Revenue Cycle Management

Ohio-based MetroHealth
Revenue Cycle Management

MetroHealth Leaders Decrease Denials Through Automation

June 21, 2024
According to a case study by Cognizant, a new revenue cycle approach nets $13M for MetroHealth, a safety-net healthcare system
Revenue cycle management solutions company CodaMetrix has closed a $40 million Series B funding round to create AI solutions that improve medical coding quality. Founded in 2019, CodaMetrix’s CMX platform was built in partnership with Mass General Brigham to provide real-time audit capabilities and seamless EHR integration, which are used as a feedback loop to continuously improve AI learning. The software-as-a-service platform uses machine learning, deep learning, and natural language processing to continuously learn from, and act upon, the clinical evidence stored in electronic health records (EHRs). As a multi-specialty platform that classifies codes across radiology, pathology, surgery, gastroenterology, and inpatient professional coding, Boston-based CodaMetrix said it is the first platform to have an impact across departments by alleviating administrative burdens from billing staff. On average, CodaMetrix said, providers using the CodaMetrix platform experience a 60 percent reduction in coding costs, 70 percent reduction in claims denials, a 5-week acceleration in time to cash, and improvements in provider satisfaction, quality and compliance. The company has partnered with several health systems – including Mass General Brigham, University of Colorado Medicine, Mount Sinai Health System, Yale Medicine, Henry Ford Health and the University of Miami Health System. “Medical coding is one of the most time-consuming, understaffed and inherently error-prone parts of the health system revenue cycle. Hospitals face a high demand on human and financial resources and clinicians must often work through tedious, administrative processes away from patient care,” said Hamid Tabatabaie, CodaMetrix president and CEO, in a statement. “Our game-changing AI platform delivers vital automation which not only addresses these pain points but, more significantly, changes claims data from notoriously unreliable to clinically valuable. We are proud to serve leading provider organizations with a comprehensive and transformative automation solution, setting the standard for coding quality as part of our vision to change healthcare through the use of AI.” The company’s Series A funding was led by SignalFire. Frist Cressey Ventures (FCV), Martin Ventures, Yale Medicine, University of Colorado Healthcare Innovation Fund, and Mass General Brigham physician organizations also participated in the round. The Series B was led by Transformation Capital with continued support from existing investors SignalFire, Series A lead, and Frist Cressey Ventures.
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Revenue Cycle Management

Is AI in Revenue Cycle’s Future? Experts Say the Answer is a Clear “Yes, But”

Sept. 20, 2021
Experts, and CFOs in the trenches, agree that revenue cycle management leaders need to buttress their technological and process foundations before they can exploit the potential...
Ten Trans Trends Logo2021
Revenue Cycle Management

The New Revenue Cycle Management

March 18, 2021
After years of work to automate manual processes, provider organizations are edging towards leveraging machine learning and AI to turbocharge their revenue cycle management processes...
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Revenue Cycle Management

CAQH: Automating Administrative Transactions Cuts Annual Costs by $122B

Feb. 11, 2021
Electronic adoption of prior authorization transactions rose 8 percentage points from the previous year, saving the industry $9.64 per transaction
Data Analytics Healthcare
Revenue Cycle Management

Realizing the Power of Data in Payer-Provider Negotiations

Jan. 5, 2021
Analytics are helping providers come to the negotiation table with far more leverage than ever before
Revenue Cycle Circle
Finance/Revenue Cycle

No More DIY Approaches to Revenue Cycle Management

Just like the DIY project, the days of internally building and managing RCM are mainly fading