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KLAS Research Emerging Technology Spotlight Report Indicates 100% Overall Satisfaction Score for CodaMetrix Customers
  • KLAS report examined overall customer experience and satisfaction with CodaMetrix's Autonomous Coding Platform, CMX Automate™
  • Report touts "A" ratings across key performance indicators including integration goals, functionality, executive involvement and overall recommendation

BOSTON, April 18, 2023 /PRNewswire/ -- HIMSS23 -- CodaMetrix, an AI technology platform transforming healthcare revenue cycles, today announced that its autonomous coding platform, CMX Automate™  has earned top customer satisfaction scores in a KLAS Emerging Technology Spotlight report titled, "Reducing Manual Coding Volumes through Automation and Machine Learning."

Emerging Technology Spotlight Reports highlight new technologies that are disrupting the healthcare market. KLAS Research surveyed a sampling of CodaMetrix's current academic health systems clients to evaluate overall client experience and satisfaction. The report highlights that 100% of customers surveyed would purchase CodaMetrix's autonomous coding solution again. Additionally, 100% of respondents also viewed CMX Automate™ as part of their long-term plans.

CodaMetrix was evaluated by a sample of its current clients in several categories and received the following grades:

Key Performance Indicators

KLAS Ratings

Supports integration goals


Executive involvement


Likely to recommend


Product has needed functionality


"CodaMetrix is coding over half of our radiology coding. We have several {full-time} coders and all our overtime is dedicated to radiology. That is a high-volume area, so being able to cut back on overtime is huge," said one director from a leading academic health system. "We had a large backlog sitting in a work queue waiting to be coded, and CodaMetrix's system has helped with that backlog. I had a concern that we would see an uptick in denials with diagnosis coding, and I was okay with that, but we have actually seen a slight decrease in denials."

Among other measurements, the study tracked customer time to see outcomes, with the following outcomes expected by customers:

  • Reduced manual coding volume
  • Improved coding accuracy and decreased denials
  • Shortened timeline for billing
  • Reallocated staff resources

All customers reported seeing outcomes in the four outlined categories. 67% of respondents saw immediate outcomes, and the remaining 33% of customers saw outcomes within six months.

"Quality coding is at the core of what we do and we continue to take great pride in providing our customers with a solution that's focused on removing cost barriers to generating reliable code sets with high clinical specificity," said Hamid Tabatabaie, President and CEO of CodaMetrix. "This report is tangible evidence of the value we create in leveraging AI and automation to transform healthcare revenue cycles for our clients."

Founded in 2019, CodaMetrix's multi-specialty platform classifies codes across radiology, pathology, GI and bedside visits for some of the nation's most prestigious health systems and major academic universities, including Mass General Brigham, University of Colorado Medicine, and Yale Medicine, University of Miami Health System, and Oregon Health and Science University. CodaMetrix recently closed a $55 million Series A round led by SignalFire.

For additional information, including access to the full KLAS report, visit or stop by the CodaMetrix booth at HIMSS (#8242)

About CodaMetrix
CodaMetrix (CMX) is a SaaS technology company providing an AI-powered platform to facilitate healthcare revenue cycle management and medical coding. The company's cutting-edge platform combines machine learning (ML), deep learning, and natural language processing (NLP) to translate clinical notes automatically, accurately, and autonomously into billing and diagnostic codes that satisfy coding requirements while reducing human coding workload. CodaMetrix's AI continuously learns from and acts upon the clinical evidence in electronic health records (EHRs). That knowledge is applied to improve the efficiency and quality of medical coding and to enable providers to code less and care more. For more information, visit

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SOURCE CodaMetrix