Medical Economics April 26, 2024
Todd Shryock

AI may be good at some tasks in the health care industry, but coding isn’t currently one of them

In a study published in the April 19 online issue of NEJM AI, researchers at the Icahn School of Medicine at Mount Sinai found significant limitations in the capability of state-of-the-art artificial intelligence systems, specifically large language models (LLMs), to accurately perform medical coding tasks.

The study, led by Dr. Ali Soroush and his team, extracted a comprehensive list of over 27,000 unique diagnosis and procedure codes from a year’s worth of routine care data within the Mount Sinai Health System. Utilizing descriptions associated with each code, researchers tasked prominent LLMs from OpenAI, Google, and Meta to generate the most precise...

Today's Sponsors

Venturous
ZeOmega

Today's Sponsor

Venturous

 
Topics: AI (Artificial Intelligence), HIM (Health Inf Mgmt), Survey / Study, Technology, Trends
AI-enabled clinical data abstraction: a nurse’s perspective
Contextual AI launches Agent Composer to turn enterprise RAG into production-ready AI agents
OpenAI’s latest product lets you vibe code science
WISeR in 2026: Legal, Compliance, and AI Challenges That Could Reshape Prior Authorization for Skin Substitutes
Dario Amodei warns AI may cause ‘unusually painful’ disruption to jobs

Share Article