scholarly journals A Risk Analysis on Blockchain Technology Usage for Electronic Health Records

2021 ◽  
pp. 1-16
Author(s):  
Christian Ploder ◽  
Teresa Spiess ◽  
Reinhard Bernsteiner ◽  
Thomas Dilger ◽  
Rebecca Weichelt
Keyword(s):  
Electronic Health Records ◽  
Technology Use ◽  
Data Exchange ◽  
Single Point ◽  
Health Data ◽  
Health Records ◽  
Blockchain Technology ◽  
Qualitative Interview Study ◽  
Wide Range ◽  
Electronic Health

Health data is one of the most valuable data and highly sensitive. Its careful handling is essential in today' s digitalized world and cloud technology use for sharing. Health Information Systems facilitate the storage and accessibility of health data for better care along the patient path. As the integration of all historical patient data, the Electronic Health Record is at the heart of health data management. The centralization of stored health data represents a single point of failure and trust, making data exchange across institutions difficult and insecure. Blockchain technology builds on consensus mechanisms and immutable chains of blocks for validating and securing data transactions as a modern decentralized approach. The application of blockchain technology for Electronic Health Records is promising but still a young concept. Due to the wide range of discussion, this paper aims at identifying risks by using blockchain technology in the eHealth sector. Based on a systematic literature review, various authors' argumentations and findings are examined and concluded to set up the empirical study. The semistructured qualitative interview study aims to find out the threats of blockchain. The paper concludes with an overall discussion and some implementation recommendations.

scholarly journals Healthchain: A novel framework on privacy preservation of electronic health records using blockchain technology

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243043
Author(s):  
Shekha Chenthara ◽  
Khandakar Ahmed ◽  
Hua Wang ◽  
Frank Whittaker ◽  
Zhenxiang Chen
Keyword(s):  
Electronic Health Records ◽  
Data Security ◽  
Data Privacy ◽  
Health Data ◽  
Cyber Attacks ◽  
Security Risk ◽  
Patient Privacy ◽  
Health Records ◽  
Blockchain Technology ◽  
Electronic Health

The privacy of Electronic Health Records (EHRs) is facing a major hurdle with outsourcing private health data in the cloud as there exists danger of leaking health information to unauthorized parties. In fact, EHRs are stored on centralized databases that increases the security risk footprint and requires trust in a single authority which cannot effectively protect data from internal attacks. This research focuses on ensuring the patient privacy and data security while sharing the sensitive data across same or different organisations as well as healthcare providers in a distributed environment. This research develops a privacy-preserving framework viz Healthchain based on Blockchain technology that maintains security, privacy, scalability and integrity of the e-health data. The Blockchain is built on Hyperledger fabric, a permissioned distributed ledger solutions by using Hyperledger composer and stores EHRs by utilizing InterPlanetary File System (IPFS) to build this healthchain framework. Moreover, the data stored in the IPFS is encrypted by using a unique cryptographic public key encryption algorithm to create a robust blockchain solution for electronic health data. The objective of the research is to provide a foundation for developing security solutions against cyber-attacks by exploiting the inherent features of the blockchain, and thus contribute to the robustness of healthcare information sharing environments. Through the results, the proposed model shows that the healthcare records are not traceable to unauthorized access as the model stores only the encrypted hash of the records that proves effectiveness in terms of data security, enhanced data privacy, improved data scalability, interoperability and data integrity while sharing and accessing medical records among stakeholders across the healthchain network.

The process of sourcing and preparing electronic health records data to implement a machine-learning algorithm for early identification of maternal cardiovascular risk (Preprint)

2021 ◽  
Author(s):  
Nawar Shara ◽  
Kelley M. Anderson ◽  
Noor Falah ◽  
Maryam F. Ahmad ◽  
Darya Tavazoei ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cardiovascular Risk ◽  
Electronic Health Records ◽  
Patient Care ◽  
Early Identification ◽  
Health Data ◽  
Patient Specific ◽  
Patient Records ◽  
Health Records ◽  
Electronic Health

BACKGROUND Healthcare data are fragmenting as patients seek care from diverse sources. Consequently, patient care is negatively impacted by disparate health records. Machine learning (ML) offers a disruptive force in its ability to inform and improve patient care and outcomes [6]. However, the differences that exist in each individual’s health records, combined with the lack of health-data standards, in addition to systemic issues that render the data unreliable and that fail to create a single view of each patient, create challenges for ML. While these problems exist throughout healthcare, they are especially prevalent within maternal health, and exacerbate the maternal morbidity and mortality (MMM) crisis in the United States. OBJECTIVE Maternal patient records were extracted from the electronic health records (EHRs) of a large tertiary healthcare system and made into patient-specific, complete datasets through a systematic method so that a machine-learning-based (ML-based) risk-assessment algorithm could effectively identify maternal cardiovascular risk prior to evidence of diagnosis or intervention within the patient’s record. METHODS We outline the effort that was required to define the specifications of the computational systems, the dataset, and access to relevant systems, while ensuring data security, privacy laws, and policies were met. Data acquisition included the concatenation, anonymization, and normalization of health data across multiple EHRs in preparation for its use by a proprietary risk-stratification algorithm designed to establish patient-specific baselines to identify and establish cardiovascular risk based on deviations from the patient’s baselines to inform early interventions. RESULTS Patient records can be made actionable for the goal of effectively employing machine learning (ML), specifically to identify cardiovascular risk in pregnant patients. CONCLUSIONS Upon acquiring data, including the concatenation, anonymization, and normalization of said data across multiple EHRs, the use of a machine-learning-based (ML-based) tool can provide early identification of cardiovascular risk in pregnant patients. CLINICALTRIAL N/A

scholarly journals Facilitating the ethical use of health data for the benefit of society: electronic health records, consent and the duty of easy rescue

