With the evolution of wellness tourism in the digital era, there has been an exponential change in the landscape of travel wellness and preventive health care. Today, the travelers are driven to seek holistic well-being, self-care, and transformative experiences beyond traditional leisure. This growing demand has led to the integration of advanced wellness and tourism technologies, such as artificial intelligence (AI), wearable devices, virtual reality (VR), telemedicine, and blockchain. These innovations enhance personalization, operational efficiency, and accessibility for the customer; they also redesign the delivery and consumption of wellness experiences. As there is a technological shift in the wellness tourism industry, critical challenges arise related to data privacy, the digital divide, sustainability, cultural sensitivity, and the erosion of authenticity in wellness practices. This chapter critically examines the relationship between wellness tourism and emerging technologies. It hides the opportunities and the underlying challenges associated with this transformation. Insights complemented by semi-structured interviews with industry experts and extensive academic literature reviews published between 2015 and 2025 offered a comprehensive exploration of future trends, challenges, and pathways for sustainable development in wellness tourism. It also proposes the framework for ethical technology integration, ensuring the wellness tourism ecosystem remains inclusive and resilient. Inform the ground of the principle of sustainability.
Case Report Forms (CRFs) are essential tools in clinical trials, serving as the primary mechanism for systematic and standardized patient data collection. This chapter discusses the critical role of CRFs in maintaining data integrity, supporting regulatory compliance, and ensuring the accuracy and consistency of clinical trial results. The chapter provides an in-depth exploration of the key principles involved in designing CRFs, including user-centric design, data standardization, and error management. It contrasts the features of well-designed and poorly designed CRFs, highlighting the significant impact that effective CRF design has on clinical trial outcomes. Additionally, the chapter addresses the evolution of CRFs, particularly the transition from paper-based systems to electronic Case Report Forms (eCRFs), and their benefits, including real-time data validation, enhanced accessibility, and compliance with regulatory guidelines. The impact of technological advances such as artificial intelligence, blockchain, and decentralized trials on the future of CRF processes is also discussed. Finally, a sample CRF is presented, providing a practical example of a well-designed form for clinical data collection in a controlled study.
Since announcing the implementation of a single electronic health record for all South Africans, the government has not yet informed healthcare facilities of how this would be accomplished. The siloed South African healthcare system would have to be redesigned to accommodate a single electronic health record. A systematic literature review conducted across three databases returned 9 790 results. By applying ten filters, 22 documents were eventually retrieved for analysis. The analysis showed that existing research focuses on healthcare architectures from a theoretical perspective. Therefore, the literature review revealed a practically based research deficiency and a lack of theoretical studies merged with practical cases. Seeking to enhance the understanding of designing a single electronic health record, the documents were analysed using a qualitative inductive content analysis technique, revealing that a single electronic health record cannot be formulated using a fully centralised architecture as this is not practical. A fully decentralised architecture, such as blockchain, is equally infeasible because this requires significant changes to the existing systems and infrastructure and would require re-skilling system builders. Since the South African healthcare architecture is already decentralised, hybrid architecture incorporating edge computing with clusters of systems and information that connect using middleware should be considered.
