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Issues And Trends In Healthcare Delivery System01:29

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Data driven healthcare insurance system using machine learning and blockchain technologies.

Irum Matloob1, Shoab Khan2, Bushra Bashir1

  • 1Department of Software Engineering, Fatima Jinnah Women University, Rawalpindi, Pakistan.

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|September 24, 2025
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Summary
This summary is machine-generated.

This study introduces an intelligent system for healthcare recommendations and insurance fraud detection, combining machine learning and blockchain for secure claims and improved service quality. The system successfully reduced hospital expenses and enhanced transparency in insurance processes.

Keywords:
Applied machine learningArtificial intelligenceBlockchainFraud detectionHealth informaticsSecurity and privacy

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Blockchain Technology

Background:

  • Healthcare insurance fraud is a growing concern, necessitating intelligent systems for monitoring services and preventing fraudulent activities.
  • Existing systems lack comprehensive features for both quality-based healthcare recommendations and automated, secure insurance claims processing.

Purpose of the Study:

  • To develop an intelligent system for recommending doctors and insurance plans based on service quality.
  • To integrate blockchain technology for secure and transparent automation of healthcare insurance claims reimbursement.
  • To combat healthcare insurance fraud and reduce associated expenditures.

Main Methods:

  • The system combines Singular Value Decomposition (SVD), K-Nearest Neighbors (KNN)-based collaborative filtering, item-based collaborative filtering, Term Frequency-Inverse Document Frequency (TF-IDF) for content-based filtering, and K-means clustering.
  • Cosine similarity is used to measure patient-doctor similarity for refined recommendations.
  • Smart contract technology on the Ethereum blockchain is employed for automating insurance claims reimbursement.

Main Results:

  • The recommendation system achieved a Root Mean Square Error (RMSE) of 0.478 and a Mean Absolute Error (MAE) of 0.0422.
  • The proposed system led to a reduction in the overall expenditure of a local hospital.
  • Blockchain integration enhanced security and transparency, significantly lowering healthcare fraud incidents.

Conclusions:

  • The developed intelligent system effectively recommends healthcare providers and optimizes insurance plans, leading to cost savings.
  • Blockchain technology provides a secure, transparent, and efficient platform for healthcare insurance claims, mitigating fraud.
  • This novel system addresses a critical need in Pakistan for a comprehensive healthcare recommendation and fraud prevention solution.