Blockchain-based electronic health system growth is hindered by privacy, confidentiality, and security. By protecting against them, this research aims to develop cybersecurity measurement approaches to ensure the security and privacy of patient information using blockchain technology in healthcare. Blockchains need huge resources to store big data. This paper presents an innovative solution, namely patient-centric healthcare data management (PCHDM). It comprises the following: (i) in an on-chain health record database, hashes of health records are stored as health record chains in Hyperledger fabric, and (ii) off-chain solutions that encrypt actual health data and store it securely over the interplanetary file system (IPFS) which is the decentralized cloud storage system that ensures scalability, confidentiality, and resolves the problem of blockchain data storage. A security smart contract hosted through container technology with Byzantine Fault Tolerance consensus ensures patient privacy by verifying patient preferences before sharing health records. The Distributed Ledger technology performance is tested under hyper ledger caliper benchmarks in terms of transaction latency, resource utilization, and transaction per second. The model provides stakeholders with increased confidence in collaborating and sharing their health records.

Multi-stakeholder and organizational involvement is an integral part of the medicine supply chain. Keeping track of the activities associated with medical products is difficult when the system is complex. Their complexity limits transparency and data provenance. Deficiencies within existing supply chains result in the counterfeiting of drugs, illegal imports, and inefficient operations. Due to these limitations, product integrity is compromised, resulting in product wastage. Visibility of the entire product supply chain is crucial for the pharmaceutical industry in terms of product safety and reduction of manufacturing costs. The Cloud-based Blockchain-powered architecture of the system provides a platform for addressing the need of pharma-material traceability, data storage, privacy of data, and quality assurance. This framework comprises of the identification of activities through tagging, information sharing in a secure environment; cloud-based storage using an off-chain Interplanetary File System (IPFS) and an on-chain couch DB; and access to this information that is controlled by the system's regulator. Electronic drug records will be accessed via a smart contract in Hyperledger Blockchain. The system assists in identifying false and cross-border products through the manufacturer and country of origin. A scan will identify counterfeit medications, showing that they are unauthorized products which may pose a risk to patients. Our experiments demonstrated the efficiency and usability of the design platform. Finally, we benchmarked the system using Hyperledger Caliper.

Text mining, also known as text analysis, is the process of converting unstructured text data into meaningful and functional information. Text mining uses different AI technologies to automate data and generate valuable insights, allowing enterprises to make data-based decisions. Text mining enables the user to extract important content from text data sets. Text analysis encourages machine learning ability for research areas such as medical and pharmaceutical innovation fields. Apart from this, text analysis converts inaccessible data into a structured format, which can be used for further analysis. Text analysis emphasizes facts and relationships from large data sets. This information is extracted and converted into structured data for visualization, analysis, and integration as structured data and refines the information using machine-learning methods. Like most things related to Natural Language Processing, text mining can seem like a difficult concept to understand. But the fact is, it does not have to be. This research article will go through the basics of text mining, clarify its different methods and techniques, and make it easier to understand how it works. We implemented Latent Dirichlet Allocation techniques for mining the data from the data set; it works properly and will be in future development data mining techniques.

Prescription drug abuse and doctor shopping are major problems in the healthcare field that have led to a significant number of deaths as a consequence of drug misuse. Doctors prescribe too much fentanyl, Demerol, and sleeping pills, along with anxiety medications, that are legal and frequently abused. In order to combat prescription drug abuse, it is imperative to develop an efficient monitoring and identification system. Blockchain technology is a promising solution to tracking prescriptions because of its decentralization and auditability, which allow medical records to be more secure as well as more reliable. Blockchain technology can help ensure the authenticity, integrity, and transparency of drug distribution between pharmacies and doctors. In this paper, we aim to develop a system of managing the integrity of the drug supply chain by integrating Hyperledger Fabric blockchain technology with Interplanetary File System (IPFS). Because of its secure encryption framework and anti-fraud and anti-forgery measures, it has prevented prescription abuse. A smart health care ecosystem is created by using smart contracts to track drugs on the blockchain. In addition, by using this approach we are able to recognize and track drugs that may be misused by individuals who shop for doctors and hop between pharmacies. The cryptographically safe and reliable framework created by Healthcare Chain can be used by doctors, pharmacists, and patients to improve how opioid prescriptions and medication are administered.

Cloud computing poses a challenge to the healthcare infrastructure, as it affects privacy, confidentiality, and security rules concerning large binary objects such as x-rays and CT scan reports. However, health records are stored and accessed using an encryption hash which is stored in the interplanetary file system (IPFS), called a peer-to-peer system. But the patient’s data is sold, share for research purposes by their healthcare providers without their knowledge as it affects their privacy and security. In the healthcare industry today, customers face the issue of health record that lacks interoperability, resulting in difficulty aggregating and examining patient data. The objective of this research is to develop cybersecurity measurement approaches that ensure patient information security by protecting against cyber threats using blockchain technology based on healthcare IT. Consequently, this paper proposes an innovative solution to the problem, namely Patient-centric healthcare data management (PCHDM). It was built using IPFS, a permissioned distributed ledger system that uses Hyperledger Fabric, which stores health records, but only with the permission of the owner. A unique cryptographic public key encryption algorithm is used to encrypt IPFS data to build an electronic health record blockchain system. Our platform offers two types of solutions: (i) a solution that utilizes a database of hyper ledger fabric, which is an on-chain database, (ii) off-chain solutions which encrypt data and store it securely off-chain using IPFS. A robust blockchain solution for PCHDM will be created by encrypting the data stored in IPFS using appropriate public key cryptographic algorithms. To determine which blocks should be incorporated into the blockchain, the Byzantine Fault Tolerance is applied in the health chain architectural model. This system hosts smart contracts and application logic as well as smart contracts known as "chain code" via container technology. As part of this research, health record hashes were stored on the blockchain and the actual health data was stored off-chain in IPFS, which is the decentralized cloud storage system that achieves scalability. Due to the encryption of healthcare records with a hash, this model proves that unauthorized access is impossible because the records are more scalable, interoperable, and reliable. Stakeholders are more confident in collaborating and sharing their medical records with this model.