G. Indirapriyadarsini, Sireesha Guttapalam, Ramyasri Mogarala, Kalpeshkumar L. Guptha
Background Maintaining optimal youth nutritional health is an urgent socio-economic imperative that underpins long-term human productivity and rights-based development. However, modern youth cohorts face unique dietary threats caused by the widespread availability of ultra-processed foods, targeted digital marketing, and complex food labeling protocols. Although Artificial Intelligence (AI) presents innovative avenues for personalized dietary profiling, existing systems remain largely technocentric and detached from statutory frameworks or behavioral realities. Objective This study bridges this interdisciplinary divide by evaluating a rights-based, technology-driven framework to improve youth nutritional health. It aims to: (1) empirically evaluate the āKnowledge-Attitude-Practiceā (KAP) gap linking statutory consumer rights to real-world eating habits; (2) present the engineering design of a non-commercial Progressive Web Application (PWA) built to translate legal safeguards into daily behavioral changes; and (3) triangulate these findings using data from youth surveys and expert legal and nutritional panels. Methods Using a cross-sectional approach based on non-parametric power constraints, a validated survey instrument was completed by a target sample of Indian youth ( n = 354, aged 15ā25 years). Concurrently, data matrices were compiled from regional legal experts ( n = 12) and public nutrition professionals ( n = 12) to cross-verify structural bottlenecks. Group variances, demographic dependencies, and rank associations were analyzed using robust non-parametric tests, including One-Way ANOVA, Kruskal-Wallis (H), Welchās t-test, and Kendallās Tau ( Ļ ) correlation coefficients. Results Inferential analysis revealed unexpected demographic trends: undergraduate status predicted significantly higher FSSAI safety awareness than post-graduate status ( p = 0.0037), while subjective health ratings exhibited a non-linear relationship with household income ( p = 0.0004), peaking in the lower-middle financial tier. Crucially, rank correlation testing revealed that the relationship between statutory knowledge and actual dietary actions is functionally non-existent ( Ļ = ā0.001). This near-zero correlation provides clear empirical proof of a pronounced Knowledge-Action Gap, confirming that passive legal literacy fails to influence food selection in modern environments. Conclusion By framing automated behavioral interventions within the constitutional protections of Article 21 of the Constitution of India and the Consumer Protection Act, 2019, this study shows how the open-access PWA (nutrition-zb.pages.dev) can bridge this behavioral gap. This shifts the focus of consumer health informatics from basic self-tracking to a rights-based, systemic public health intervention.
Open access
Nutrition, Genetics, and Disease
Mobile Health and mHealth Applications
Artificial Intelligence in Healthcare and Education
Momodu Mustapha, Susan Konyeha, Akinola Samson Olayinka
This study examines user trust and perception of cryptographic technologies specifically SHA3-512 hashing, SERPENT encryption, and Zero-Knowledge Proofs (ZKP) in the context of centralized Electronic Health Record (EHR) systems. As healthcare institutions increasingly migrate patient data to digital platforms, the security and privacy properties of underlying cryptographic mechanisms have become critical determinants of user confidence and system adoption. Using a quantitative, survey-based design, data were collected from 92 healthcare practitioners, IT professionals, and system administrators actively engaged with EHR systems in Auchi, Nigeria. A Random Forest classifier was trained to predict perceived satisfaction levels (Low, Neutral, High) based on respondents' assessments of cryptographic effectiveness, usability, and trust. Results indicate that trust in ZKP is the strongest predictor of overall perception, followed by confidence in SERPENT encryption and SHA3-512 integrity guarantees. The model achieved a classification accuracy of 63.3% on a held-out test set derived from this exploratory sample, with a Kappa statistic of 0.52 reflecting moderate agreement beyond chance. Balanced accuracy across classes (approximately 0.49ā0.50) and low per class sensitivity confirm that the findings should be interpreted as preliminary and directional rather than definitive. Key themes from open ended feedback analyzed using TF-IDF text mining reveal that while respondents broadly recognize the security value of these cryptographic mechanisms, concerns about system slowdown, usability complexity, and insufficient user education present barriers to wider adoption. This study contributes a pilot-level empirical baseline for understanding stakeholder perception of layered cryptographic security in resource-constrained healthcare environments, and highlights the need for larger-scale replication studies. Keywords: SHA3-512; SERPENT encryption; Zero-Knowledge Proofs; healthcare data security; user perception; Electronic Health Records; Random Forest
Augusto MagalhĆ£es Pinto de MendonƧa, Filipe PessĆ“a Sousa, fellipe souza pessanha, Igor Machado Coelho
Fitness apps help users track their exercises and health. Wearable sensors provide increasing amounts of data, bringing motivation but also challenges to privacy. Data shared by usersā devices may exceed what they want to share for the desired results. Health insurers, corporate wellness programs, and gamified apps all want proof of exercise, but current systems require users to disclose raw activity logs, heart rate, and location data. This paper presents a system that lets users prove they met exercise goals without revealing raw sensor data. We embed a Decision Tree classifier inside a zero-knowledge proof circuit using the Groth16 protocol. The classifier distinguishes rest, moderate, and vigorous activity from accelerometer and gyroscope readings. The model reaches 97.19% holdout accuracy on the MHEALTH dataset, validated through $\mathbf{1 0}$-fold crossvalidation. The circuit uses 10,447 constraints, small enough for smartphones and wearables. Proofs take about 500 ms on desktop and 1.1 seconds on mobile, with only 800 bytes each. Unlike systems where classification runs outside the proof, our approach makes the classification itself verifiable, so label injection attacks become computationally infeasible. We tested 30 cases covering all intensity classes and boundary conditions, and all proofs were generated and verified correctly. The system provides cryptographic guarantees while remaining practical for real-world deployment.
