Maverick Medical AI Partners with RadNet to Launch AI-powered Medical Coding Across U.S. Imaging Sites

Rhea-AI Summary

Maverick Medical AI (Maverick) (NASDAQ: RDNT) partners with RadNet, Inc. to integrate its autonomous AI-powered medical coding platform, achieving an 85 percent direct-to-bill rate. The partnership aims to optimize revenue cycle management, reduce operational costs, and increase reimbursement. Maverick's platform combines generative AI with medical coding domain knowledge, autonomously analyzing clinical notes and reports to generate reimbursement codes in real-time. The platform's auditing features enable real-time feedback collection, resulting in a significant boost in productivity.

Maverick Medical AI is the first autonomous coding platform to surpass an 85 percent direct-to-bill rate by utilizing generative AI.

WILMINGTON, Del.--(BUSINESS WIRE)-- Maverick Medical AI, or Maverick, a provider of an innovative and autonomous AI-powered medical coding platform, announced today that it has partnered with RadNet, Inc. (NASDAQ: RDNT), a leading national provider of free-standing, fixed-site radiology diagnostic imaging services in the United States. Through this partnership, Maverick integrates its Autonomous Medical Coding platform as the solution for RadNet’s medical coding needs, which will help optimize its revenue cycle management process, reduce operational costs, and increase reimbursement.

Maverick’s Autonomous Medical Coding platform has already been successfully deployed within RadNet’s network of imaging centers. By integrating with DeepHealth, RadNet’s AI-powered health informatics system, Maverick is part of the company’s drive to create breakthroughs in care delivery.

Maverick combines the domain knowledge of medical coding with cutting-edge machine learning and generative AI. It autonomously analyzes clinical notes and reports, accurately generating reimbursement codes (ICD-10, CPT) in real-time and allowing for charges to be available to billing systems within seconds. One of Maverick’s key capabilities is its auditing features, which provide RadNet’s medical coding team the ability to review pre-populated reimbursement codes in a timely fashion. Maverick’s ability to perform active learning enables the collection of feedback in real-time from auditors and medical coders, allowing the platform to adapt without any human intervention. The result is a significant boost in productivity.

RadNet’s Senior Vice President of Information Technology, Susan Hollabaugh, said, “Prior to choosing Maverick, we conducted a year-long assessment of various autonomous coding platforms. Our selection was driven by a combination of key criteria, including a requirement for cutting-edge generative AI technology, support for MIPS quality measures, the development of a real-time radiologist interface for addendum creation, and the ability for the platform to continuously adapt to evolving coding guidelines and regulations. Additionally, we conducted a successful pilot of Maverick's generative AI engine on 350,000 studies, achieving an unprecedented 85 percent direct-to-bill rate.”

“Our platform's ability to blend the power of deep learning generative AI and medical coding domain knowledge has proven to significantly transform medical coding efficiency,” says Yossi Shahak, CEO of Maverick Medical AI. “Our integration with RadNet’s AI informatics platform, DeepHealth, will span all 360-plus imaging sites in their nationwide network, ensuring a superior direct-to-bill rate. By replacing the legacy computer-assisted coding systems with Maverick Medical AI, we are not just streamlining medical coding processes, but also reducing errors and shaping the future of medical coding.”

About Maverick Medical AI

Maverick Medical AI streamlines medical coding for healthcare providers, including imaging centers and hospitals, by automating the process with its personalized, autonomous medical coding platform. This innovative technology leads to decreased operational expenses, reduced denials, and increased direct-to-bill percentage. Its proprietary deep learning generative AI models and synthetic data generation capabilities set Maverick apart from the competition as the go-to solution for any medical coding needs.

For more information, visit www.maverick-ai.com/.

About RadNet

RadNet, Inc., is the leading national provider of freestanding, fixed-site diagnostic imaging services and related information technology solutions (including artificial intelligence) in the United States based on the number of locations and annual imaging revenue. RadNet has a network of 366 owned and/or operated outpatient imaging centers. RadNet's markets include California, Maryland, Delaware, New Jersey, New York, Florida, and Arizona. Together with affiliated radiologists, including full-time and per diem employees and technologists, RadNet has approximately 9,000 employees.

For more information, visit http://www.radnet.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20231126705828/en/

Inbar Kneller

ReBlonde for Maverick Medical AI

inbar@reblonde.com

Source: Maverick Medical AI

FAQ

What is the name of the company mentioned in the press release and its ticker symbol?

The company mentioned in the press release is Maverick Medical AI, with the ticker symbol RDNT.

What is the main focus of the partnership between Maverick Medical AI and RadNet, Inc.?

The partnership aims to integrate Maverick's autonomous AI-powered medical coding platform with RadNet's network of imaging centers to optimize revenue cycle management, reduce operational costs, and increase reimbursement.

How does Maverick's Autonomous Medical Coding platform work?

Maverick's platform combines generative AI with medical coding domain knowledge to autonomously analyze clinical notes and reports, accurately generating reimbursement codes (ICD-10, CPT) in real-time and allowing for charges to be available to billing systems within seconds.

What benefits does Maverick's platform offer to RadNet?

Maverick's platform provides RadNet's medical coding team with auditing features, enabling real-time feedback collection and resulting in a significant boost in productivity.

What are the key criteria that drove RadNet's selection of Maverick's platform?

RadNet's selection was driven by a combination of key criteria, including a requirement for cutting-edge generative AI technology, support for MIPS quality measures, the development of a real-time radiologist interface for addendum creation, and the ability for the platform to continuously adapt to evolving coding guidelines and regulations.