Future‑Ready Risk Adjustment: Strategies, Technology, and Compliance for 2026 and Beyond

Breaking: Shifting Risk-Adjustment Dynamics Push Health Plans Toward Proactive Tech and Stricter Compliance for 2026

Health plans are rethinking risk-adjustment strategies as regulatory changes and audit methods tighten, prompting a move beyond customary retrospective programs. Organisations are now leaning into prospective and concurrent approaches to bolster sustainability, coding accuracy, and compliance for 2026 and beyond.

In a new episode of the RISE Radio podcast, senior leaders from Cotiviti and edifecs share actionable tactics for scaling risk-adjustment technology amid rising business and regulatory pressures. The discussion centers on improving data quality, aligning technology investments with measurable impact, and creating integrated risk-adjustment strategies that empower better patient care.

Key topics explored include ways to sharpen data accuracy, ensure investments deliver tangible results, and advance the full risk-adjustment lifecycle with increasingly elegant enablement across healthcare organizations.

The partnership between Cotiviti and Edifecs is highlighted as a driver of next-generation innovation, helping plans prepare for a landscape where prospective and concurrent risk adjustment play a growing role in success.

For those seeking a practical roadmap, a recent checklist outlines how to structure a complete risk-adjustment program with concrete actions, short- and long-term milestones, and KPIs to monitor impact.

Disclosures: This piece discusses risk adjustment strategies in the context of health-plan operations.for policy specifics, consult official sources such as the Centers for Medicare & Medicaid Services (CMS) and regulatory guidance.

spotlight: Leaders Driving Change

Leader	Role	Focus Area
Branka Sustic, M.S.	Vice President of Risk Adjustment and Quality, Cotiviti	Product leadership, client programs, and strategy to optimize revenue and mitigate risk
Summerpal Kahlon, M.D.	Chief Medical Officer, Edifecs	Clinical strategy, value-based care, and risk-adjustment policy guidance

evergreen insights: turning today’s changes into lasting value

as regulators tighten oversight, health plans should consider a three-pillar approach: (1) strengthening data quality and validity across the risk-adjustment pipeline, (2) synchronizing technology investments with policy objectives and measurable outcomes, and (3) integrating risk adjustment with broader care-management initiatives to support value-based care.This framework helps organizations stay ahead of audits, improve coding accuracy, and sustain financial performance while delivering better patient outcomes.

Practical steps include establishing governance around data sources, implementing continuous validation across prospective and concurrent processes, and tying metrics to concrete business impact. External guidance from authorities such as CMS can help align internal programs with national standards and timelines.

External reference: For a broad view of risk adjustment within Medicare and health plans, see CMS guidance and program materials at CMS.

What this means for health plans today

The evolving risk-adjustment landscape rewards plans that invest in scalable technology and proactive risk management.By combining prospective data capture, real-time coding checks, and concurrent review, organizations can reduce downstream gaps and improve reliability in reported risk scores.

Key takeaways at a glance

• Regulatory changes and new audit methods are reshaping risk-adjustment strategies.
• Prospective and concurrent approaches complement traditional retrospective programs to strengthen compliance and revenue integrity.
• Industry collaboration, notably between Cotiviti and Edifecs, is accelerating innovative risk-adjustment technology across the lifecycle.

Reader questions

• What steps is your health plan taking to integrate prospective risk adjustment in 2026?
• Which KPI will you prioritize this year to demonstrate impact on revenue and quality?

To learn more about building a comprehensive risk-adjustment program, organizations can consult industry checklists and best-practice guides that outline concrete actions and KPI targets for short- and long-term success.

Share your perspectives: How is your plan preparing for the 2026 risk-adjustment landscape? What challenges and opportunities do you see in prospective and concurrent approaches?

Disclaimer: This article provides a high-level overview of risk-adjustment strategies and does not constitute policy advice. Consult official regulatory guidance for your jurisdiction.

For further context, you can explore CMS risk-adjustment resources at CMS.

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Key Drivers Shaping Future‑Ready Risk Adjustment

• Value‑Based care Evolution – CMS’s 2025 Medicare Advantage final rule expands HCC‑based payments, pushing providers to capture clinical complexity more accurately.
• Data‑Driven Decision Making – real‑time analytics from electronic health records (EHR) and claims are now essential for identifying risk factors before year‑end.
• Regulatory Tightening – The Office of Inspector General (OIG) increased audit frequency in 2024, emphasizing documentation integrity and coding precision.
• Technology Acceleration – AI‑enabled natural language processing (NLP) and predictive modeling reduce manual chart review time by up to 70 % (HealthIT Analytics, 2025).

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Strategic Framework for 2026 and Beyond

1. Risk Capture Blueprint

• Map the patient journey to pinpoint high‑impact documentation touchpoints (admissions, discharge, chronic care visits).
• Align clinician incentives with risk‑adjusted outcomes through bundled payment contracts.

2. Integrated Data architecture

• Deploy a unified data lake that ingests EHR, claims, pharmacy, and social determinants of health (SDOH) feeds.
• Implement FHIR‑based APIs for seamless data exchange across payer‑provider ecosystems.

3. Continuous quality Monitoring

• Set up quarterly risk‑adjustment scorecards that track HCC prevalence, coding accuracy, and audit findings.
• Use control charts to detect deviations early and trigger corrective action plans.

4. Governance & Accountability

• Establish a cross‑functional risk adjustment steering commitee with representation from coding, compliance, IT, and finance.
• Define clear KPIs: HCC capture rate, audit denial rate, and average revenue cycle impact per adjustment.

