HealthSureChain: A Smart Contract-Based Decentralized Framework for Healthcare Insurance Claim Processing and Predictive Fund Allocation

Abstract

The traditional process of handling health insurance claims involves centralized systems and manual verification processes that are associated with high chances of delays, lack of transparency, and even fraud. Additionally, the lack of a secure and tamper-proof data sharing process between insurance companies, hospitals, and patients. This paper proposes a blockchain technology-based solution for the efficient management of health insurance claims, which is named HealthSureChainand is developed as a decentralized application on the permissioned Ethereum blockchain technology. Smart contract is used to automate the process of policy registration, premium payment, claims submission, eligibility checking, and claims approval. Medical records and patient data are stored in a secure manner through IPFS storage, while the hash of the data is stored on the blockchain for checking purposes. A predictive analytics component has been used to determine the future reserve fund requirements.

Introduction

The paper presents HealthSureChain, a decentralized health insurance claim processing system designed to address inefficiencies, fraud risks, and lack of transparency in traditional centralized insurance workflows.

Conventional systems rely on intermediaries and manual verification, leading to slow processing, high operational costs, vulnerability to fraud, and poor data security. To overcome these issues, HealthSureChain uses a permissioned Ethereum blockchain with smart contracts to automate key processes such as registration, policy management, claim verification, and fund disbursement. Medical records are stored securely off-chain using IPFS, while only cryptographic hashes are stored on-chain to ensure integrity and privacy.

The system includes multiple smart contracts handling role management, policy storage, claim processing, document linking, and fund allocation. A Flask-based middleware connects blockchain with off-chain components, while machine learning (XGBoost regression) is used to predict future claim reserves and support financial planning. A risk-aware formula adjusts reserves using predicted claims, volatility, and safety factors, with monitoring based on depletion ratios.

Security is enhanced through blockchain immutability, encrypted document storage, and role-based access control. A private Ethereum network ensures controlled participation and reduced fraud.

Experimental results show that the system successfully automates end-to-end claim processing, enables real-time tracking for patients and insurers, and achieves strong forecasting performance (R² ≈ 0.94–0.95 with low error rates). Overall, the approach improves transparency, efficiency, fraud resistance, and financial planning compared to traditional insurance systems.

Conclusion

In this paper, a new health insurance claim management system called HealthSureChain was introduced, which uses a blockchain-based system to promote transparency, security, automation, and economic efficiency. In this system, a permissioned Ethereum network is used to execute a series of smart contracts that are used to automate participant registration, policy management, claim verification, and settlement. In order to overcome the problem of storage that exists with the blockchain, a new method of storing the encrypted medical information using the IPFS has been proposed, and a cryptographic hash has been stored on the blockchain. In addition, a predictive reserve management module using XGBoost regression is used to predict monthly claim expenses and determine the reserve buffers. HealthSureChain provides a secure, scalable, and financially intelligent solution for decentralized health insurance claim management.

References

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Copyright

Copyright © 2026 Poojashree K, Shekinah Sharon P, Thasweeha Juhei. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.