Enhancing Healthcare Management during COVID-19: A Patient-Centric Architectural Framework Enabled by Hyperledger Fabric Blockchain

Abstract

The highly transmissible COVID-19 virus has wreaked havoc on the global economy, health, and lives. The abrupt burst and exponential spread of this pandemic has shown the inadequacies of existing healthcare institutions in handling a public health emergency. As governments around the world strive to re-establish their economies, open workplaces, ensure safe journeys, and return to regular life, they require solutions to reduce losses. The proposed framework provides virtual assistance from various medical practitioners and physicians. Furthermore, it promotes the accuracy of information gathered from COVID-19 patients, which can aid in the launch of a variety of government decisions and public guidelines aimed at combating health exigencies. The authors present a revolutionary blockchain-based solution that builds trust between the medical professionals and patients while preventing accidental coronavisrus transmission. This solution also keeps track of COVID-19 patients and improves EHR management, which can be a viable solution for common EHR challenges such as lowering the risk of patient data loss, maintaining privacy and security, and obtaining immutable consensus on the maintenance of health records, gaps in hospital communication, and inefficient clinical data retrieval methods. This research work describes a COVID-19 patient-centric blockchain-based EHR employing JavaScript-based smart contracts for a decentralized healthcare management system. The proposed Hyperledger fabric and a Composer-based working prototype ensure the model’s security and the authenticity of the health records. The authors used the Hyperledger Caliper benchmarking tool, which measures latency, throughput, resource utilization, etc., under different conditions and control parameters. The findings highlight the importance of the proposed blockchain-enabled architecture in revolutionizing healthcare administration during and after the COVID-19 pandemic, promoting enhanced clinical outcomes and supporting patient-centered care.

Public Health Implications for Effective Community Interventions Based on Hospital Patient Data Analysis Using Deep Learning Technology in Indonesia

“…This work guides the potential use of advanced analysis techniques in conducting more in-depth research on public health using hospital patient data. Hospital patient data have been used in public health research in developing countries [14][15][16]. The study conducted presents an overview of the utilisation of hospital patient data in public health in developing countries.…”

Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

“…The ascendancy of this scientific, evidence-based reasoning carries considerable weight in judicial settings, often tipping the scales in favor of more conclusive, fact-based judgments. Such evidence is often subjected to rigorous standards of validation and reliability, adding a layer of objectivity to legal proceedings that was previously unattainable through anecdotal or circumstantial evidence alone [8,9].…”

“…In light of these complexities, there is an escalating need for a robust framework that seamlessly integrates scientific evidence with traditional investigative data, which includes elements like police reports, eye-witness accounts, and physical evidence, while minimizing human subjectivity. The framework should be capable of synthesizing diverse types of data-from forensic reports and biological samples to witness testimonies and digital footprints-into a cohesive and interpretable format [3,5,8,9]. The key feature of our proposed model is its focus on "interoperability-enhanced" systems.…”