Background: Health care has seen several new disruptive technologies. One such innovation is the introduction of blockchain smart contracts. These smart contracts are activated automatically once preprogrammed conditions are met. Smart contracts have improved patient outcomes, the efficiency of care delivery, and reduced costs. Despite their benefits, patients have had limited interactions with smart contracts in primary care; therefore, they may not trust blockchain-based smart contracts and may perceive them as risky or have concerns about their security. Objective: This study aimed to evaluate how patients' perceptions of smart contracts affect their adoption in primary care. Specifically, we investigated the impact of patients' perceptions of smart contract security, risk, and trust in their health care providers. Methods: This study used an experimental survey design to evaluate acceptance of smart contracts. Patients were randomly assigned to 1 of 2 research scenarios proposing either the positive use of blockchain smart contracts or the loss of benefits if a patient opted out. We collected data from a total of 387 participants. The Likert survey used 3 items to measure 5 constructs in the conceptual model. The 5 hypotheses were that gain-loss-framed messaging, perceived security, and trust would have a positive impact on the adoption of smart contracts, whereas perceived risk and the clinical setting would have a negative impact on patients' intention to adopt smart contracts. The conceptual model was tested using structural equation modeling, and the model fit indices suggested a good fit. Results: Most of the hypotheses were supported, except for the gain-loss-framing effect. As hypothesized, perceived security had the strongest positive influence on the intention to use smart contracts (Ī²=.50; P<.001). Trust in health care providers also showed a significant positive relationship (Ī²=.43; P<.001), while perceived risk had a smaller but still significant negative impact (Ī²=-.071; P.048). Patients in clinic-based settings had a lower intention to use smart contracts than patients in telehealth settings, and male patients had a lower intention to use smart contracts than female patients. Conclusions: The results of this study have implications for health care providers who intend to adopt smart contracts early, that is, early majority or late adopters. To facilitate their implementation, providers should highlight the security benefits of smart contracts and leverage patient trust. Providers should customize smart contract implementation strategies based on patient demographics such as age, health status, and gender. By understanding these factors, health care organizations can more effectively promote the adoption of smart contracts and realize the potential benefits of this disruptive technology in primary care.
Background: Blockchain has many applications in healthcare and can improve mobile health applications, monitoring devices, electronic media record sharing and storage, clinical trial data, and insurance information storage. In this study, the aim was to investigate the application areas of blockchain and its impact in telemedicine. Methods: This study considers articles use blockchain for telemedicine. PubMed, Science direct, and Web of Science databases are considered as searchable databases. Information on authors' names, year of publication, country, application, privacy mechanism, blockchain platform, and encryption techniques are used. 249 studies were retrieved after the initial search. Finally, 16 cases had the necessary criteria to enter this study. The JBI checklist was applied to all 16 studies. Results: China with 5 studies and Italy with 3 studies are the most important countries about blockchain in telemedicine that electronic health records are more used than others. Blockchain platforms are Ethereum, Internet of thing, cloud-service provider, and GPS. Encryption techniques are Attribute-based encryption: Decentralized identity: Order-preserving encryption- hashcode- Double blockchain. Conclusions: Blockchain plays an important role in creating security for telemedicine technology. In the future, the use of technology will have a significant and important leap, which will attract the attention of many researchers.
