Cognizant and Palantir Partner to Modernize Healthcare Operations with AI
Cognizant has partnered with Palantir to bring AI into the core of healthcare and enterprise operations. The plan: combine Palantir Foundry and AIP with Cognizant's TriZetto healthcare platforms and business process operations to streamline work, reduce manual effort, and keep governance tight.
For healthcare leaders, this isn't another pilot on the side. It's embedding AI inside the workflows you already run-claims, prior auth, care management, and revenue cycle-while preserving compliance and auditability.
What the collaboration includes
- Integration of Palantir Foundry and AIP with TriZetto platforms and BPaaS operations.
- Ontology-driven AI that maps real-world healthcare entities (member, provider, claim, encounter) for consistent, governed decisioning.
- Security, access controls, and full audit trails to meet regulatory requirements in high-stakes, labor-heavy environments.
- A roadmap to accelerate product development and future AI capabilities without sacrificing oversight.
Beyond healthcare, both companies plan to pursue broader enterprise AI opportunities, aligning with Cognizant's push to build a composable ecosystem of AI platforms for internal use and client-facing innovation.
Why this matters for healthcare operators
Most payers and providers sit on fragmented data and people-heavy processes. This partnership targets that bottleneck: unify data, automate tedious work, and give teams decision support right where they act.
- Claims and adjudication: speed up triage, detect errors early, cut rework.
- Prior authorization: auto-summarize clinical evidence, propose determinations with human review, reduce turnaround time.
- Care management: surface high-value interventions, route tasks, and track outcomes with clear attribution.
- Revenue cycle: reduce denials, predict underpayments, and prioritize follow-ups.
- Contact centers: AI copilots that fetch member, policy, and claim context in a single view.
- Compliance and audit: standardize controls, log every decision, and generate evidence on demand.
Governance and compliance (the non-negotiables)
- PHI isolation, role-based access, and fine-grained permissions across data and prompts.
- End-to-end lineage: who touched what, which model contributed, and why a decision was made.
- Model risk management: bias testing, approval workflows, versioning, and rollback plans.
- Prompt and output logging with retention policies that pass audit scrutiny.
A practical 90-day plan to capture value
- Pick 1-2 high-friction workflows (e.g., prior auth for a specific specialty, a denial category in RCM).
- Define success: turnaround time, cost per case, rework rate, or audit findings. Baseline it.
- Map a simple ontology: member, provider, claim/encounter, policy, clinical notes. Keep it lean at first.
- Connect data sources into Foundry; establish permissioning and lineage from day one.
- Build a copilot that reads policies, guidelines, and case history (RAG), and embeds into TriZetto workflows.
- Require human-in-the-loop approvals. Log everything.
- Pilot with a small team, measure weekly, and expand only after hitting target metrics.
Metrics to track
- Claims: days to adjudication, touch rate per claim, rework/appeal rate, cost per claim.
- Prior auth: decision turnaround time, deflection to auto-approve/auto-deny with human review, audit exceptions.
- Care management: time-to-intervention, adherence to protocols, avoidable ED visits or readmissions.
- Operations: FTE hours saved, average handle time in contact centers, first-call resolution.
- Risk and compliance: model approval cycle time, audit findings closed, data access exceptions.
Risks and how to manage them
- Vendor lock-in: standardize interfaces, keep your ontology documented, and export models/artifacts regularly.
- Data residency and PHI: confirm deployment model (on-prem/VPC) and encryption policies early.
- Integration complexity: inventory interfaces, master data sources, and change owners before build.
- Change management: train supervisors first, codify new SOPs, and set clear escalation paths.
- Model drift: schedule monitoring, threshold alerts, and quarterly re-validation.
Where to learn more
Product overviews are a good start:
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