How will Artificial Intelligence transform Revenue Cycle Management?

medical billing

Artificial intelligence and automation have made a significant mark in industries worldwide and it is relevant to healthcare as well. PwC has released a recent report which predicts that 38 percent of existing jobs in America could be affected by AI automation by the early 2030s.

Revenue cycle management in healthcare is liable to AI automation due to many activities which are relatively transactional. Here are four reasons why AI could make a marked change in Revenue Cycle Management (RCM).

  • Cost: A major portion of RCM costs is people. With reduced staff expense due to automation and AI, healthcare systems would bring down their collection expense.  The number of processes which will be executed by AI and automation would determine the debt collection at revenue cycle management for organizations which can go up to 50 percent in the next 10 years.
  • Quality: AI can also add value with quality control to RCM with higher standardization and repetition of processes with the same level of quality. Higher predictability in accuracy, productivity, and performance will be seen subject to AI algorithms if they are executed accurately.
  • Analytics for prevention of issues: On a real-time basis, AI can inject a higher level of transparency and visibility to exceptions that happen in the revenue cycle, such as denials and credits management.  Patterns identifying revenue slippages would be executed on a real time basis with the help of AI. It could lead to problems like a change in reimbursement process, or error in mapping codes etc.
  • RCM experts are slow:  Despite the ability of AI to change the RCM operational landscape, RCM experts are not sure of the outcomes and lack clarity in this area. The trust factor on this concept is quite low as to its work methodology.  Currently, AI has made significant inroads into clinical data and it is coming to RCM as well.

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