The accurate and timely classification of toddlers' nutritional status is critical for early intervention, particularly in remote or underserved communities with limited access to healthcare professionals. However, data security, especially for children's health data, is equally essential to ensure safe storage and access. To address these challenges, this study proposes a hybrid AI-powered chatbot that integrates ensemble learning, blockchain, and decentralized storage to support both nutritional status classification and educational interaction. The system combines a random forest model for classification with GPT-3.5 Turbo for bilingual (IndonesianāEnglish) stunting education deployed via Telegram. Preprocessing includes standardizing, normalizing, and encoding Indonesian-language nutrition data to ensure machine learning readiness. Six ensemble algorithms are evaluated using stratified five-fold cross-validation, with classification results hashed using SHA-256 and immutably stored on the Interplanetary File System (IPFS) and a local Ethereum blockchain. The chatbot effectively manages both structured inputs and natural language queries, ensuring secure, transparent, and real-time nutritional assessments. Results demonstrate high classification performance, with the random forest model achieving the highest mean F1-score (0.9987) and the lowest deviation. Its robustness was validated by a 20% hold-out test set and stratified five-fold cross-validation, which obtained excellent balanced performance across nutritional status categories (F1-macro, precision, recall, accuracy ā 0.99; ROC AUC = 1.00). External validation also yielded robust and consistent results (F1-macro = 0.97, precision = 0.97, recall = 0.96, ROC AUC = 0.98, and accuracy = 0.97), demonstrating the model's generalization ability and mitigating concerns regarding overfitting. Blockchain evaluation confirmed stable and linear CID transaction throughput (blocks 29ā46) with no observed latency, ensuring reliable and continuous data recording. Furthermore, gas prices decreased by ~87.5%, highlighting significant improvements in cost efficiency and scalability, which reinforces blockchain's feasibility for decentralized, AI-driven health data management. Received: 9 June 2025 | Revised: 29 September 2025 | Accepted: 31 October 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in Kaggle at https://www.kaggle.com/datasets/rendiputra/stunting-balita-detection-121k-rows and https://www.kaggle.com/datasets/jabirmuktabir/stunting-wasting-dataset. Author Contribution Statement Wa Ode Siti Nur Alam: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing ā original draft, Writing ā review & editing, Visualization, Project administration. Riri Fitri Sari: Conceptualization, Writing ā review & editing, Supervision, Funding acquisition.
"With growing concerns about mental well-being, users want efficacious means to monitor emotions and get personalized assistance, with current solutions often sacrificing privacy or offering shallow revelations. ZenLoop overcomes the shortcomings by combining AI-based analysis of emotion with safe Web3 storage to provide both well-being support alongside privacy. This paper builds a conversational AI chatbot that offers coping mechanisms, a mood tracker to record emotion states, and an analysis dashboard to enable users to identify behavior patterns. Developed with React for frontend, Node.js for backend, and MongoDB for organized data, ZenLoop provides empathy-based responses leveraging NLP models trained on mental well-being dialogues. Journals are encrypted and stored in Web3-based storage, with immutable, decentralized protection. Trends in moods are depicted in interactive graphs, and AI-driven insights enable users to monitor emotion shifts. Tests show enhanced user engagement, improved self-perception, along with superior protection of data. The chatbot is effective in detecting levels of distress along with recommended interventions, promoting emotional resilience. By combining AI-driven tools for mental well-being with the security of blockchain, ZenLoop enables users to express emotion securely, monitor their mental well-being patterns, and get personalized advice at no cost of privacy. This work demonstrates the potential of privacy-based AI-based solutions to promote well-being at the emotional level, leading to the development of secure, user-centric applications for mental well-being.
Integrating blockchain into healthcare devices offers the potential for improved data control but faces significant usability and acceptance challenges. This study addresses this gap by evaluating CipherPal, an improved blockchain-enabled Smart Fidget Toy prototype, using a multi-framework approach to understand the interplay between technology, design, and user experience. We synthesized insights from three complementary frameworks: an expert review assessing adherence to Web3 Design Guidelines, a User Acceptance Toolkit assessment with professionals based on UTAUT2, and an extended three-day user testing study. The findings revealed that users valued CipherPalās satisfying tactile interaction and perceived benefits for well-being, such as stress relief. However, significant usability barriers emerged, primarily related to challenging deviceāapplication connectivity and data synchronization. The multi-framework approach proved valuable in revealing these core tensions. While the device was conceptually accepted, the blockchain integration added significant interaction friction that overshadowed its potential benefits during the study. This research underscores the critical need for user-centered design in health-related blockchain applications, emphasizing that seamless usability and abstracting technical complexity are paramount for adoption.
