Securing Patient-Centric Personal Health Records Sharing System in Cloud Computing

Personal health record （PHR） enables patients to manage their own electronic medical records （EMR） in a centralized way, and it is oRen outsourced to be stored in a third-party server. In this paper we propose a novel secure and scalable system for sharing PHRs. We focus on the multiple data owner scenario, and divide the users in the system into multiple security domains that greatly reduce the key management complexity for owners and users. A high degree of patient privacy is guaranteed by exploiting hierarchical and multi- authority attribute-sets based encryption （HM- ASBE）. Our system not only supports compound attributes due to flexible attribute sets combinations, but also achieves fine-grained access control. Our scheme supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios.

Fog-Based Secure Framework for Personal Health Records Systems

The rapid development of personal health records(PHR)systems enables an individual to collect,create,store and share his PHR to authorized entities.Health care systems within the smart city environment require a patient to share his PRH data with a multitude of institutions’repositories located in the cloud.The cloud computing paradigm cannot meet such a massive transformative healthcare systems due to drawbacks including network latency,scalability and bandwidth.Fog computing relieves the load of conventional cloud computing by availing intermediate fog nodes between the end users and the remote servers.Assuming a massive demand of PHR data within a ubiquitous smart city,we propose a secure and fog assisted framework for PHR systems to address security,access control and privacy concerns.Built under a fog-based architecture,the proposed framework makes use of efficient key exchange protocol coupled with ciphertext attribute based encryption(CP-ABE)to guarantee confidentiality and fine-grained access control within the system respectively.We also make use of digital signature combined with CP-ABE to ensure the system authentication and users privacy.We provide the analysis of the proposed framework in terms of security and performance.

A Pilot Study of Health Coaching on Older Adults’ Personal Healthcare and Maintenance during the Outbreak of Covid-19 in Singapore

With a rapidly ageing population in Singapore, older adults and their family members face challenges of age-related diseases, caregiver stress, and increasing demand for caregiving services. To address this pressing issue, this pilot study aims to introduce online health coaching for older adults in Singapore and evaluate its effectiveness on maintenance of personal healthcare. In the midst of the COVID-19 outbreak, older adults’ activities were largely restricted by measures on social distancing. The online health coaching provided a solution for older adults to achieve a healthy lifestyle in a contactless manner. In this pilot study, 18 older adults (≥55 years old) who were willing to be coached by trained health coaches (n = 10) for 8 weeks (once a week) were recruited. Pre- and post-surveys with older adults were conducted. Furthermore, health coaching booklet was used to control the quality of coaching and to record diet and exercise plans. The pilot study demonstrated that the health coaching provided older adults with knowledge of nutrition and exercise, raised their awareness of well-being in terms of daily meals and regular exercise, and provided an alternative to maintain a healthy lifestyle amidst global pandemic. Additionally, we also identified that the older adults’ satisfactions with health coaching were positively associated with educational levels (R2 = 0.31). Lastly, this pilot study highlighted that health coaching standardization process for older adults is critical for researchers and healthcare practitioners in the future.

Moisture‑Electric–Moisture‑Sensitive Heterostructure Triggered Proton Hopping for Quality‑Enhancing Moist‑Electric Generator

Moisture-enabled electricity(ME)is a method of converting the potential energy of water in the external environment into electrical energy through the interaction of functional materials with water molecules and can be directly applied to energy harvesting and signal expression.However,ME can be unreliable in numerous applications due to its sluggish response to moisture,thus sacrificing the value of fast energy harvesting and highly accurate information representation.Here,by constructing a moisture-electric-moisture-sensitive(ME-MS)heterostructure,we develop an efficient ME generator with ultra-fast electric response to moisture achieved by triggering Grotthuss protons hopping in the sensitized ZnO,which modulates the heterostructure built-in interfacial potential,enables quick response(0.435 s),an unprecedented ultra-fast response rate of 972.4 mV s^(−1),and a durable electrical signal output for 8 h without any attenuation.Our research provides an efficient way to generate electricity and important insight for a deeper understanding of the mechanisms of moisture-generated carrier migration in ME generator,which has a more comprehensive working scene and can serve as a typical model for human health monitoring and smart medical electronics design.

An Efficient Blockchain-Based Healthcare System Using Artificial Intelligence

Personal health records and electronic health records are considered as the most sensitive information in the healthcare domain.Several solutions have been provided for implementing the digital health system using blockchain,but there are several challenges,such as secure access control and privacy is one of the prominent issues.Hence,we propose a novel framework and implemented an attribute-based access control system using blockchain.Moreover,we have also integrated artificial intelligence(AI)based approach to identify the behavior and activity for security reasons.The current methods only focus on the related clinical records received from a medical diagnosis.Moreover,existing methods are too inflexible to resourcefully sustenance metadata changes.A secure patient data access framework is proposed in this research,integrating blockchain,trust chain,and blockchain methods to overcome these problems in the literature for sharing and accessing digital healthcare data.We have used a neural network and classifier to categorize the user access to our proposed system.Our proposed scheme provides an intelligent and secure blockchain-based access control system in the digital healthcare system.Experimental results surpass the existing solutions by collecting attributes such as the number of transactions,number of nodes,transaction delay,block creation,and signature verification time.

