Trusted technology. Proven results.
AI, ML, NLP. At Apixio, these acronyms are more than just tech buzzwords. These computational techniques provide the foundation for our risk adjustment coding and QA solutions, extracting insights from structured and unstructured healthcare data to support a streamlined, smarter approach to retrospective and prospective risk capture. Our solutions drive consistent value for 50+ health plan & provider clients nationwide.
Benefits of AI-powered coding & QA
- Accuracy. Accurate identification of risk-adjusting conditions.
- Completeness. Fuller picture of population risk from clinical data.
- Productivity. Review important supporting evidence for risk adjustment more quickly.
- Flexibility. Supports pre-encounter, point-of-care, post-encounter, and retrospective coding.
HCC Complete uses proven AI algorithms to support a comprehensive retrospective chart review experience for Medicare Advantage and Affordable Care Act programs. Our technology identifies both net-new coding opportunities and unsupported known codes and serves them up for coding and auditing in a straightforward workflow.Learn More
HCC Identifier is the most efficient, accurate way to manage HCC coding projects for Medicare Advantage, ACA, and Medicare ACO programs. Our comprehensive chart review & QA solution is available as a web-based application for in-house coding teams or a full-service coding service for first-pass and second-pass reviews.Learn More
Running a paper-based prospective risk program? Our Prospective Analytics solution provides targeted AI-generated condition suspects and supporting evidence delivered in a simple report you can integrate into your existing initiatives such as direct-mail or fax-based programs to improve condition capture at the point of care.Learn More
Providers serving MA and ACA patients don’t always document patient encounters with HCC coding in mind. Apixio’s Documentation Gaps solution identifies encounter notes with attributed HCCs lacking critical documentation elements required for submission. Gaps are attributed to specific providers and include missing elements and dates of service so you can follow up with physicians to close gaps and improve their documentation approach.Learn More