scholarly journals Privacy Preserving model for patient centric health record management using chaincode

Author(s):  
vinodhini mani ◽  
Prakash M

Abstract 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.

2012 ◽  
pp. 1387-1402
Author(s):  
Mary Kuehler ◽  
Nakeisha Schimke ◽  
John Hale

Electronic Health Record (EHR) systems are a powerful tool for healthcare providers and patients. Both groups benefit from unified, easily accessible record management; however, EHR systems also bring new threats to patient privacy. The reach of electronic patient data extends far beyond the healthcare realm. Patients are managing their own health records through personal health record (PHR) service providers, and businesses outside of the healthcare industry are finding themselves increasingly linked to medical data. The Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule and other regulatory measures establish baseline standards for protecting patient privacy, but the inclusion of medical images in patient records presents unique challenges. Medical images often require specialized management tools, and some medical images may reveal a patient’s identity or medical condition through re-linkage or inherent identifiability. After exploring EHR systems in-depth and reviewing health information policy, the chapter explores how privacy challenges associated with EHR systems and medical images can be mitigated through the combined efforts of technology, policy, and legislation designed to reduce the risk of re-identification.


2019 ◽  
Author(s):  
Özlem Özkan ◽  
Yeşim Aydin Son ◽  
Arsev Umur Aydinoğlu

AbstractWith the increasing use of genetic testing and applications of bioinformatics in healthcare, genetic and genomic data needs to be integrated into electronic health systems. We administered a descriptive survey to 174 participants to elicit their views on the privacy and security of mobile health record systems and inclusion of their genetic data in these systems. A survey was implemented online and on site in two genetic diagnostic centres. Nearly half of the participants or their close family members had undergone genetic testing. Doctors constituted the only profession group that people trusted for the privacy of their health and genetic data; however, people chose to limit even their doctor’s access to their genetic/health records. The majority of the respondents preferred to keep full access for themselves. Several participants had negative experience or preconceptions about electronic health records: the medical reports of 9.7% of the respondents had been used or released without their consent, 15.1% stated that they avoided being tested due to violation risks, and 3.5% asked their doctors to enter a less embarrassing health status in their records. The participants wanted to see some regulations and security measurements before using any system for their health/genetic data. In addition, significantly more participants stating that storing genetic data in a mobile system was riskier compared to other health data. Furthermore, the comparative analysis revealed that being young, being a woman and having higher education were associated with having greater privacy concerns.


Author(s):  
Mary Kuehler ◽  
Nakeisha Schimke ◽  
John Hale

Electronic Health Record (EHR) systems are a powerful tool for healthcare providers and patients. Both groups benefit from unified, easily accessible record management; however, EHR systems also bring new threats to patient privacy. The reach of electronic patient data extends far beyond the healthcare realm. Patients are managing their own health records through personal health record (PHR) service providers, and businesses outside of the healthcare industry are finding themselves increasingly linked to medical data. The Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule and other regulatory measures establish baseline standards for protecting patient privacy, but the inclusion of medical images in patient records presents unique challenges. Medical images often require specialized management tools, and some medical images may reveal a patient’s identity or medical condition through re-linkage or inherent identifiability. After exploring EHR systems in-depth and reviewing health information policy, the chapter explores how privacy challenges associated with EHR systems and medical images can be mitigated through the combined efforts of technology, policy, and legislation designed to reduce the risk of re-identification.


10.29007/2x3r ◽  
2019 ◽  
Author(s):  
Suboh Alkhushayni ◽  
Du'A Al-Zaleq ◽  
Nadine L Gadjou Kengne

Blockchain technology is on the cusp of revolutionizing the way we handle healthcare data, in term of storage and utilization. The main goal is to empower patients to be the center of their own health record so that, the patient doesn't have to rely on different institutions or hospitals they might visit. Blockchain technology and smart contracts provide an interesting and innovative way to keep track of Electronic Health Records (EHRs). This technology could help the patients to have better control of their own data. Health professionals and institutions, such as hospitals, could have access to patient’s data owned by other institutions. In the present article, we discuss how blockchain technologies can be used to handle EHR while improving the efficiency of operations through streamlining processes and transparency. We propose an architecture to manage and share healthcare data among different organizations. The proposed work could significantly reduce the time needed to share patient data among different health organizations and reduce the overall cost.


Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3003
Author(s):  
Vinodhini Mani ◽  
Prakash Manickam ◽  
Youseef Alotaibi ◽  
Saleh Alghamdi ◽  
Osamah Ibrahim Khalaf

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.


2020 ◽  
Author(s):  
Tamadur Shudayfat ◽  
Çağdaş Akyürek ◽  
Noha Al-Shdayfat ◽  
Hatem Alsaqqa

BACKGROUND Acceptance of Electronic Health Record systems is considered an essential factor for an effective implementation among the Healthcare providers. In an attempt to understand the healthcare providers’ perceptions on the Electronic Health Record systems implementation and evaluate the factors influencing healthcare providers’ acceptance of Electronic Health Records, the current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. OBJECTIVE The current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. METHODS A quantitative cross-sectional survey design was used, in which 319 healthcare providers from five public hospital participated in the present study. Data was collected using a self-administered questionnaire, which was based on the Technology Acceptance Model. RESULTS Jordanian healthcare providers demonstrated positive perceptions of the usefulness and ease of use of Electronic Health Record systems, and subsequently, they accepted the technology. The results indicated that they had a significant effect on the perceived usefulness and perceived ease of use of Electronic Health Record, which in turn was related to positive attitudes towards Electronic Health Record systems as well as the intention to use them. CONCLUSIONS User attributes, organizational competency, management support and training and education are essential variables in predicting healthcare provider’s acceptance toward Electronic Health records. These findings should be considered by healthcare organizations administration to introduce effective system to other healthcare organizations.


2021 ◽  
Vol 13 (11) ◽  
pp. 5889
Author(s):  
Faiza Hashim ◽  
Khaled Shuaib ◽  
Farag Sallabi

Electronic health records (EHRs) are important assets of the healthcare system and should be shared among medical practitioners to improve the accuracy and efficiency of diagnosis. Blockchain technology has been investigated and adopted in healthcare as a solution for EHR sharing while preserving privacy and security. Blockchain can revolutionize the healthcare system by providing a decentralized, distributed, immutable, and secure architecture. However, scalability has always been a bottleneck in blockchain networks due to the consensus mechanism and ledger replication to all network participants. Sharding helps address this issue by artificially partitioning the network into small groups termed shards and processing transactions parallelly while running consensus within each shard with a subset of blockchain nodes. Although this technique helps resolve issues related to scalability, cross-shard communication overhead can degrade network performance. This study proposes a transaction-based sharding technique wherein shards are formed on the basis of a patient’s previously visited health entities. Simulation results show that the proposed technique outperforms standard-based healthcare blockchain techniques in terms of the number of appointments processed, consensus latency, and throughput. The proposed technique eliminates cross-shard communication by forming complete shards based on “the need to participate” nodes per patient.


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