Abstract

The recent advances in information management systems coupled with machine learning algorithms paved the way for a significant revolution in animal healthcare industries. However, the data in such systems suffer from various challenges such as security, reliability, and convenience, to name a few. Traditional systems are not useful to meet these critical issues because these systems have not a consistent structure for data security and reliability policies. Therefore, a new solution is required to enhance data accessibility and should regulate government security policies to ensure the accountability of the usage of the medical records system. Moreover, it is also required to analyze historical data of veterinary clinic using data mining and machine learning techniques to predict the future appointments scheduling requests, which is essential for veterinary management to drive better future decisions, for instance, future demands of medical supplies and to plan veterinary medical staff, etc. This paper aims to fill the gap by proposing a novel blockchain-based reliable and intelligent veterinary information management system (RIVIMS) using smart contract and machine learning techniques. The proposed RIVIMS consists of two main modules; blockchain-based secured veterinary information management, data and predictive analytics modules. First, a blockchain-based secure and reliable veterinary clinic information management system is developed using Hyperledger Fabric. Second, a smart contract enabled data, and predictive analytics modules are developed using permissioned blockchain framework. The data and predictive modules aim to analyze veterinary clinic patients appointments data in order to discover underlying patterns and build a robust prediction model using machine learning algorithms. The data and predictive helps veterinary management to drive better future business decisions to provide better healthcare services to veterinary patients. Hyperledger Caliper is used as a benchmark tool to evaluate the performance of the developed blockchain-based system in terms of transaction per second, transaction success rate, transaction throughput, and transaction latency. Furthermore, machine learning performance measures have utilized, such as MAE, RMSE, and R2 score to evaluate the overall performance of the prediction model. The experimental results demonstrate the effectiveness and robustness of the proposed RIVIMS.

Highlights

  • IntroductionTime, which is varying from remote access to healthcare data or exchanging medical records of the patients electronically [1], [2]

  • The proposed reliable and intelligent veterinary information management system (RIVIMS) consists of two main modules; (i) a blockchain-based reliable and secure veterinary information management system, and (ii) a smart contract enabled data and predictive analytics modules using DM and machine learning (ML) techniques for predicting frequency of appointments scheduling requests

  • The proposed RIVIMS is based on the permissioned blockchain network, where all nodes of the entire network required authentication to participate in a decentralized blockchain network

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Summary

Introduction

Time, which is varying from remote access to healthcare data or exchanging medical records of the patients electronically [1], [2]. E-health technology enables information technology and computer networks to improve healthcare quality and safety of the patient’s sensitive data, which enables patients and the healthcare industry to drive effective. EMR is a digital version of the medical records related to patient’s medical history data. It helps healthcare organizations to track patient’s data and ensure preventive screenings for patients. The lack of effective management and sharing leads the personal medical data of the patients to be fragmented rather than unitive [4]. There are many cases reported related to unauthorized access of the medical data and leaking of personal medical data from the existing EMR systems [5]. It is required to develop a close private network to enhance data security, data consistency and reliability of personal healthcare data

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