AKASA focuses on the revenue cycle and on improving billing so that hospitals are fully paid for their services. Although the company has been doing this for quite a while before generative AI became feasible, CEO and Cofounder Malinka Walaliyadde has seen that LLMs “unlock capabilities in the revenue cycle that weren’t available before.”
In a recent interivew with Walaliyaadde, we talk about the emerging crisis in coding and billing. Walaliyadde says that the highly trained workforce is “aging out” and that providers can’t find new people fast enough to replace the ones who leave. At the same time, health care problems are growing, requiring more diagnoses and billing. This is a challenge for healthcare organizations where good revenue cycle management is the key to their financial success.
AI, therefore, when implemented properly can “capture the patient story” and improve an organization’s revenue despite all this added complexity. Walaliyadde notes that the patient record now has an average of 60 documents and is 50,000 words long and so its no wonder that humans have a hard time coding it properly. It’s the perfect opportunity for generative AI and LLMs though.
AKASA tunes their LLM for each institution in order to handle the particular needs and complexities of that provider. Some clients are having all hospital billing reviewed by the AI model, which Walaliyadde calls an “AI copilot.” But a human always reviews the results. Walaliyadde expects a human in the loop continuing to be important for certain types of work, while other types of work will progress to autopilot.
Check out our interview with Malinka Walaliyadde from AKASA to learn more about how they’re applying the latest generative AI and other technology to improve revenue cycle management efforts.
Learn more about AKASA: https://akasa.com/
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