3 ways AI is changing the healthcare revenue cycle
The healthcare revenue cycle depends on teams investigating denied claims, checking payer rules and deciding which problems need a human’s attention. AI agents could take on some of that work, but the harder question is how to fit them into the way health systems operate. For Mount Sinai Health System Inc., that starts with clear […] The post 3 ways AI is changing the healthcare revenue cycle…
Three ways artificial intelligence (AI) is transforming the healthcare revenue cycle were explored in a recent interview series. Adonis Technology Inc. is developing AI agents to investigate denied claims and reduce manual processes involved in securing payment. At Mount Sinai Health System, the focus is on establishing clear workflows and assigning accountability for AI exceptions, ensuring that automation does not exacerbate existing problems.
Adonis distinguishes between repetitive tasks suitable for automation and complex work that requires human expertise, such as high-value appeals. Rush University System for Health engages frontline employees to identify and automate time-consuming steps, making staff advocates for further changes. Ultimately, the aim is to leverage AI to alleviate administrative burdens, but regulatory rules governing billing, documentation, and interactions with insurers must evolve to support the successful integration of AI agents in the revenue cycle.
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