- Born out of Mass General Brigham, and led by healthtech veterans, CodaMetrix empowers health systems to use Artificial Intelligence to prevent revenue setbacks driven by manual coding inefficiencies
- Overhauling medical coding is now crucial for health systems grappling with physician burnout, billing backlogs and claim denials, skilled labor shortages, and a graying medical coding workforce
- AI-powered, multi-specialty, autonomous medical coding eliminates human intervention, reduces coding costs, improves coding quality and unlocks clinician capacity
BOSTON, Feb. 27, 2023 /PRNewswire/ -- CodaMetrix, the leading AI technology platform transforming healthcare revenue cycle management, today announced that it closed a $55 million Series A round led by SignalFire. Frist Cressey Ventures (FCV), Martin Ventures, Yale Medicine, CU Healthcare Innovation Fund, and Mass General Brigham physician organizations also participated in the round. Chris Scoggins, Partner at SignalFire, will join the CodaMetrix Board of Directors.
The capital injection will accelerate go-to-market with major provider organizations and health systems, as U.S. healthcare contends with high coding expense, increasing complexity and ongoing skilled labor scarcity further underscoring the critical need for automation to address the chronic inefficiencies that continue to waste 25-30% of every dollar spent in healthcare.
"CodaMetrix's innovations in AI technologies and the experienced team of healthtech executives are a couple of key factors that went into our decision to partner with the company to systematically improve the way our health system accounts for patient care in both billing and clinical cycles", said Chris Scoggins. "This platform literally wasn't possible even a few years ago but now because of advances in AI and cloud computing, combined with unique training data from our world-class health system partners, CodaMetrix has built a platform that really works for physicians, financial administrators and health systems."
Senator Bill Frist, M.D, Co-founder and Partner at FCV commented, "The proven outcomes, customer traction of the platform, and focus on quality coding are well in line with our goals of administrative streamlining to tackle wasteful spending in billing and insurance-related expenses".
Hospital CFOs and revenue cycle VPs are facing a severe shortage within their revenue cycle management or billing departments. Medical coding is one of the costliest and most time-consuming roles to fill, based on job search and time for onboarding, and 30% of positions sit empty. Held largely by older Gen X-ers and Baby Boomers, medical coding needs have been outpacing the speed of healthcare innovation.
As it stands today, medical coding is still a highly manual and error-prone process that plagues hospital finances and contributes to physician burnout. Certified professional medical coders sift through clinical notes (non-standardized) to correlate each patient encounter with standard and regulated codes (e.g., Procedure (CPT) and Diagnosis (ICD)) for each claim submitted for reimbursement. Coders must navigate tens of thousands of classification options to choose codes mandated by varying payer rules, contributing to a 40% or more error rate. As such, coders are expected to "speak the language" of physicians and payers, a mistake-prone exercise that drains time from coders and physicians alike.
"As a company born out of one of the largest and most innovative health systems in the country, our team experienced firsthand the pain points caused by medical billing challenges, including delayed payments, claim denials, coder shortages, high costs, and the time they take time away from patient care," said Hamid Tabatabaie, CodaMetrix President and CEO. "To address these challenges, medical coding, as the proxy for evidence of care provided, has to become largely autonomous. Beyond the clear cost and efficiency advantages, automation for the first time will make it affordable and practical to ensure selected codes include the clinical specificity required for use cases in population health, value-based care, care management, research, and quality initiatives. Our goal is to use our platform to bridge the gap between clinical and administrative use cases of medical coding, while continuously delivering actionable insights to make the revenue cycle faster, smarter, and less of a burden on physicians and the coding workforce."
Currently in partnership with 10 health systems and major academic universities, including Mass General Brigham, University of Colorado Medicine, Yale Medicine, and Henry Ford Health Systems, CodaMetrix improves clinical coding accuracy and reduces revenue leakage. The platform uses AI in the form of 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, CodaMetrix is the first platform to have an impact across departments by alleviating administrative burdens from billing staff.
"Frustrated by the lack of quality autonomous solutions out there, we built CodaMetrix through the lens of healthcare revenue cycle experts, addressing real health system and physician concerns. Our outcomes — a 70% reduction in manual labor — 59% reduction in denials due to coding, and a significant increase in cost savings — is the proof." said Michael Mercurio, Vice President of Physician Revenue Cycle Services at Mass General Brigham.
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 https://www.codametrix.com.
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