Cleveland Clinic and Akasa have entered a strategic partnership to introduce generative AI tools aimed at enhancing medical coding practices in the US.
The collaboration will provide AI-powered solutions to improve efficiency and accuracy in the mid-revenue cycle across the US.
The mid-revenue cycle is an important phase between patient care and billing, which involves billing documentation and coding.
The revenue cycle staff at the Cleveland Clinic typically review over 100 clinical documents per case, including progress notes, discharge summaries, and pathology reports.
They select codes from more than 140,000 options, a process that can take up to an hour per patient encounter.
The new AI coding assistant tool will allow coders to streamline the process, supporting comprehensive and precise coding practices.
Cleveland Clinic chief digital officer Rohit Chandra said: “AI can be transformational for healthcare, not only in patient care, but for helping health system operations run more smoothly and efficiently.
“We are looking forward to sharing this technology with our revenue cycle teams and continuing to innovate in this space.”
Both organisations have piloted a second AI tool, which focuses on clinical documentation integrity (CDI) to further enhance coding accuracy and efficiency.
The AI tool expedites the coding process, ensuring the most appropriate codes are used.
The AI coding assistant can read a clinical document in under two seconds and process over 100 documents in 1.5 minutes.
It is designed to understand clinical context and adapt to a patient’s complexity.
Cleveland Clinic executive vice-president and chief financial officer Dennis Laraway said: “Cleveland Clinic has embraced artificial intelligence to enhance the experience of patients and caregivers, and with our collaboration with Akasa, we are bringing AI-powered enhancements to our mid-revenue cycle.
“Because we treat some of the highest acuity patients in the country, our revenue cycle activities are incredibly complex.
“Through autonomous coding, we aim to bring greater efficiency and accuracy to these complicated and time-consuming tasks, something that AI is ideally suited to address.”
Akasa’s health-system specific approach enables the AI to learn from real-world documentation practices and recognise nuances in individual health systems.
Its AI capability is crucial for analysing complex patient cases, such as inpatient hospital encounters, which are common at the Cleveland Clinic.
Cleveland Clinic has started deploying this tool across its US locations and will continue to refine the product while contributing to the development of new AI tools for healthcare.
Akasa CEO and co-founder Malinka Walaliyadde said: “We chose to pilot this technology with Cleveland Clinic because we wanted to test our AI against some of the most complex patient encounters in the world.
“We are proud to now be rolling it out, as well as collaborating with Cleveland Clinic’s coders and CDI specialists in developing additional products to make the revenue cycle process easier and more efficient.”