2016 ◽  
Vol 374 (2083) ◽  
pp. 20160130 ◽  
Author(s):  
Sebastian Porsdam Mann ◽  
Julian Savulescu ◽  
Barbara J. Sahakian
Keyword(s):  
Informed Consent ◽  
Electronic Health Records ◽  
Data Science ◽  
Real Life ◽  
Health Data ◽  
Sensitive Information ◽  
Minimal Risk ◽  
Sensitive Data ◽  
Health Records ◽  
Electronic Health

Advances in data science allow for sophisticated analysis of increasingly large datasets. In the medical context, large volumes of data collected for healthcare purposes are contained in electronic health records (EHRs). The real-life character and sheer amount of data contained in them make EHRs an attractive resource for public health and biomedical research. However, medical records contain sensitive information that could be misused by third parties. Medical confidentiality and respect for patients' privacy and autonomy protect patient data, barring access to health records unless consent is given by the data subject. This creates a situation in which much of the beneficial records-based research is prevented from being used or is seriously undermined, because the refusal of consent by some patients introduces a systematic deviation, known as selection bias, from a representative sample of the general population, thus distorting research findings. Although research exemptions for the requirement of informed consent exist, they are rarely used in practice due to concerns over liability and a general culture of caution. In this paper, we argue that the problem of research access to sensitive data can be understood as a tension between the medical duties of confidentiality and beneficence. We attempt to show that the requirement of informed consent is not appropriate for all kinds of records-based research by distinguishing studies involving minimal risk from those that feature moderate or greater risks. We argue that the duty of easy rescue—the principle that persons should benefit others when this can be done at no or minimal risk to themselves—grounds the removal of consent requirements for minimally risky records-based research. Drawing on this discussion, we propose a risk-adapted framework for the facilitation of ethical uses of health data for the benefit of society. This article is part of the themed issue ‘The ethical impact of data science’.

scholarly journals Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study

10.2196/13585 ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. e13585 ◽  
Author(s):  
Jan Heinrich Beinke ◽  
Christian Fitte ◽  
Frank Teuteberg
Keyword(s):  
Electronic Health Records ◽  
Data Security ◽  
Design Science ◽  
Science Research ◽  
Design Science Research ◽  
Future Research ◽  
Health Records ◽  
Blockchain Technology ◽  
Recommendations For Action ◽  
Electronic Health

Background Data security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs. Objective This study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs. Methods The blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants. Results We identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice. Conclusions Our findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.

scholarly journals Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study (Preprint)

2019 ◽  
Author(s):  
Jan Heinrich Beinke ◽  
Christian Fitte ◽  
Frank Teuteberg
Keyword(s):  
Electronic Health Records ◽  
Data Security ◽  
Design Science ◽  
Science Research ◽  
Design Science Research ◽  
Future Research ◽  
Health Records ◽  
Blockchain Technology ◽  
Recommendations For Action ◽  
Electronic Health

BACKGROUND Data security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs. OBJECTIVE This study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs. METHODS The blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants. RESULTS We identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice. CONCLUSIONS Our findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.

scholarly journals A Proposed Electronic Health Record Content Structure Based on Clinical Organizations Survey

2014 ◽  
Vol 15 (13) ◽  
pp. 5233-5246 ◽  
Author(s):  
Dr. Ayman E. Khedr ◽  
Fahad Kamal Alsheref
Keyword(s):  
Data Structure ◽  
Electronic Health Records ◽  
Electronic Health Record ◽  
Clinical Data ◽  
Data Exchange ◽  
Medical Information System ◽  
Health Record ◽  
Medical Organization ◽  
Health Records ◽  
Electronic Health

Computer systems and communication technologies made a strong and influential presence in the different fields of medicine. The cornerstone of a functional medical information system is the Electronic Health Records (EHR) management system. Several electronic health records systems were implemented in different states with different clinical data structures that prevent data exchange between systems even in the same state. This leads to the important barrier in implementing EHR system which is the lack of standards of EHR clinical data structure. In this paper we made a survey on several in international and Egyptian medical organization for implementing electronic health record systems for finding the best electronic health record clinical data structure that contains all patient’s medical data. We proposed an electronic health record system with a standard clinical data structure based on the international and Egyptian medical organization survey and with avoiding the limitations in the other electronic health record that exists in the survey.

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