INTEGRATION OF WORKFLOW AND RPA TECHNOLOGIES IN HEALTHCARE CLAIMS PROCESSING: A SYSTEMATIC ANALYSIS OF EFFICIENCY AND ERROR REDUCTION
DOI:
https://doi.org/10.34218/IJCET_16_01_176Keywords:
Healthcare Automation, Robotic Process Automation (RPA), Claims Processing Optimization, Workflow Automation Systems, Healthcare Administrative EfficiencyAbstract
This article investigates the implementation and impact of integrated Workflow Automation and Robotic Process Automation (RPA) solutions in healthcare claims and prior authorization processing. Through a comprehensive analysis of multiple healthcare organizations, this article examines how these technologies address critical challenges in administrative healthcare operations, including processing delays, human error rates, and compliance requirements. The article employs a mixed-methods approach, combining quantitative performance metrics with qualitative assessments of implementation challenges and organizational adaptation. Article demonstrates significant improvements in processing turnaround times, error reduction, and operational efficiency, while highlighting key considerations for successful implementation. The article also identifies critical success factors for integration with existing healthcare information systems and presents a framework for healthcare organizations to evaluate and implement automated solutions. This article contributes to the growing body of knowledge on healthcare automation and provides practical insights for healthcare administrators and technology leaders seeking to optimize their administrative operations through technological innovation.
References
Matthew Pike, Nasser M. Mustafa, Dave Towey, & Vladimir Brusic (2019). “Sensor Networks and Data Management in Healthcare: Emerging Technologies and New Challenges”. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), 890-895. DOI: 10.1109/COMPSAC.2019.00123. https://ieeexplore.ieee.org/abstract/document/8753998
Karoline Farias, Pedro Santos Neto, Andre Santana, & Ranulfo Bezerra Neto (2019). “Using Historical Information of Patients for Prior Authorization in Health Maintenance Organizations.” 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 574-579. DOI: 10.1109/BRACIS.2019.00110. https://ieeexplore.ieee.org/document/8923676
Ashish Dwivedi, Rajeev K. Bali, Amos E. James, & Raouf N.G. Naguib (2002). "Workflow Management Systems: The Healthcare Technology of the Future". 2001 IEEE 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS). https://ieeexplore.ieee.org/document/1019689
Paula Hernández García & Dina Simunic (2021). "Regulatory Framework of Artificial Intelligence in Healthcare". 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO). https://ieeexplore.ieee.org/abstract/document/9597180
Mohamed Mouine & Mohamed Aymen Saied (2023). "Model-Driven Approach to Design & Architecture of Healthcare IoT Infrastructure". 2022 3rd International Conference on Human-Centric Smart Environments for Health and Well-being (IHSH). https://ieeexplore.ieee.org/document/10092095
Lauren Roberts, Peter Michalák, Sarah Heaps, et al. (2018). "Automating the Placement of Time Series Models for IoT Healthcare Applications". 2018 IEEE 14th International Conference on e-Science (e-Science). https://ieeexplore.ieee.org/document/8588675
Stephen L. Grimes (2005). "The Challenge of Integrating the Healthcare Enterprise". IEEE Engineering in Medicine and Biology Magazine, 24(2). https://ieeexplore.ieee.org/document/1411360
Remya Sivan & Zuriati Ahmad Zukarnain (2021). "Security and Privacy in Cloud-Based E-Health System". Symmetry, 13(5), 742. https://www.mdpi.com/2073-8994/13/5/742
Qizhang Feng, Mengnan Du, Na Zou, & Xia Hu (2020). "Fair Machine Learning in Healthcare: A Survey". IEEE Transactions on Artificial Intelligence, 00(0). https://arxiv.org/pdf/2206.14397v3
M. R. Sumalatha & M. Prabha (2019)."Mediclaim Fraud Detection and Management Using Predictive Analytics". International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), Dubai, UAE, 2020. https://ieeexplore.ieee.org/document/9004241/citations#citations
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Phani Kumar Praturi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