BC-PC-Share:Blockchain-Based Patient-Centric Data Sharing Scheme for PHRs in Cloud Computing

Sharing of personal health records(PHR)in cloud computing is an essential functionality in the healthcare system.However,how to securely,efficiently and flexibly share PHRs data of the patient in a multi-receiver setting has not been well addressed.For instance,since the trust domain of the cloud server is not identical to the data owner or data user,the semi-trust cloud service provider may intentionally destroy or tamper shared PHRs data of user or only transform partial ciphertext of the shared PHRs or even return wrong computation results to save its storage and computation resource,to pursue maximum economic interest or other malicious purposes.Thus,the PHRs data storing or sharing via the cloud server should be performed with consistency and integrity verification.Fortunately,the emergence of blockchain technology provides new ideas and prospects for ensuring the consistency and integrity of shared PHRs data.To this end,in this work,we leverage the consortiumblockchain technology to enhance the trustworthiness of each participant and propose a blockchain-based patient-centric data sharing scheme for PHRs in cloud computing(BC-PC-Share).Different from the state-of-art schemes,our proposal can achieve the following desired properties:(1)Realizing patient-centric PHRs sharing with a public verification function,i.e.,which can ensure that the returned shared data is consistent with the requested shared data and the integrity of the shared data is not compromised.(2)Supporting scalable and fine-grained access control and sharing of PHRs data with multiple domain users,such as hospitals,medical research institutes,and medical insurance companies.(3)Achieving efficient user decryption by leveraging the transformation key technique and efficient user revocation by introducing time-controlled access.The security analysis and simulation experiment demonstrate that the proposed BC-PC-Share scheme is a feasible and promising solution for PHRs data sharing via consortium blockchain.

Effect on Patient Safety of Brief Interventions Performed by Pharmacists via Drug Profile Books: VISualization of Treatment Assist by pharmacists (VISTA) Project in Japan

In Japanese pharmacies, Drug Profile Books (DPBs), which are a type of Personal Health Record (PHR), are incorporated in order to prevent duplicate medication and drug interactions in outpatients (patients) through the uniform management of drug administration information. In this study, we tried to clarify the effect on patient safety of brief interventions via DPBs by pharmacists. The study design was a randomized controlled trial on pharmacies as clusters. 65 pharmacies agreed to participate in the study (intervention group (IG): 33;control group (CG): 32). The primary outcomes were: rate of inquiry occurrence, rate of prescription change, and rates of duplicate medications & drug interactions. 56 pharmacies (IG: 29;CG: 27) completed the study. There was a higher tendency for prescription changes in the IG compared to the CG (IG: 0.03%;CG: 0.02%;P = 0.08). In addition, the rate of duplicate medications & drug interactions accounting for the inquiries was significantly higher in the IG than in the CG (IG: 89.2%;CG: 71.9%;P = 0.01). This implied that brief interventions by pharmacists using DPBs had an effect in raising patient safety.

Domain ontology development of knowledge base in cardiovascular personalized health management

In China,cardiovascular disease has become the leading killer in recent years,and mortality from cardiovascular disease is continuing to rapidly increase.Extant medical research has proven that personal health management(prevention,intervention,and recuperation)of chronic diseases,such as cardiovascular diseases,is the best strategy for their prevention and treatment.Currently,the public can obtain health management knowledge through the Internet,newspapers,books,and other channels.However,with the explosive growth of available information,the public is limited to obtain effective health management guidance due to the characteristics of multiple sources,uneven accuracy(even some contradictory knowledge)and a major paucity of personalization,especially for the general public who lack professional medical knowledge.To address these problems,this paper proposes a knowledge base framework(i.e.domain ontology library)of health management programs based on the cardiovascular disease domain,which can standardize knowledge of health management programs both logically and structurally.In order to satisfy the needs of personalized health management,the core ontology of the domain ontology library is health-management-program ontology.In addition to common ontologies(e.g.disease ontology,drug ontology,etc.),basic ontologies include the ontology of individual health characteristics(e.g.individual-healthcharacteristics and environmental-characteristics ontology),and ontologies comprising diet and sport(e.g.ingredients,recipes,physical exercise,etc.).We then construct the ontology library through the professional ontology tool,Protégé.With a case study,we translate a piece of text health management knowledge into instances of an ontology library.At the same time,we present a personalized health management program recommendation algorithm based on the ontology library,and a recommendation case is realized according to this algorithm.As a basic research,the results of this paper can also support other health management applications in the future.

