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Strategic adoption trends for automation across the revenue cycle
Management in Healthcare: A Peer-Reviewed Journal,
7
(2),
112-120
(2023)
Abstract
This paper analyses how, while many healthcare organisations are automating portions of the revenue cycle today, there is significant variation in the breadth and depth of automation technology deployed. While robotic process automation (RPA) is helpful, it also has limitations that are easily addressed by more advanced technology, namely artificial intelligence (AI) and machine learning (ML). Identifying best practices for the strategic adoption of advanced revenue cycle automation can help organisations leverage lean processes that reduce the cost to collect, promote strategic customer service tactics and redeploy employees to higher-value tasks that improve the overall patient financial experience.
Keywords: revenue cycle management; RCM; revenue cycle automation; artificial intelligence; machine learning; robotic process automation; patient financial experience
The full article is available to subscribers to the journal.
Author's Biography
Amy Raymond is a revenue cycle leader with more than 20 years of experience in healthcare. As head of revenue cycle operations at AKASA, she leads a remote team of healthcare revenue cycle management (RCM) experts located across the country. Raymond was most recently the senior director for programme management in technology implementations at the Advisory Board, where she managed large-scale RCM implementations. She has overseen numerous revenue cycle teams — for health systems large and small — in different settings and specialities. With an interdisciplinary studies degree in health sciences from the University of Texas at Dallas, Raymond’s career has focused on leading RCM departments through process improvements and system implementations.
Citation
Raymond, Amy (2023, December 1). Strategic adoption trends for automation across the revenue cycle. In the Management in Healthcare: A Peer-Reviewed Journal, Volume 7, Issue 2. https://doi.org/10.69554/CESQ6688.
© Henry Stewart
Publications LLP
Publications LLP