BACKGROUND The integration of digital health tools and algorithms in mental healthcare brings a transformative era where technologies like digital phenotyping, affective computing, and computational behavioral analysis are used to passively collect and analyze data from patients outside clinical settings. These "computer perception" (CP) technologies offer new insights into symptom manifestation in daily life while generating large volumes of potentially sensitive data that raise significant data privacy concerns requiring high levels of patient awareness and consent. Empirical research is lacking into stakeholder understandings and perspective towards the collection, management and protection of these data types. OBJECTIVE This study aimed to explore key stakeholder perspectives on the sensitivity of CP data, trust in existing data protections, willingness to share CP data externally, and desire for transparency of CP data transactions outside of the clinical space. METHODS As part of a larger, multi-site study, we conducted qualitative interviews (n=40) via Zoom with 20 adolescents (aged 12-17 years) familiar with CP tools and their caregivers (n=20). Interviews consisted of a series of open-ended questions regarding stakeholdersā perspectives on privacy, data security, and the use and exchange of CP data. We developed a qualitative codebook to identify and label thematic patterns in responses to questions addressing the topics above, using thematic content analysis to inductively identify themes. Each interview was coded by merging work from at least two separate coders, and several team members contributed to qualitative analysis. RESULTS Most adolescents and caregivers viewed CP data as highly sensitive and expressed a reluctance to share these data beyond their clinical teams. While many participants expressed trust in existing data protections to protect CP data, they often misunderstood or overestimated the extent of protections like HIPAA to safeguard CP data. CONCLUSIONS Our findings underscore the critical need for clear and effective patient communication and education about the risks, benefits, and protections associated with CP data through informed consent protocols. To promote greater visibility, understanding, and trust (when justified) in digital tools that have strong promise to promote patient health, we recommend five key strategies, including: (1) educating patients on the limitations of existing data protections; (2) conducting targeted research, including forensic analyses, into secondary data exchanges and to identify privacy breaches or reidentification risks; (3) enacting regulations that mandate greater transparency in health data transactions; (4) implementing computational mechanisms, such as distributed ledger technologies, to enhance data traceability and auditability; and (5) adopting dynamic consent models that allow patients to continuously manage and update their consent preferences.
Child immunization programs are critical for public health, yet their record management remains a challenge due to reliance on manual or centralized digital systems, leading to issues of data integrity, accessibility, and transparency. This paper presents an Ethereum blockchain-based solution introducing advantages over traditional cloud-based architectures. The proposed framework leverages smart contracts, decentralized storage, and interoperability with CVX codes, ensuring secure, tamper-proof, and transparent immunization records. Unlike centralized cloud systems, the blockchain-based architecture mitigates single-point failures, enhances stakeholder's trust, and provides superior scalability and cost efficiency. The framework addresses multi-stakeholder needs, enabling governments, healthcare providers, and parents to access reliable immunization data anytime.
Abstract Background Demographic ageing, shortages in health workforce and increased use of digital tools in daily life kindle decision makersā interest to utilize digital health applications (DHA). While there are several reviews that provide an overview across remuneration frameworks, no synthesis between additional regulatory aspects and frequency of remuneration approval has been conducted. Methods European countries with either strong status in digital health in general or regulation for health apps in particular were chosen for analysis (BE, DK, DE, EE, EN, FR, NL). Country specific information was collected from scientific and grey literature, legal and stakeholder webpages. Semi-structured interviews were conducted with country experts via video call or e-mail and analyzed using Mayringās structured, qualitative content analysis. Preliminary results We find three approaches concerning DHT-definitions: For BE, DE, FR, specific regulations define national remuneration requirements. EN and NL define only minimum requirements while decentralized payors make financing decisions. DK and EE fit DHTs into existing financing schemes. Among countries with a national financing framework, DE achieved the largest number of approvals, followed by FR, while BE has not yet issued a (lasting) financing approval. Evaluation requirements focus on clinical and economic outcomes, largely ignoring non-clinical improvements for patients. Conclusions The German regulation stands out with a peculiar definition that might help clarify evaluation criteria, increase the number of financing approvals but also empower patients while reducing the role of health workforce in their application. BE and NL regulations necessitate involvement of health workers, thus addressing structurally different applications. Key messages ā¢ Drawing lessons for DHT regulations across countries needs to address differences in national definitions and evaluation criteria. ā¢ A standardization system for DHT may help to speed utilization of effective tools and clarify evaluation requirements.
