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.
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:
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.
Health systems succeeding in value-contracting models like TEAM share common data infrastructure characteristics:
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 |
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.
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.
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.
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:
Key metrics driving success included:
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.
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?
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).
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.
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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