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Hyperledger Fabric Blockchain: Secure and Efficient Solution for electronic health records

Computers, Materials & Continua 2021年第8期68卷 2377-2397页

作者： Mueen Uddin M.S.Memon Irfana Memon Imtiaz Ali Jamshed Memon Maha Abdelhaq Raed Alsaqour Faculty of Science Universiti Brunei DarusslamGadongBE1410Negara Brunei Darussalam CSE Department QUESTNawabshahPakistan School of Computing and Mathematics Ulster UniversityJordanstown CampusNewtownabbeyBT370QBUK Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic UniversityRiyadh93499Saudi Arabia

Background:electronic health Record(EHR)systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients ***,the existing EHR systems mostly lack in providing appropriate security,entrusted access control and handling privacy and secrecy issues and challenges in current hospital ***:To solve this delicate problem,we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR ***:In our EHR blockchain system,Peer nodes from various organizations(stakeholders)create a ledger network,where channels are created to enable secure and private communication between different stakeholders on the ledger *** patients and other stakeholders are identified and registered on the network by unique digital certificates issued by membership service provider(MSP)component of the fabric ***:We created and implemented different Chaincodes to handle the business logic for executing separate EHR transactions on the *** proposed fabric architecture provides a secure,transparent and immutable mechanism to store,share and exchange EHRs in a peer-to-peer network of different healthcare *** ensures interoperability,scalability and availability in adapting the existing EHRs for strengthening and providing an effective and secure method to integrate and manage patient records among medical institutions in the healthcare ecosystem.

关键词： electronic health records blockchain hyperledger fabric patient data privacy private permissioned blockchain healthcare ecosystem

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A Secure Signcryption Scheme for electronic health records Sharing in Blockchain

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Computer Systems Science & Engineering 2021年第5期37卷 265-281页

作者： Xizi Peng Jinquan Zhang Shibin Zhang Wunan Wan Hao Chen Jinyue Xia School of Cybersecurity Chengdu University of Information TechnologyChengdu610225China International Business Machines Corporation(IBM) New York10041NY212USA

In the existing electronic health records(EHRs),the medical information of patients is completely controlled by various medical *** such,patients have no dominant power over their own *** personal data are not only inconvenient to access and share,but are also prone to cause privacy *** blockchain technology provides a new development direction in the medical ***-based EHRs are characterized by decentralization,openness and non-tampering of records,which enable patients to better manage their own *** order to better protect the privacy of patients,only designated receivers can access EHRs,and receivers can authenticate the sharer to ensure that the EHRs are real and *** this study,we propose an identity-based signcryption scheme with multiple authorities for multiple receivers,which can resist N-1 collusion attacks among N *** addition,the identity information of receivers is anonymous,so the relationship between them and the sharer is not *** the random oracle model,it was proved that our scheme was secure and met the unforgeability and confidentiality requirements of ***,we evaluated the performance of the scheme and found that it had the moderate signcryption efficiency and excellent signcryption attributes.

关键词： electronic health records blockchain identity-based signcryption multiple authorities multiple receivers

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Deletion and Recovery Scheme of electronic health records Based onMedical Certificate Blockchain

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Computers, Materials & Continua 2023年第7期76卷 849-859页

作者： Baowei Wang Neng Wang Yuxiao Zhang Zenghui Xu Junhao Zhang School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044JiangsuChina Engineering Research Center of Digital Forensics Ministry of EducationNanjing210044JiangsuChina

The trusted sharing of electronic health records(EHRs)can realize the efficient use of medical data *** speaking,EHRs are widely used in blockchain-based medical data *** are valuable private assets of patients,and the ownership belongs to *** recent research has shown that patients can freely and effectively delete the EHRs stored in hospitals,it does not address the challenge of record sharing when patients revisit *** order to solve this problem,this paper proposes a deletion and recovery scheme of EHRs based on Medical Certificate *** paper uses cross-chain technology to connect the Medical Certificate Blockchain and the Hospital Blockchain to real-ize the recovery of deleted *** the same time,this paper uses the Medical Certificate Blockchain and the InterPlanetary File System(IPFS)to store Personal health records,which are generated by patients visiting different medical *** addition,this paper also combines digital watermarking technology to ensure the authenticity of the restored electronic medical *** the combined effect of blockchain technology and digital watermarking,our proposal will not be affected by any other rights throughout the *** analysis and security analysis illustrate the completeness and feasibility of the scheme.

