AKASA has launched an autonomous AI platform for medical coding and clinical documentation in healthcare revenue cycles. The South San Francisco-based company's customers now represent more than $180 billion in aggregate net patient revenue and roughly 10% of US inpatient discharges. The platform codes complex inpatient cases across all specialties without human intervention. Third-party evaluations showed AKASA's AI matched or exceeded human coder performance on key accuracy measures. The system completes coding in under 90 seconds after patient discharge, compared to 30–60 minutes for human coders. AKASA fine-tunes AI models for individual health systems, accounting for differences in patient populations and documentation practices. The company's inpatient volume has grown nearly sixfold in the past year. Cleveland Clinic and Nebraska Methodist Health System are among its customers exploring the autonomous platform.

AKASA Launches GenAI-Powered CDI Optimizer to Enhance Clinical Documentation Integrity. by Jasmine Pennic 05/05/2025 Leave a Comment. What You Should Know: – AKASA, the preeminent provider of generative AI (GenAI) solutions for the healthcare revenue cycle, today announced the launch of AKASA CDI Optimizer™. – The new GenAI assistant is designed to help healthcare organizations significantly enhance clinical documentation integrity (CDI), improve compliance, and ensure the full clinical picture is captured for every patient encounter.Addressing Mid-Cycle Revenue Cycle ChallengesThe launch of CDI Optimizer comes as healthcare provider organizations face mounting pressures within their mid-cycle operations – the crucial steps encompassing clinical documentation, coding, and compliance. Factors like rising denial rates, constantly evolving regulatory requirements, and persistent staffing shortages challenge traditional CDI processes. AKASA notes that many health systems still depend on manual chart reviews or older, rules-based systems, which can often miss crucial revenue opportunities and fail to capture necessary quality and compliance metrics.Leveraging Generative AI for Deeper InsightsCDI Optimizer utilizes clinically trained large language models (LLMs) – a form of generative AI – to automatically review 100% of inpatient encounters across all service lines. This AI-driven approach allows the tool to identify documentation gaps and surface high-impact query opportunities that might be missed by other methods.“CDI Optimizer is more than a new product — it’s a strategic leap forward for the mid-cycle,” said Malinka Walaliyadde, CEO and co-founder of AKASA

What You Should Know:– Cleveland Clinic and AKASA have established a strategic collaboration to deploy generative AI tools to support efficient and accurate medical coding practices.– Through this partnership, Cleveland Clinic will apply multiple AKASA AI-powered tools during the mid-revenue cycle – the phase between patient care and billing, where documentation and coding occur – across its U.S. locations.Cleveland Clinic Advances Revenue Cycle Operations with AI-Powered Coding and Documentation ToolsCleveland Clinic, a nonprofit multispecialty academic medical center based in Cleveland, Ohio, continues to drive healthcare innovation by integrating clinical care, research, and education. Founded in 1921 by four physicians dedicated to cooperation, compassion, and innovation, the institution remains a leader in delivering outstanding patient care.Reflecting the complexity of patient care through accurate documentation and coding has long been a time-intensive task. Revenue cycle staff at Cleveland Clinic typically review over 100 clinical documents per case—including progress notes, discharge summaries, and pathology reports—and select from more than 140,000 coding options. This manual process can take up to an hour per patient encounter.To enhance efficiency and accuracy, Cleveland Clinic has begun implementing new AI tools:AI coding assistant : Capable of reading clinical documents in less than two seconds and processing over 100 documents in 1.5 minutes, this tool supports comprehensive and efficient coding by understanding clinical context beyond keyword matching and adapting to patient complexity.: Capable of reading clinical documents in less than two seconds and processing over 100 documents in 1.5 minutes, this tool supports comprehensive and efficient coding by understanding clinical context beyond keyword matching and adapting to patient complexity. Clinical Documentation Integrity (CDI) AI tool: Currently in pilot testing, this tool aims to further improve documentation accuracy by ensuring clinical narratives align with coding practices.Developed with AKASA’s health-system-specific approach, these AI solutions are designed to learn from real-world documentation practices and recognize institutional nuances