Autonomous Medical Coding
See what sets autonomous medical coding apart from AI-assisted and computer-assisted coding, and learn more about Nym’s autonomous medical coding engine.
Not All AI Medical Coding Works the Same Way
Most medical coding AI tools still depend on people. Computer-assisted coding (CAC) suggests codes for coders to validate, and AI-assisted solutions automate portions of code assignment but still require human approval before billing. Autonomous medical coding goes further, assigning codes to patient encounters in seconds and routing them directly to billing with no human intervention.
Nym’s Engine
AI-assisted coding
Computer-assisted coding
Requires zero human intervention to code charts
May require human review, or codes only part of an encounter
Designed as a tool to help human coders with their work
No staff training required
Requires staff training to review and validate flagged charts
Requires special training for staff
Provides audit-ready, traceable documentation for every code it generates
Often a “black box” — no traceable rationale for how a code was reached
Offers none to little help in understanding why the chart was coded the way it was
Flexible and scalable
Scalability limited by reviewer availability
Does not alleviate coding scalability constraints
Explore Autonomous Medical Coding with Nym
Nym's Engine
A true multispecialty solution supporting six specialties and helping top health systems and physician groups reduce coding costs, accelerate time-to-bill, improve revenue capture, and support coding teams.
The Technology
Nym's proprietary Clinical Language Understanding (CLU) technology combines machine learning with rules-based clinical ontologies to code patient encounters in seconds with no human intervention.
Implementation
An organized, transparent implementation process from pre-kickoff to go-live, typically completed in 3 to 6 months, with dedicated Nym experts guiding every phase.
Transforming Emergency Department Medical Coding at Inova
Frequently Asked Questions
What is AI medical coding?
AI medical coding is the use of artificial intelligence, such as machine learning and natural language processing, to assign medical codes to patient encounters. The term spans a wide range of technologies, from computer-assisted coding (CAC) tools that suggest codes for human review to AI-assisted software that automates portions of code assignment. Most AI medical coding software still requires human validation before an encounter can be billed.
What is the difference between AI medical coding and autonomous medical coding?
The difference is human intervention: autonomous medical coding assigns codes and routes encounters directly to billing with zero human intervention, while AI medical coding solutions generally require human review before billing. Nym’s engine is autonomous, sending successfully coded encounters straight to billing with a fully transparent audit trail for every decision.
Does Nym use AI in its medical coding engine?
Yes. Nym’s autonomous medical coding engine is powered by proprietary Clinical Language Understanding (CLU) technology, which combines machine learning models with rules-based clinical ontologies. Unlike “black box” approaches to AI in medical coding, this approach makes every coding decision explainable and audit-ready.
What should health systems look for in medical coding automation tools?
Health systems should evaluate medical coding automation tools on level of automation, coding accuracy, transparency of coding decisions, specialty coverage, EHR integration, and security certifications. The most important question when evaluating medical coding AI is whether encounters route directly to billing or require human validation, since that distinction drives most of the impact on cost and time-to-bill.
Explore the latest from Nym
