Revolutionizing Claims Processing in the Healthcare Industry: The Expanding Role of Automation and AI
Keywords:
automation, artificial intelligence, claims processingAbstract
Hard, inefficient, and error-prone healthcare claims processing is changing. Says AI and processing system automation will improve efficiency and alleviate industrial issues. AI and automation reduce mistakes, handle claims quickly, and save time.
Automation changed claims. Automation of data-intensive claims administration may save healthcare and insurance firms time and money. Processing claims faster and more accurately using automation boosts cash flow and reimbursement. Through machine learning and predictive analytics, AI improves claims processing decision-making, anomaly identification, and adjudication. AI and automation reduce redundancies and speed claims.
References
A. K. Gupta and P. C. Gupta, “Robotic Process Automation: A Game Changer for Insurance Claims Processing,” Journal of Business Research, vol. 115, pp. 295–300, 2020.
A. K. Bhatia, S. J. Ahuja, and R. K. Arora, “Automating Claims Processing in Insurance Using RPA,” Journal of Automation and Control Engineering, vol. 8, no. 1, pp. 46–51, 2020.
H. W. Tseng, “Improving Claims Processing Through Machine Learning Techniques,” Insurance Technology Journal, vol. 12, no. 3, pp. 78–85, 2019.
R. Abubakar, G. M. Ibrahim, and N. S. Hussain, “Health Insurance Fraud Detection: A Review of Machine Learning Techniques,” Journal of Big Data, vol. 7, no. 1, p. 39, 2020.
M. K. Li and Y. W. Chen, "Machine Learning Techniques for Personalized Health Insurance Pricing," IEEE Access, vol. 8, pp. 175933-175941, 2020.
A. Albrecht, R. S. M. Bradshaw, and K. F. F. M. Ransome, “Machine Learning in Health Insurance: Risk Assessment and Fraud Detection,” Health Informatics Journal, vol. 27, no. 2, pp. 1–15, 2021.
J. T. H. M. Ghali, “Using Machine Learning Algorithms for Fraud Detection in Health Insurance: A Systematic Review,” International Journal of Applied Science and Technology, vol. 11, no. 5, pp. 43-50, 2021.
D. R. Chen, L. Q. Li, and Y. X. Wang, “Machine Learning in Insurance: A Comprehensive Review,” IEEE Transactions on Big Data, vol. 7, no. 4, pp. 1033–1047, 2021.
Marciniak, Piotr, and Robert Stanisławski. "Internal determinants in the field of RPA technology implementation on the example of selected companies in the context of industry 4.0 assumptions." Information 12.6 (2021): 222.
Dhatterwal, Jagjit Singh, Kuldeep Singh Kaswan, and Naresh Kumar. "Robotic process automation in healthcare." Confluence of Artificial Intelligence and Robotic Process Automation. Singapore: Springer Nature Singapore, 2023. 157-175.
Bhattacharyya, Siddhartha, Jyoti Sekhar Banerjee, and Debashis De, eds. Confluence of Artificial Intelligence and Robotic Process Automation. Vol. 335. Springer Nature, 2023.
Devapatla, Harini, and Srikantha Reddy Katti. "Streamlining Administrative Processes in Healthcare through Robotic Process Automation: A Comprehensive Examination of RPA's Impact on Billing, Scheduling, and Claims Processing." African Journal of Artificial Intelligence and Sustainable Development 3.2 (2023): 14-27.
Doguc, Ozge. "Robot process automation (RPA) and its future." Research Anthology on Cross-Disciplinary Designs and Applications of Automation. IGI Global, 2022. 35-58.