Leveraging Artificial Intelligence for Enhanced Revenue Cycle Management in the United States

Victor Kilanko

Abstract

This academic paper explores the role of artificial intelligence (AI) in revolutionizing revenue cycle management (RCM) practices in the United States. It examines the current challenges faced by healthcare providers in managing revenue cycles efficiently and analyzes how AI-based solutions can address these challenges. The paper also highlights the potential benefits of AI in improving accuracy, efficiency, and cost-effectiveness in the revenue cycle process. Drawing on peer-reviewed research and industry case studies, this paper provides insights into the implementation of AI technologies in the US healthcare system and discusses the implications for healthcare providers, payers, and patients. With the healthcare industry facing increasing pressure to reduce costs and improve patient outcomes, the use of AI in RCM has emerged as a promising solution. AI has the potential to automate repetitive tasks, reduce errors, and enable predictive analytics, leading to more efficient and effective revenue cycle management. However, the implementation of AI in RCM also presents significant challenges, including the need for data standardization and interoperability and concerns around data privacy and security. Despite these challenges, the potential benefits of AI in RCM cannot be ignored. By leveraging AI-based solutions, healthcare providers can streamline revenue cycle operations, reduce administrative burdens, and improve patient experiences. As AI technologies continue to advance, it is clear that they will play an increasingly important role in the future of healthcare, particularly in revenue cycle management.

Keywords

revenue cycle management; artificial intelligence; United States

Cite This Article

Kilanko, V. (2023). Leveraging Artificial Intelligence for Enhanced Revenue Cycle Management in the United States. International Journal of Scientific Advances (IJSCIA), Volume 4| Issue 4: Jul-Aug 2023, Pages 505-514, URL: https://www.ijscia.com/wp-content/uploads/2023/07/Volume4-Issue4-Jul-Aug-No.463-505-514.pdf

Volume 4 | Issue 4: Jul-Aug 2023

 

ISSN: 2708-7972

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This work is licensed under a Creative Commons Attribution 4.0 (International) Licence.(CC BY-NC 4.0).

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