic Investments

Long-term success requires modern cloud data infrastructure (legacy systems can't deliver the required scalability), continuous integration capabilities (replacing nightly batch jobs with event-driven architectures), advanced analytics and AI/ML tools (beyond spreadsheets and BI dashboards), and change management for clinical adoption (technology alone doesn't drive results without clinician engagement).

The Partnership Approach

Winning organizations leverage partnerships: technology partners providing modern data platform infrastructure, domain experts bringing TEAM-specific analytics and proven interventions, and clinical champions driving physician engagement from within. The key is ensuring these partners work as an integrated team rather than siloed workstreams.

The Path Forward

TEAM represents both significant opportunity and substantial risk. The difference between success and failure won't be determined by hospital size or historical market position, it will be determined by the data foundations you build and the capabilities it delivers, no matter where you are on your TEAM journey. 

Organizations still relying on retrospective reporting are discovering through early 2026 episodes that traditional approaches cannot compete. Meanwhile, health systems that invested in intelligent data infrastructure are already identifying high-risk episodes, optimizing discharge decisions, proactively closing quality gaps, and capturing shared savings.

Perhaps most importantly, the capabilities required for TEAM success extend far beyond this single program. These investments position your organization to future-proof your data estate and empower data-driven decisions.  TEAM is not just a payment model—it is a forcing function for building a Learning Health System. Organizations that invest now are not only positioning for success under TEAM, but creating the foundation for continuous performance improvement across their entire enterprise.

Databricks and a team of value-based care expert partners have developed a comprehensive TEAM Risk Readiness Assessment for participants at any stage of their TEAM journey. The assessment evaluates your current capabilities across data integration, analytics maturity, clinical workflows, and financial performance tracking. Organizations completing this assessment gain immediate clarity on where to focus resources and how to prioritize investments for maximum impact while minimizing downside risk.

Connect with the team at Strategic APM Collaborative to schedule an assessment or request more information.

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