AKASA launches authorization advisor, first in a suite of generative AI assistants to optimize revenue cycle for healthcare providers

AKASA, the preeminent provider of generative AI (GenAI) solutions for the revenue cycle, today launched the first in a suite of AI assistants focused on optimizing revenue cycle management for healthcare providers.

Editor's Note: This article originally appeared on AKASA's website

Authorization AdvisorTM is a new GenAI tool that helps prior authorization specialists efficiently and comprehensively complete authorization submissions. In addition, it supports any payer portal or service line and most electronic health record (EHR) systems. With Authorization Advisor, revenue cycle teams can now reduce the time spent on prior authorization by up to 50% and submit more thorough authorizations by finding 15% more relevant clinical documents.

AKASA’s unique approach is to develop a health system–specific AI model by training on that organization’s own clinical and financial data. The company’s solutions, including Authorization Advisor, are powered by these tailored models and are able to deeply understand a health system’s specific nuances. AKASA’s models are already outperforming the top generic versions (like GPT-4 from OpenAI) — for example, they are 38% more accurate when it comes to correctly selecting prior authorization documents.

Prior authorization is the second most time-consuming part of the revenue cycle. Authorization Advisor is infusing GenAI capabilities to address this burden. It provides prior authorization specialists — from entry-level to veteran — with an interactive sidebar view of patient details and curated clinical documentation from the EHR, all directly in their workflow while they are on a payer portal.

Authorization Advisor enables patient access teams to fill in information on the payer portal securely and accurately. This GenAI assistant also empowers staff to easily attach AI-recommended relevant clinical documentation (with evidence for the recommendations) as part of the authorization submission. It eliminates the need to hunt for and read vast amounts of supporting documentation manually, and it aids in the accuracy of prior authorization submissions. Click here to continue>>

 

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