Funding Moves Signal Practical AI Momentum in Payment Integrity and Clinical Trials
Two headlines worth your attention: Codoxo closed an oversubscribed $35M Series C led by CVS Health Ventures, and Mass General Brigham spun out AIwithCare to scale AI-driven clinical trial screening. Both point to the same direction-move interventions upstream, reduce waste, and give clinicians back time.
Codoxo's Series C: Payment Accuracy at "Point Zero"
Codoxo raised $35M in Series C funding led by CVS Health Ventures, with Echo Health Ventures joining and ongoing participation from Sands Capital, 111 West Capital, Brewer Lane Ventures, Wipro Ventures, 450 Ventures, and QED Investors. Total funding now tops $75M. National health plans are adopting Codoxo's AI and generative AI platform to prevent payment errors before they occur-what the company calls "Point Zero."
This shift matters. Health plans are feeling cost pressure while trying to lower provider abrasion. Prepay detection, explainable policy checks, and proactive education can reduce error rates without increasing administrative burden. The upside: fewer reworks, faster payments, and better relationships with providers.
- Map your claims lifecycle end-to-end and identify where prepay checks can replace post-pay recovery.
- Run a controlled pilot: pick 3-5 high-variance benefit areas (e.g., imaging, DME, pharmacy claims) and track denial preventions, dollars protected, cycle time, and provider contacts avoided.
- Demand explainability: require natural-language rationales tied to policy IDs and historical precedent. Set clear guardrails for GenAI output and PHI handling.
- Measure provider experience: monitor appeal rates and "first-pass payment" improvements alongside financial ROI.
- Align SIU and payment integrity: use GenAI to summarize records and create consistent case narratives while retaining human review for action.
Mass General Brigham's AIwithCare: Faster, Fairer Trial Screening
Mass General Brigham launched AIwithCare to bring RECTIFIER (RAG-Enabled Clinical Trial Infrastructure for Inclusion Exclusion Review) to more sites. The tool outperformed manual screening in a proof-of-concept (June 2024) and a randomized, blinded trial (February 2025). It's already in use or onboarding across more than 20 areas including cardiology, oncology, GI, neurology, pathology, and psychiatry.
RECTIFIER's core strength is translating complex inclusion/exclusion criteria into consistent, auditable recommendations with clinician oversight. Through the AIwithCare Studio platform, the team plans to help other health systems match patients to trials and support operational analytics. Success depends on workflow fit, change management, and security-points emphasized by the health system's leadership.
- Start where screening is slow and costly: oncology and cardiology typically show clear ROI.
- Co-design with clinicians, coordinators, IRB, and IT security from day one; define who reviews AI suggestions and how exceptions are handled.
- Integrate quietly: read-only EHR access, clear audit trails, and single sign-on reduce friction.
- Track outcomes: eligible patients found per hour, consent rate, time-to-enroll, screen-failure reasons, and diversity of enrolled participants.
- Standardize criteria: convert protocols into structured rules; align with how eligibility is explained to patients and documented in notes. For context on eligibility basics, see ClinicalTrials.gov guidance.
- Governance first: validate against a gold-standard cohort, check for bias across demographics, and document model and prompt versions for audit.
What This Means for Healthcare Leaders
- Budgets are moving from post-pay chase to prepay accuracy. Expect procurement cycles that demand measurable denial prevention and provider experience metrics.
- AI-supported trial screening is shifting from nice-to-have to standard infrastructure, especially for high-volume research centers.
- The common thread: AI that explains itself, fits existing workflows, and delivers results you can verify.
If your teams need practical AI upskilling to support initiatives like these, explore role-based programs at Complete AI Training.
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