Quality indicators for the care of older adults with disabilities in longterm care facilities based on Maslow’s hierarchy of needs

Purpose:This study aimed to develop quality indicators for the care of older adults with disabilities in long-term care facilities(LTCFs)based on Maslow’s hierarchy of needs.Methods:The draft of the quality indicators was drawn up based on a literature review and research group discussion.The quality indicators were finalized by two rounds of expert consultation(involving 15 experts)using the Delphi method.The Analytic Hierarchy Process was applied to calculate the indicators’weight.Results:The response rates of the two rounds of consultation were 100%and 93%,and the expert authority coefficients were 0.86 and 0.87.After two rounds of consultation,the expert opinion coordination coefficients of the first-,second-and third-level indicators were 0.42,0.25,and 0.96,respectively(P<0.05),and the variation coefficient was0.25.The final quality indicators for the care of older adults with disabilities in LTCFs included 7 first-level,19 second-level,and 107 third-level indicators.Conclusion:The quality indicators for the care of older adults with disabilities in LTCFs are reliable,scientific,comprehensive,and practical and specify the content of person-centered care needs.This can provide a reference for evaluating and improving care quality in LTCFs.

Promoting whole person health:Exploring the role of traditional Chinese medicine in Polish healthcare

Poland has a unique history of traditional Chinese medicine(TCM)dating back to the 17th century when Polish missionary Michael(Michal)Boym was a pioneer in the field.In the 20th century,his successor,Professor Zbigniew Garnuszewski,reintroduced acupuncture to medical practice in Poland.However,other methods of TCM and its holistic approach to patient care have not found their place in modern medicine in Poland.At present,the legal status of TCM in Poland remains unregulated,with TCM included in the broad spectrum of complementary and alternative medicine(CAM)practices.Few reports are available on the use of TCM methods among the Polish population.Integrative medicine combines conventional medicine with evidence-based CAM interventions and considers all aspects of a patient's health,including physical,emotional,mental,social,and environmental factors.An integrative healthcare model that incorporates TCM modalities and lifestyle recommendations as well as a whole person approach may provide a more sustainable solution for the constantly underfinanced Polish healthcare system,which faces challenges of multimorbidity in an aging society and limited access to care.The coronavirus disease 2019 pandemic,war in Ukraine,and ongoing climate crisis have underscored the need to strengthen the resilience of the Polish healthcare system and search for new solutions.A model of care that blends the best of biomedicine and TCM healing approaches may be a better option for both patients and the healthcare system in Poland.

Curriculum Development for FAIR Data Stewardship

The FAIR Guidelines attempts to make digital data Findable, Accessible, Interoperable, and Reusable(FAIR). To prepare FAIR data, a new data science discipline known as data stewardship is emerging and, as the FAIR Guidelines gain more acceptance, an increase in the demand for data stewards is expected. Consequently, there is a need to develop curricula to foster professional skills in data stewardship through effective knowledge communication. There have been a number of initiatives aimed at bridging the gap in FAIR data management training through both formal and informal programmes. This article describes the experience of developing a digital initiative for FAIR data management training under the Digital Innovations and Skills Hub(DISH) project. The FAIR Data Management course offers 6 short on-demand certificate modules over 12 weeks. The modules are divided into two sets: FAIR data and data science. The core subjects cover elementary topics in data science, regulatory frameworks, FAIR data management, intermediate to advanced topics in FAIR Data Point installation, and FAIR data in the management of healthcare and semantic data. Each week, participants are required to devote 7–8 hours of self-study to the modules, based on the resources provided. Once they have satisfied all requirements, students are certified as FAIR data scientists and qualified to serve as both FAIR data stewards and analysts. It is expected that in-depth and focused curricula development with diverse participants will build a core of FAIR data scientists for Data Competence Centres and encourage the rapid adoption of the FAIR Guidelines for research and development.

DAMS:A Distributed Analytics Metadata Schema

In recent years,implementations enabling Distributed Analytics(DA)have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data.These concepts propose privacy-enhancing alternatives to data centralisation approaches,which have restricted applicability in case of sensitive data due to ethical,legal or social aspects.Nevertheless,the immanent problem of DA-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions,particularly the absence of basic metadata for data sets or analysis tasks.To approach the mentioned problems,we propose a metadata schema for DA infrastructures,which provides a vocabulary to enrich the involved entities with descriptive semantics.We initially perform a requirement analysis with domain experts to reveal necessary metadata items,which represents the foundation of our schema.Afterwards,we transform the obtained domain expert knowledge into user stories and derive the most significant semantic content.In the final step,we enable machine-readability via RDF(S)and SHACL serialisations.We deploy our schema in a proof-of-concept monitoring dashboard to validate its contribution to the transparency of DA architectures.Additionally,we evaluate the schema’s compliance with the FAIR principles.The evaluation shows that the schema succeeds in increasing transparency while being compliant with most of the FAIR principles.Because a common metadata model is critical for enhancing the compatibility between multiple DA infrastructures,our work lowers data access and analysis barriers.It represents an initial and infrastructure-independent foundation for the FAIRification of DA and the underlying scientific data management.