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RSNA 2023: CodaMetrix Announces Agreement to Bring AI-Powered Automated Coding to More Healthcare Providers

CodaMetrix (PRNewsfoto/CodaMetrix)

News provided by

CodaMetrix

Nov 21, 2023, 12:43 ET

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CodaMetrix's solution is recognized by KLAS Research, and proven to help providers realize an average 60% reduction in claims denials and 50% savings on coding costs

BOSTON, Nov. 21, 2023 /PRNewswire/ -- CodaMetrix announced a strategic distribution agreement with GE HealthCare to bring CMX Automate™, a cloud-based autonomous coding solution, to GE HealthCare customers. This agreement will enable GE HealthCare customers to rapidly benefit from CodaMetrix's CMX Automate solution that uses artificial intelligence (AI)-powered autonomous medical coding to bolster both quality and efficiency in coding. CMX Automate is recognized by KLAS Research as No. 1 in the "Reduce Cost of Care" category.

In GE HealthCare's booth 7326 at the Radiological Society of North America (RSNA) 2023 annual meeting, they will share how CMX Automate fits into its digital ecosystem. CodaMetrix will also provide live product demonstrations in booth 6146 at RSNA.

CodaMetrix's solution will be delivered through GE HealthCare's digital platform, which standardizes integration architecture and offers a secure, vendor-neutral environment that aggregates siloed healthcare data and enables core application services. The addition of CodaMetrix reflects GE HealthCare's commitment to bringing AI powered digital solutions to customers that address the mission-critical challenges facing healthcare providers today.

CMX Automate™ from CodaMetrix combines machine learning (ML), deep learning, and natural language processing (NLP) to translate clinical notes automatically, accurately, and autonomously into billing and diagnostic codes to ensure claims consistently represent the unique and complete episode of care, while reducing the human coding workload.

By leveraging the power of AI-based autonomous medical coding, healthcare providers can reduce costs, improve accuracy, and increase efficiency across the revenue cycle. Today, leading healthcare provider organizations - including Mass General Brigham, University of Colorado Medicine, Yale Medicine, and Henry Ford Health Systems - have already recognized a significant reduction in claims denials (60%) and savings on coding costs (50%) as a result of adopting CMX Automate.

"We're honored to work with GE HealthCare. This collaboration reflects our mission at CodaMetrix to make high-quality, consistent coding affordable and reliable through the intelligent application of AI and automation," said Hamid Tabatabaie, President and CEO at CodaMetrix. "We're excited to now offer even more providers access to CMX Automate at a time when coder workforce shortages and physician burnout are at all-time highs. The type of clinical specificity provided by our CMX Automate platform is key to optimizing the revenue cycle management process, but it also holds the potential to support clinical-decision making and data-driven research over time."

To set time to meet at RSNA and learn more about the partnership between GE Healthcare and CodaMetrix, please visit: http://bit.ly/3G5ZyLb.

About CodaMetrix

CodaMetrix provides an AI-powered platform for multi-specialty medical coding, a $20B annual market. On average, providers utilizing the CMX platform see a 60% reduction in claims denials and a 50% savings on coding costs. CMX is in use at more than a dozen premier provider organizations and health systems, representing more than 200 hospitals and 50K providers. The platform - which was incubated within a leading healthcare system - is uniquely designed with a comprehensive patient-centric longitudinal view of records. Built for and by providers, the CMX platform is recognized by KLAS Research as No. 1 in the "Reduce Cost of Care" category, and provides real-time audit capabilities and seamless EHR integration which are used as a feedback loop to continuously improve learning. For more information, visit us at: Codametrix.com and on LinkedIn.

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