MEDICOMP SYSTEMS @ VIVE 2023

DIAGNOSTICALLY CONNECTING DATA @ VIVE 2023 : BOOTH V-2128

VIVE 2023 • NASHVILLE, TN March 26-29, 2023 Booth V-2128

Is Your Documentation Audit Proof?

With CMS’ increased scrutiny on risk-based reimbursement through Medicare Advantage and similar programs, providers must have audit-proof documentation that accurately and fully captures details of a patient’s condition for risk assessment.

Medicomp’s Clinical AI solutions facilitate audit-proof documentation, as well as diagnostically connect data for:

  • Clinical Documentation Improvement (CDI)
  • Clinical Quality Measures (CQMs)
  • HCC coding and risk adjustment (HCC/RAF)
  • Guidelines and pathways
  • Clinical decision support

Schedule a Meeting!

    To reserve your space to try Quippe or to schedule a 15-minute demo with the Medicomp team, simply complete the form below. If you have any questions, please email marketing@medicomp.com








    Quippe Clinical Lens

    Today’s healthcare problem isn’t a lack of data; it’s a lack of usable data. Quippe® Clinical Lens 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 demo

    Recent Posts

    “Tell Me Where IT Hurts” Podcast: Chuck Tuchinda, MD, MBA, EVP and COO of Hearst Health and Executive Chairman of FDB

    On this episode of Tell Me Where IT Hurts, host Dr. Jay Anders sits down with Chuck Tuchinda, MD, MBA, a physician leader at the intersection of data, artificial intelligence, …Continue

    Planetary Health First Mars Next Podcast: If AI gets it wrong, patients at risk with Dr. Jay Anders

    Dr. Jay Anders talks about trust, accuracy, and reliability of AI in healthcare and clinical decision-making with Michael Mann on the Planetary Health First Mars Next podcast.

    HealthcareIT News: The damage AI hallucinations can do – and how to avoid them

    Dr. Jay Anders offers recommendations for effective AI implementation in healthcare.