WEB3 technologies on network architectures, distributed ledgers and decentralised artificial intelligence represent a transformative shift in how data are handled, stored and shared. These innovations promise to significantly enhance consumer data privacy rights by addressing fundamental vulnerabilities associated with traditional centralised systems and self-custody wallets. Data breaches in traditional systems operated mainly by third parties are more common, resulting in significant data leaks because of centralised storage and excessive data movement, sometimes unnecessarily. Healthcare data breaches have been a growing concern globally. Several hospitals faced operational halts on account of the impact of ransomware on patient care and privacy. WEB3 Wallets are a vital component emerging as a significant force for global financial inclusion, especially in developing economies. They promote inclusion, reduce costs and empower individuals through self-custody. Though major improvements are needed in these wallets, their use is rising steadily. The global cryptocurrency user base is expected to reach over 500 million by 2025, with substantial growth in emerging markets, according to a report by Statista in 2023. This paper introduces a concept beyond cryptocurrencies and finance into everyday real-world use cases that need combinatorial access to a person's holistic data, including financial and health records, genomic data, advanced directives, among others, that need to be privacy protected and shared with specific actors identified for their roles in the WEB3 ecosystem through decentralised identifiers and non-fungible token badges identifying particular recipients. The author introduced the concept at ETHBoston in April 2024, won accolades for a primitive implementation using underlying threshold cryptography technologies, and enhanced it into a conceptual holistic data share application for global healthcare as presented in this paper.
Sebastian Griewing, Johannes Knitza, Niklas Gremke, Markus Wallwiener Ā· 7 authors
Emerging digital technologies promise to improve breast cancer care, however lack of awareness among clinicians often prevents timely adoption. This study aims to investigate current awareness and intention-to-use of three technologies among breast cancer healthcare professionals (HCP): (1) digital health applications (DHA), (2) artificial intelligence (AI), and (3) blockchain technology (BC). A 22-item questionnaire was designed and administered before and after a 30 min educational presentation highlighting technology implementation examples. Technology awareness and intention-to-use were measured using 7-point Likert scales. Correlations between demographics, technology awareness, intention-to-use, and eHealth literacy (GR-eHEALS scale) were analyzed. 45 HCP completed the questionnaire, of whom 26 (57.8%) were female. Age ranged from 24 to 67 {mean age (SD): 44.93 Ā± 12.62}. Awareness was highest for DHA (68.9%) followed by AI (66.7%) and BC (24.4%). The presentation led to a non-significant increase of intention-to-use AI {5.37 (Ā±1.81) to 5.83 (Ā±1.64)}. HCPsĀ“ intention-to-use BC after the presentation increased significantly {4.30 (Ā±2.04) to 5.90 (Ā±1.67), p < 0.01}. Mean accumulated score for GR-eHEALS averaged 33.04 (Ā± 6.61). HCPsĀ“ intended use of AI significantly correlated with eHealth literacy (Ļ = 0.383; p < 0.01), intention-to-use BC (Ļ = 0.591; p < 0.01) and participantsĀ“ age (Ļ = ā0.438; p < 0.01). This study demonstrates the effect that even a short practical presentation can have on HCPsĀ“ intention-to-use emerging digital technologies. Training potential professional users should be addressed alongside the development of new information technologies and is crucial to increase HCPsĀ“ corresponding awareness and intended use.
In Peru, there is currently no integrated electronic health record (EHR) system that can be automatically shared between healthcare facilities. This leads to increased service costs due to duplicated examinations and records, as well as additional time required to manage patientsā clinical information. One alternative for ensuring the secure interoperability of EHRs while preserving data privacy is the use of blockchain technology. However, existing works consider a pre-established format for exchanging EHRs, which is not applicable when systems have different formats, as is the case in Peru. This work proposes an architecture and a web application for exchanging EHRs in heterogeneous systems. The proposed system includes the homologation of an EHR with rapid interoperability resources for medical attention using FHIR HL7, and vice versa, to achieve interoperability. Additionally, it utilizes blockchain technology to ensure data security and privacy. The web application was tested using a case simulation to demonstrate EHR interoperability between clinics in a clear, secure, and efficient manner. In addition, a survey was conducted with 30 patients regarding adoption, and another survey was conducted with 10 doctors from a public hospital in Peru regarding usability. The results demonstrate a very high level of adoption and usability for them all. Unlike other studies, the proposal does not necessitate alterations to existing EHR systems for interoperability. In other words, the proposal presents a feasible and cost-effective alternative to addressing the EHR interoperability issue in clinics and hospitals in Peru.