关键词： electronic health records cross-chain medical certificate blockchain data deletion and recovery

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Nursing decision support system:application in electronic health records

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Frontiers of Nursing 2020年第3期7卷 185-190页

作者： Mi-Zhi Wu Hong-Ying Pan Zhen Wang School of Nursing Sciences Huzhou UniversityHuzhouZhejiang 313000China Nursing Department of Sir Run Run Shaw Hospital Medical School Zhejiang UniversityHangzhouZhejiang 310017China School of Medicine East Campus of Huzhou UniversityHuzhouZhejiang 313000China

The clinical decision support system makes electronic health records(EHRs)structured,intelligent,and *** nursing decision support system(NDSS)is based on clinical nursing guidelines and nursing process to provide intelligent suggestions and *** impact on nurses’work is mainly in shortening the recording time,improving the quality of nursing diagnosis,reducing the incidence of nursing risk events,and so ***,there is no authoritative standard for the NDSS at home and *** review introduces development and challenges of EHRs and recommends the application of the NDSS in EHRs,namely the nursing assessment decision support system,the nursing diagnostic decision support system,and the nursing care planning decision support system(including nursing intervene),hoping to provide a new thought and method to structure impeccable EHRs.

关键词： electronic health records decision support systems clinical nursing process review

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Practical use of electronic health records among patients with diabetes in scientific research

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Chinese Medical Journal 2020年第10期133卷 1224-1230页

作者： Yun Shen Jian Zhou Gang Hu departm ent of Endocrinology and Metabolism Shanghai Clinical Center for DiabetesShanghai Diabetes InstituteShanghai Key Laboratory of Diabetes MellitusShanghai Jiao Tong University Affiliated Sixth People's HospitalShanghai 200233China Chronic Disease Epidemiology Pennington Biomedical Research CenterBaton RougeLAUSA.

electronic health(medical)records,which are also considered as patients*information that are routinely collected,provide a great chance for researchers to develop an epidemiological understanding of *** health records systems cannot develop without the advance of computer *** conducting clinical trials that are always costly,feasible and reasonable analysis of routine patients5 information is more cost-effective and reflective of clinical practice,which is also called real world *** world studies can be well supported by big data in healthcare *** world studies become more and more focused and important with the development of evidence-based *** big data will definitely help in making decisions,making policies and guidelines,monitoring of effectiveness and safety on new drugs or ***,cleaning,and analyzing such big data will be a great challenge for clinical *** applications and developments of electronic health record in western countries(eg,disease registries,health insurance claims,etc)have provided a clear direction for Chinese ***,it is still at primary stages in *** review tries to provide a full perspective on how to translate the electronic health records into scientific achievements,for example,among patients with *** a summary in the end,resource sharing and collaborations are highly recommended among hospitals and healthcare groups.

关键词： electronic health records Real world Cohort study

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Machine-Learning-Enabled Obesity Level Prediction Through electronic health records

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Computer Systems Science & Engineering 2023年第9期46卷 3715-3728页

作者： Saeed Ali Alsareii Muhammad Awais Abdulrahman Manaa Alamri Mansour Yousef AlAsmari Muhammad Irfan Mohsin Raza Umer Manzoor Department of Surgery College of MedicineNajran UniversityNajran61441Saudi Arabia Department of Computer Science Edge Hill UniversitySt Helens RdOrmskirkL394QPUK Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Computer Science Aston UniversityBirminghamB47ETUK

