Apixio Launches AI-Powered Quality Identifier Solution for Improved Quality Measurement and Patient Care
Apixio's Industry-Leading AI Analytics Platform Enables Accurate Measures of Care Quality SAN…
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The Apixio Platform
Every year, 1.2 billion clinical documents are generated in the U.S., but most of this data goes unused in the provision of care. The Apixio Platform surfaces targeted insights from healthcare documents to inform operations and care delivery.
Why Apixio
Apixio is using machine learning to create better decision making for quality healthcare. Our technology analyzes unstructured and structured datasets to model patient care. We help providers and payers better perform critical activities such as risk adjustment and quality reporting to achieve optimal outcomes.
Data-driven intelligence
Our AI platform converts unstructured patient information into actionable data, so you can get a complete picture of healthcare. Our solutions support better decisions to deliver quality and affordable care.
Powered by experience
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Events
Experience the Apixio difference firsthand
We frequently attend events around the country to provide an in-depth look at our technology and services. Take a look at where we'll be next and stop by to learn more.
Featured
Our AI technology is growing
As part of our ongoing commitment to innovation and improving healthcare, we're excited to announce the release of our latest technology. See how we're now using AI to improve clinical care.
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Apixio Achieves HITRUST CSF® Certification
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Prospective: The Future of Risk Adjustment
Understanding the health of a population and predicting how patient health will…
Testimonials
By using Apixio, we’re improving our auditing bandwidth and enhancing the ability of our coders to focus on other chart audits and other projects that we couldn’t do before.
The coding team was wonderful to work with, and incorporated our specific coding guidelines when working on our project. When they noticed a trend in what we were rejecting, they shared a Coding Clinic we were unaware of for clarification on how to code the scenarios.