Medical and health related information about patients qualifies as sensitive and personal information. There are many laws such as HIPAA that prohibit sharing of a patientās intimate medical data to third party organizations without the full consent of the patient. With this in consideration, when the actual medical health record systems are analysed, vulnerabilities that threatens the confidentiality and integrity of the data were found. The other consideration about the current system is the fact that patients do not have control over their data. Therefore, a decentralized ledger can resolve such security issues, where can have control on their own data. Such a decentralization can be implemented by utilizing blockchain technology. Also, within a decentralized system, many number of participants would be connected as network participants. Hence, a permissioned blockchain system using Ethereum helps in facing these attacks. The proposed Ethereum based Electronic Health Record storage system uses InterPlanetary File System (IPFS), for storing the patientās sensitive data that can be encrypted and only after duly authorized by the patient, a person can view or change it. Further, the proposed Ethereum based Electronic Health Record storage system system can be used to protect other kinds of sensitive data without being limited to health data.
Using wearable devices and WEB3.0 to make doctor-patient interaction smarter. The aging of the population and COVID-19 have placed a tremendous workload on the medical field. Traditional monitoring has been centralized, with healthcare professionals providing face-to-face care to all patients. This is where blockchain is utilized, where users themselves have data and monitor each other. Mutual monitoring of medical information on the blockchain creates a mutually supportive relationship where users themselves monitor each other. In this demonstration experiment, the system was introduced to six elderly people. This decentralized system in which users themselves monitor each other is called the Web3 type. The Web type is a technology that is expected to break through the current concentration of data in overseas digital industries and leave digital data resources in Japan. This research is unique in that it combines blockchain technology, which is at the core of this technology, with medical information. A mutual assistance system was constructed to visualize and mutually monitor their exercise habits using wearable terminals. As a result, the exercise habits of all participants improved, and unique information was obtained from the questionnaire survey.
Health Insurance Portability and Accountability Act Regulations place a high priority on healthcare data security. In 2021, there were over 750 data breaches, and the top seven of those exposed over 193 million personal records to fraud and identity theft. Data security is the process of preventing data from being accessed by unauthorised parties and being corrupted at any point in its lifespan. Data across all apps and platforms is protected via data encryption, hashing, tokenization, and key management procedures. The security solution now in use data encryption software to successfully improve data security by converting plain text into encrypted cypher text using an algorithm (referred to as a cypher) and an encryption key. The encrypted data will be unintelligible to unauthorised individuals. With a permitted key, only that user can then decrypt the data. Yet, when data security becomes more lax, confidential data is lost because the key is so easily hackable due to the use of a single algorithm. This project offers a solution for this issue: an effective data security system that heavily relies on WEB 3.0 and smart contracts to protect data. Additionally, it offers total data protection, ensuring that a hacker is unable to alter the data in any way. The development of a framework known as WEB 3.0 includes a block chain framework to safeguard the data at the backend. Data access does not require an encryption or decryption key, thus there is no need to worry about data breaches or tampering by hackers. Thus, this system offers complete data protection for a hospital's medical records.
Dounia Marbouh, Mecit Can Emre Simsekler, Khaled Salah, Raja Jayaraman Ā· 5 authors
Mobile health (mHealth) is playing a key role in facilitating health services for patients. Such services may include remote diagnostics and monitoring, chronic conditions management, preventive medicine, and health promotion. While mHealth has gained significant traction during the COVID-19 pandemic, they may pose safety risks to patients. This entails regulations and monitoring of shared data and management of potential safety risks of all mHealth applications continuously and systematically. In this study, we propose a blockchain-based framework for regulating mHealth apps and governing their safe use. We systematically identify the needs, stakeholders, and requirements of the current mHealth practices and regulations that may benefit from blockchain features. Further, we exemplify our framework on a diabetes mHealth app that supports safety risk assessment and incident reporting functions. Blockchain technology can offer a solution to achieve this goal by providing improved security, transparency, accountability, and traceability of data among stakeholders. Blockchain has the potential to alleviate existing mHealth problems related to data centralization, poor data quality, lack of trust, and the absence of robust governance. In the paper, we present a discussion on the security aspects of our proposed blockchain-based framework, including limitations and challenges.