Obesity is a critical health condition that severely affects an individual’s quality of life *** occurrence of obesity is strongly associated with extreme health conditions,such as cardiac diseases,diabetes,hypertension,and some types of ***,it is vital to avoid obesity and or reverse its *** healthy food habits and an active lifestyle can help to prevent *** this regard,artificial intelligence(AI)can play an important role in estimating health conditions and detecting obesity and its *** study aims to see obesity levels in adults by implementing AIenabled machine learning on a real-life *** dataset is in the form of electronic health records(EHR)containing data on several aspects of daily living,such as dietary habits,physical conditions,and lifestyle variables for various participants with different health conditions(underweight,normal,overweight,and obesity type I,II and III),expressed in terms of a variety of features or parameters,such as physical condition,food intake,lifestyle and mode of *** classifiers,i.e.,eXtreme gradient boosting classifier(XGB),support vector machine(SVM),and artificial neural network(ANN),are implemented to detect the status of several conditions,including obesity *** findings indicate that the proposed XGB-based system outperforms the existing obesity level estimation methods,achieving overall performance rates of 98.5%and 99.6%in the scenarios explored.

关键词： Artificial intelligence obesity machine learning extreme gradient boosting classifier support vector machine artificial neural network electronic health records physical activity obesity levels

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The development and impact of adopting electronic health records in the United States:A brief overview and implications for nursing education

Health Care Science

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health Care Science 2022年第3期1卷 186-192页

作者： Song Ge Yuting Song Jiale Hu Xianping Tang Junxin Li Linda Dune Department of Natural Sciences College of Sciences and TechnologyUniversity of Houston-DowntownHoustonTexasUSA School of Nursing Qingdao UniversityQingdaoShandongChina Department of Nurse Anesthesia College of Health ProfessionsVirginia Commonwealth UniversityRichmondVirginiaUSA School of Nursing Xuzhou Medical UniversityXuzhouJiangsuChina School of Nursing Johns Hopkins UniversityBaltimoreMarylandUSA

1|DEVELOPMENT AND ADOPTION OF EHR IN THE UNITED STATES At present,health-care systems in the United States face enormous challenges in providing quality care,characterized by safe,effective,efficient,patientcentered,timely,and equitable care while containing health-care costs[1,2].To understand and address patients'increasingly complicated health-care needs,we need safe access to quality information that is characterized by integrity,reliability,and accuracy[3],and establish mutually beneficial relationships among a multidisciplinary team of professionals[4].Traditional paper-based clinical workflow produces many issues such as illegible handwriting,inconvenient access,the possibility of computational prescribing errors,inadequate patient hand-offs,and drug administration *** problems can lead to medical errors,omissions,and duplications and,ultimately,poor patient outcomes and compromised quality of care[2].

关键词： electronic health records electronic medical record US healthcare health information system health informatics Nursing education

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P2HBT: Partially Policy Hidden E-healthcare System with Black-Box Traceability

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Chinese Journal of electronics 2021年第2期30卷 219-231页

作者： YING Zuobin SI Yuanping MA Jianfeng JIANG Wenjie XU Shengmin LIU Ximeng School of Computer Science and Technology Anhui University Institutes of Physical Science and Information Technology Anhui University School of Computer Science and Technology Xidian University School of Information Systems Singapore Management University College of Mathematics and Computer Science Fuzhou University

electronic health record(EHR), as the core of the e-healthcare system, is an electronic version of patient medical history, which records personal healthrelated information. EHR embodies the value of disease monitoring through large-scale sharing via the Cloud service provider(CSP). However, the health data-centric feature makes EHR more preferable to the adversaries compared with other outsourcing data. Moreover, there may even be malicious users who deliberately leak their access privileges for benefits. An e-healthcare system with a black-box traceable and robust data security mechanism is presented for the first time. Specifically, we propose an effective P2 HBT, which can perform fine-grained access control on encrypted EHRs, prevent the leakage of privacy contained in access policies, and support tracing of *** the standard model, the scheme is proved fully secure. Performance analysis demonstrates that P2HBT can achieve the design goals and outperform existing schemes in terms of storage and computation overhead.

