Activate Your Clinical Data with Quippe
Evidence-based clinical AI that’s built for the future, and works with your system today.
Powered by the Quippe Clinical Knowledge Graph, EHRs and health technologies are delivering the next generation of tools to assist clinicians at the point of care.
• Smart, multi-modal workflows & AI-assisted documentation
• Intelligent chart analysis and decision support
• Data-driven care coordination
Quippe transforms how clinicians access and use patient data for care delivery.
Book an appointment or stop by the booth during exhibit hall hours to learn how Medicomp's clinically intelligent AI can complement your systems.
Medicomp’s Quippe Clinical Knowledge Graph and Intelligence Engine diagnostically connect data for:
- Intelligent Chart Analysis
- Guidelines and Care Pathways
- CDI
- CQMs
- HCC/RAF
- HTI, USCDI, & SDOH
- Billing, Compliance, & Interoperability
News
- Feb 25, 2025 Medicomp Systems at HIMSS 2025 – Quippe Solidifies Position as a Clinical Data Source of Truth
- Feb 12, 2025 Medicomp Systems Announces Support for USCDI v3, v4 and v5 Along with SDOH Accelerator Tools
- Oct 1, 2024 Medicomp Systems Announces Update of the Quippe® Solutions to the Web Component Standard
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Quippe Clinical Lens
Today’s healthcare problem isn’t a lack of data; it’s a lack of usable data. Quippe® uses MEDCIN's intelligence links to identify and interpret disorganized, complex arrays of medical data and transforms that data into actionable information and clinical insights – all within the physician’s workflow.
Request a demoRecent Posts
A decade after health care dreaded the complexity of ICD-10, the industry now faces a bigger problem: diagnosis codes still aren’t specific enough to safely power AI-driven clinical decision-making.
CEO David Lareau makes the case for deterministic AI as essential healthcare infrastructure, arguing that without a structured, validated clinical knowledge layer, AI-enabled clinical tools produce outputs too unreliable to …Continue
David Lareau, Medicomp Systems CEO, explains that deterministic, rules-based AI models can validate the probabilistic, often inconsistent outputs that LLMs deliver to avoid errors in clinical documentation.