Document Type : Research Article
Authors
1 ECO Collage of Insurance, Allameh Tabataba’i University, Tehran, Iran
2 ECO College of Insurance, Allameh Tabataba’i University, Tehran, Iran
3 ECO college of Insurance, Allameh Tabataba’i University, Tehran, Iran
Abstract
This study aims to examine the function of blockchain technology to detect fraud in healthcare insurance. we consider the literature on fraud in healthcare insurance, blockchain, and smart contracts to to test a newly structured software system based on blockchain technology for this purpose. Different blockchain platforms, consensus algorithms, and structures have been used to pick the proposed system’s best structure based on blockchain. Eventually, the best techniques to put the system to the test and evaluate the findings were assessed. we propose a standardized system, where blockchain is applied to store data and smart contracts are used to automate insurance policies. Furthermore, a web-based application, which acts as core insurance software, is proposed for all stakeholders to communicate with the blockchain and smart contracts. Therefore, the proposed system comprises a blockchain, web app, and standardized smart contracts. The proposed system mainly focuses on fraud detection in insurance claims while maintaining a standard data storage and transfer structure. The system proved to be thriving once claim data can be created, read, and analyzed (i.e. fraudulent data are caught) effectively in a standard way. The web app consists of a front-end and back-end section. The front-end enables users to interact with the proposed system, and the back-end allows the insurance company to store records on the blockchain and increase the chances of detecting fraud in insurance claims, especially Digital Insurance Claims. Finally, a blockchain-based web application that can be used as core insurance software for any healthcare insurance company is proposed.
Keywords
[2] Sparrow, Malcolm K, Health care fraud control: understanding the challenge, JOURNAL
OF INSURANCE MEDICINE-NEW YORK- 28 (1996): 86-96.
[3] A. Rashidian, H. Joudaki, and T. Vian, No evidence of the effect of the interventions to
combat health care fraud and abuse: A systematic review of literature, PLoS One, vol. 7, no.
8, 2012, Art. no. e41988, doi: 10.1371/ journal.pone.0041988.
[4] IBM, Blockchain: The Chain of Trust and its Potential to Transform Healthcare Our Point
of View, 2016, unpublished.
[5] M. Wohrer and U. Zdun, Smart contracts: security patterns in the ethereum ecosystem and
solidity, Blockchain Oriented Software Engineering (IWBOSE) 2018 International Workshop
on, pp. 2-8, 2018.
[6] Mendoza-Tello, J. C., Mendoza-Tello, T., & Mora, H, Blockchain as a Healthcare
Insurance Fraud Detection Tool. In Research and Innovation Forum 2020: Disruptive Technologies in Times of Change, Springer International Publishin, pp. 545-552, (2021).
[7] https://doi.org/10.37896/jxu14.6/096
[8] Mackey, T. K., Miyachi, K., Fung, D., Qian, S., & Short, J. , Combating Health
Care Fraud and Abuse: Conceptualization and Prototyping Study of a Blockchain Antifraud Framework, Journal of medical Internet research, 22(9), e18623, (2020). https:
//doi.org/10.2196/18623
[9] Ismail & Materwala, Article A Review of Blockchain Architecture and Consensus Protocols: Use Cases, Challenges, and Solutions, Symmetry, 11(10), 1198, (2019). https:
//doi.org/10.3390/sym11101198
[10] Ismail, L., Materwala, H., & Zeadally, S., Lightweight blockchain for healthcare, IEEE
Access, 7, 149935-149951, (2019).
[11] Kousaridas, A., Falangitis, S., Magdalinos, P., Alonistioti, N., Dillinger, M., SYSTAS: Density-based algorithm for clusters discovery in wireless networks, In Proceedings
of the 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile
Radio Communications (PIMRC), Hong Kong, China, 30 August2 September 2015; IEEE:
Piscataway, NJ, USA, 2015; pp. 21262131.
[12] Oracle, Available online: https://cloud.oracle.com/en_US/blockchain, (accessed on 20
January 2022).
[13] L. Ismail and S. Zeadally, Healthcare Insurance Frauds: Taxonomy and Blockchain-Based
Detection Framework (Block-HI), in IT Professional, vol. 23, no. 4, pp. 36-43, 1 July-Aug.
2021, doi:10.1109/MITP.2021.3071534.
[14] Mackey, T. K., Miyachi, K., Fung, D., Qian, S., & Short, J., Combating Health Care
Fraud and Abuse: Conceptualization and Prototyping Study of a Blockchain Antifraud
Framework, Journal of medical Internet research, 22(9), e18623, (2020).
[15] G. Saldamli, V. Reddy, K. S. Bojja, M. K. Gururaja, Y. Doddaveerappa and L.
Tawalbeh, Health Care Insurance Fraud Detection Using Blockchain, Seventh International Conference on Software Defined Systems (SDS), 2020, pp. 145-152, (2020). doi:
10.1109/SDS49854.2020.9143900
[16] W. Liu, Q. Yu, Z. Li, Z. Li, Y. Su and J. Zhou, A Blockchain-Based System for Anti-Fraud
of Healthcare Insurance, IEEE 5th International Conference on Computer and Communications (ICCC), pp. 1264-1268, (2019).
[17] Mohan T., Praveen K., Fraud Detection in Medical Insurance Claim with Privacy Preserving Data Publishing in TLS-N Using Blockchain. In: Singh M., Gupta P., Tyagi V.,
Flusser J., Oren T., Kashyap R. (eds) Advances in Computing and Data Sciences. ICACDS ¨
2019, Communications in Computer and Information Science, vol 1045. Springer, Singapore.
https://doi.org/10.1007/978-981-13-9939-8_19
[18] Mendoza-Tello J.C., Mendoza-Tello T., Mora H., Blockchain as a Healthcare Insurance Fraud Detection Tool. In: Visvizi A., Lytras M.D., Aljohani N.R. (eds) Research and
Innovation Forum 2020. RIIFORUM 2020., Springer Proceedings in Complexity. Springer,
Cham. https://doi.org/10.1007/978-3-030-62066-0_41
[19] Rui Roriz, Jose Luis Pereira ´ , Avoiding Insurance Fraud: A Blockchain-based Solution for
the Vehicle Sector, Procedia Computer Science, Volume 164, 2019, Pages 211-218.
)