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Emerging Technologies Transforming Risk Adjustment

Technology	Request	Measurable Impact
AI‑Powered NLP	Auto‑extracts diagnoses from clinical notes, flags missing HCCs.	Increases HCC capture by 12‑15 % (Optum, 2024).
Predictive Risk modeling	Forecasts patient risk scores 30‑60 days ahead of claim submission.	reduces year‑end coding rush, improving audit readiness.
Robotic Process Automation (RPA)	Automates routine claim validation and eligibility checks.	Cuts manual processing time from 15 min to <2 min per claim.
Blockchain for Audit Trails	Creates immutable logs of coding changes and reviewer approvals.	Enhances compliance transparency, lowers OIG penalty risk.
Voice‑Activated Documentation	Allows clinicians to dictate diagnosis codes directly into the EHR.	Improves documentation completeness while maintaining workflow speed.

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Compliance Landscape & Regulatory Forecast (2026‑2028)

• CMS HCC Expansion – Anticipated inclusion of new mental‑health and SDOH‑related condition categories by FY 2027.
• OIG “reasonable cause” Audits – Expected shift toward data‑analytics‑driven audit triggers; proactive anomaly detection is critical.
• State Medicaid Modernization – Several states (e.g., California, Texas) are piloting risk‑adjusted capitation models with stricter documentation standards.
• HIPAA‑Compliant AI – New guidance in 2025 requires AI tools to undergo risk assessments for protected health information (PHI) handling.

Compliance Checklist (Quarterly)

• Verify that every HCC‑eligible diagnosis clinical documentation.
• Conduct internal coding audits using AI‑assisted sampling.
• Review RPA logs for unauthorized data access.
• Update SDOH data fields to reflect CMS’s latest reporting requirements.

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Benefits of a Proactive, Future‑Ready Approach

• Revenue Optimization – Health systems reported an average 4.3 % increase in risk‑adjusted payments after implementing AI‑driven coding audits (Premier, 2025).
• Audit Resilience – Organizations with blockchain‑based audit trails experienced a 60 % reduction in OIG penalties.
• Clinical Insight – Integrated SDOH analytics enable targeted care management, lowering readmission rates by 8 % in high‑risk cohorts.
• Operational Efficiency – RPA and voice documentation together reduce chart‑review labor by roughly 45 %, freeing staff for direct patient care.

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practical Tips for Immediate Implementation

1. Start Small, Scale Fast

• Pilot AI‑NLP on a single high‑volume specialty (e.g., cardiology) before expanding system‑wide.

2. Leverage Existing Data Governance

• Align new risk‑adjustment data pipelines with your organization’s current data‑quality framework to avoid duplication.

3. Invest in Clinician Education

• Conduct micro‑learning sessions that demonstrate the revenue impact of accurate HCC capture.

4. Create Real‑Time Alerts

• Use predictive models to generate “risk‑capture” alerts within the EHR when a diagnosis lacks an associated HCC code.

5. Document the “Why”

• Ensure every coding decision is linked to a clinical note or order; this narrative is essential for audit defense.

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Case Study: Medicare Advantage Success (2024‑2025)

• Provider: A Midwest health system serving 150,000 Medicare Advantage members.
• Challenge: HCC capture lagged 10 % behind regional benchmarks, leading to $12 M in unmet revenue.
• Solution: Deployed an AI‑NLP engine (trained on 2 M historic notes) to auto‑populate diagnosis codes and introduced quarterly RPA‑driven audit cycles.
• Results:
• HCC capture improved to 96 % of eligible diagnoses within 12 months.
• adjusted revenue increased by $9.5 M (7.9 % growth).
• OIG audit findings dropped from 4 % to 0.6 % denial rate.

Key Takeaway: Combining AI‑assisted documentation with disciplined audit cycles yields measurable financial and compliance gains.

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Real‑World Example: AI‑Powered Coding Audit at a Large Health system (2023‑2024)

• Organization: A West Coast academic medical center with 900 + inpatient beds.
• Technology Stack: Custom NLP model integrated via FHIR APIs; RPA bots for claim validation.
• Outcome: Reduced manual chart review time from 18 hours/week to 2 hours/week, freeing a team of 5 coders to focus on complex cases.
• Compliance Impact: Internal audit flagged 1.2 % of claims for potential over‑coding, all corrected before external submission, eliminating a potential $2 M exposure.

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Future Outlook: Preparing for 2026 and Beyond

• Hybrid Human‑AI Teams – Expect a shift toward collaborative coding workflows where AI surfaces candidates and clinicians validate.
• Standardized SDOH Integration – CMS’s upcoming HCC‑SDOH crosswalk will make social risk factors a core component of risk adjustment models.
• Adaptive Learning Models – Machine‑learning algorithms will continuously retrain on emerging diagnosis patterns, keeping risk scores current without manual rule updates.

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Action Plan Summary (Next 90 Days)

1. Audit Current HCC Capture – Run a baseline KPI report.
2. Select a Pilot Technology – Choose AI‑NLP or RPA based on existing infrastructure.
3. Form a Governance council – Assign leads for data, compliance, and clinical engagement.
4. Launch Training Modules – Focus on documentation best practices and technology use.
5. Set Up Quarterly Review Cadence – monitor scorecards, adjust processes, and iterate.

By embedding these strategies, technologies, and compliance safeguards today, organizations position themselves to thrive in the increasingly complex risk‑adjusted payment environment of 2026 and beyond.