关键词： outsourcing Cloud service provider malicious users effective P2HBT medical information systems partially policy hidden e-healthcare system electronic health record patient medical history security of data diseases black-box traceability data privacy authorisation electronic health records health data-centric feature cloud computing electronic version large-scale sharing access policies cryptography disease monitoring fine-grained access control health care outsourcing data black-box traceable robust data security mechanism encrypted EHRs personal health-related information access privileges EHR

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Impact of mobile health and medical applications on clinical practice in gastroenterology

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World Journal of Gastroenterology 2020年第29期26卷 4182-4197页

作者： Sven Kernebeck Theresa S Busse Maximilian D Bottcher Jurgen Weitz Jan Ehlers Ulrich Bork Didactics Educational Research in health Science Faculty of HealthWitten/Herdecke UniversityWitten 58455Germany Department of GI- Thoracic-and Vascular SurgeryDresden Technical UniversityUniversity Hospital DresdenDresden 01307Germany

Mobile health apps (MHAs) and medical apps (MAs) are becoming increasinglypopular as digital interventions in a wide range of health-related applications inalmost all sectors of healthcare. The surge in demand for digital medical solutionshas been accelerated by the need for new diagnostic and therapeutic methods inthe current coronavirus disease 2019 pandemic. This also applies to clinicalpractice in gastroenterology, which has, in many respects, undergone a recentdigital transformation with numerous consequences that will impact patients andhealth care professionals in the near future. MHAs and MAs are considered tohave great potential, especially for chronic diseases, as they can support the selfmanagementof patients in many ways. Despite the great potential associated withthe application of MHAs and MAs in gastroenterology and health care in general,there are numerous challenges to be met in the future, including both the ethicaland legal aspects of applying this technology. The aim of this article is to providean overview of the current status of MHA and MA use in the field ofgastroenterology, describe the future perspectives in this field and point out someof the challenges that need to be addressed.

关键词： Mobile health health applications Medical applications Technology Telemedicine Mobile applications Smartphone ehealth mhealth Digital biomarker electronic health records

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Predictive modeling of 30-day readmission risk of diabetes patients by logistic regression,artificial neural network,and EasyEnsemble

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Asian Pacific Journal of Tropical Medicine 2021年第9期14卷 417-428页

作者： Xiayu Xiang Chuanyi Liu Yanchun Zhang Wei Xiang Binxing Fang School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijingChina School of Computer Science and Technology Harbin Institute of Technology(Shenzhen)ShenzhenChina Institute for Sustainable Industries and Liveable Cities Victoria UniversityMelbourneAustralia Key Laboratory of Tropical Translational Medicine of Ministry of Education Hainan Medical UniversityHaikouChina NHC Key Laboratory of Control of Tropical Diseases Hainan Medical UniversityHaikouChina Cyberspace Security Research Center Peng Cheng LaboratoryShenzhenChina

Objective:To determine the most influential data features and to develop machine learning approaches that best predict hospital readmissions among patients with ***:In this retrospective cohort study,we surveyed patient statistics and performed feature analysis to identify the most influential data features associated with *** of all-cause,30-day readmission outcomes were modeled using logistic regression,artificial neural network,and Easy Ensemble.F1 statistic,sensitivity,and positive predictive value were used to evaluate the model ***:We identified 14 most influential data features(4 numeric features and 10 categorical features)and evaluated 3 machine learning models with numerous sampling methods(oversampling,undersampling,and hybrid techniques).The deep learning model offered no improvement over traditional models(logistic regression and Easy Ensemble)for predicting readmission,whereas the other two algorithms led to much smaller differences between the training and testing ***:Machine learning approaches to record electronic health data offer a promising method for improving readmission prediction in patients with *** more work is needed to construct datasets with more clinical variables beyond the standard risk factors and to fine-tune and optimize machine learning models.

关键词： electronic health records Hospital readmissions Feature analysis Predictive models Imbalanced learning Diabetes

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