Blockchain Papers

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Jun 16, 2026·JMIR Publications Inc.
0 cites
Electronic Visit Verification as a Fraud Surveillance Instrument:Visit-Level Anomaly Analysis, Multi-Agency Comparative Findings, and the Industry-Wide Compliance Engineering Infrastructure in Massachusetts Medicaid Home Care. (Preprint)

Lianne Wachira, Agnes Kiriama

BACKGROUND Home- and community-based services funded through the Medicaid program account for $125 billion in annual federal and state expenditure (Center for Medicare Services, 2023), serving millions of elderly and disabled individuals who receive care in private residences rather than institutional settings. The decentralized nature of home care delivery creates fundamental accountability challenges: services occur in private homes largely beyond direct supervisory oversight, making home care one of the highest-risk categories for Medicaid fraud. Nationwide investigations by the HHS Office of Inspector General from 2011 through 2015 recovered $975 million in fraudulent home health claims (OIG, 2016). A 2024 New York State Comptroller audit documented $14.5 billion in Medicaid personal care payments made without required electronic visit verification (Office of the New York State Comptroller, 2024). In Massachusetts, a 2024 federal conviction established that a home health agency co-owner defrauded MassHealth of at least $100 million over four years through billing for services never rendered (U.S Department of Justice, 2024). Electronic visit verification was mandated under the 21st Century Cures Act (Pub. L. No. 114-255, § 12006, 2016) to address these vulnerabilities by requiring real-time electronic capture of six data elements at each Medicaid-billable visit: service type, recipient identity, date, location, provider identity, and start and end times. MassHealth selected Sandata Technologies as the Commonwealth's designated EVV aggregator, with hard billing edits scheduled no earlier than July 2026 (MassHealth, 2025). Despite widespread EVV implementation nationally, no published peer-reviewed study has empirically characterized visit-level EVV anomaly patterns from operational agency data or documented the industry-wide pre-submission exception management infrastructure through which GPS verification failures are converted into billing-ready records before aggregator transmission. Direct telephone communication with Axxess customer support on June 16, 2026 confirmed that most agencies use the EVV Exception Center and that through this workflow an agency can achieve 100% compliance (Axxess, personal communication, June 16, 2026). WellSky customer support confirmed on the same date that flagged visits can be changed to verified visits prior to state aggregator transmission (WellSky, personal communication, June 16, 2026). OBJECTIVE This study had two primary objectives. First, to characterize the prevalence, typology, and distribution of EVV anomalies through quantitative analysis of 15,172 de-identified visit records from an operational Massachusetts Medicaid home care agency during the pre-enforcement window preceding MassHealth hard billing edits. Second, to document the industry-wide pre-submission exception management infrastructure across six major documentation platforms through direct vendor communication and systematic platform review, and to characterize the response pattern of Massachusetts home care agencies to voluntary research participation requests. METHODS This study employed a five-agency mixed-methods comparative design. Agency A: cross-sectional observational analysis of 15,172 de-identified Sandata EVV visit records from January 1 through May 20, 2026 (140 days; 120 unique patients; 52 caregivers; 11 procedure codes). Written data use authorization was obtained from Agency A leadership. Six anomaly categories were analyzed: GPS location exceptions (GPS_EXCEPTION field); non-verified visit status (VISIT_STATUS field); systematic minimum-time patterns (ACTUAL_TIME = 8.0 minutes exactly); manual time adjustments (both ADJUSTED_IN_TIME and ADJUSTED_OUT_TIME populated); batch backdating (entry creation timestamps versus visit dates); and geographic impossibility (Haversine formula applied to sequential GPS coordinates). Financial exposure was calculated by applying verified 2026 MassHealth fee schedule rates from 101 CMR 350.00 to actual billing units in non-verified visit records. Agency B: operational observation of Axxess Exception Center pre-submission workflows. Agencies C, D, and E: structured professional interviews and research participation solicitation. Twenty additional Massachusetts Medicaid-enrolled agencies were contacted by telephone for voluntary participation between June 15 and 16, 2026. Direct primary source telephone communication was conducted with Axxess and WellSky customer support on June 16, 2026, including step by step exception center workflow on how to correct a mismatched visit. Systematic review of published technical documentation was conducted for six major documentation platforms: Axxess, WellSky/Kinnser, HHAeXchange, AlayaCare, AxisCare, and Alora Health. All analyses were conducted in Microsoft Excel using raw Sandata export data. RESULTS Agency A: GPS exception flags were present in 12,683 of 15,172 visits (83.6%). The GPS_CALL_IN_DISTANCE field, available for 4,983 records, revealed a mean clock-in distance of 12,922 meters from the patient address, a median of 391 meters, and a maximum of 156,956 meters (97.5 miles). A total of 1,410 visits (9.3%) recorded distances exceeding 10 kilometers and 516 visits (3.4%) exceeded 50 kilometers. Non-verified visits totaled 3,333 (22.0%), with estimated potential financial exposure of $246,610 for the five-month period applying verified 2026 MassHealth rates (101 CMR 350.00), annualizing to approximately $642,948 at this single agency. A total of 1,992 visits (13.1%) were documented at exactly eight minutes duration, appearing across four procedure codes including G0299 registered nurse and G0300 licensed practical nurse. Employee E18 recorded 1,304 of 1,441 visits (90.5%) at exactly eight minutes — 6.9 times the agency-wide rate — across four service types, sustained over five months without attenuation. Manual time adjustments affected 601 records (4.0%), with five employees accounting for 299 of 601 adjusted visits (49.8%). Sequential visit records required implied travel speeds of 87 to 230 miles per hour between Massachusetts communities, constituting mathematical proof of fabricated location entries. A weekly batch backdating pattern was identified in which no real-time EVV entries were generated Monday through Thursday, followed by retroactive bulk entry on Friday. Agency B demonstrated systematic use of the Axxess Exception Center to normalize GPS exceptions before Sandata submission, self-reporting 96% compliance — illustrating the EVV Compliance Paradox. Agency C quality assurance professionals identified Drive-By Clock-In Fraud, in which caregivers clock in from within GPS geofence range of a patient's address without entering the premises. Agency D identified a theoretical Complicit Patient vulnerability through dual-device registration. Agency E declined research participation, stating their EVV data was problematic and they did not wish attention called to their records. Of 20 additional agencies approached, zero agreed to participate; responses included -direct refusals, non-responses, and one representative who stated no staff member had any knowledge of EVV. Vendor communication confirmed that most agencies use pre-submission exception management and that flagged visits can be reclassified as verified prior to aggregator transmission (Axxess, personal communication, June 16, 2026; WellSky, personal communication, June 16, 2026). Further documented photographic evidence from Axxess help system showing: The Exception Center workflow step by step, their own template example with a geographically mismatched visit, including a four- day visit error and correction steps: “select a reason code, type clinician signature, click update visit.” Upon completion, the visit is a verified record regardless of the original GPS mismatch or duration anomaly. CONCLUSIONS EVV data contains substantially more actionable fraud intelligence than current practice extracts. Six anomaly categories affecting thousands of visits in a single Massachusetts agency over five months reflect systemic rather than isolated non-compliance. Geographic impossibility requiring 87 to 230 mph implied travel speeds constitutes mathematical proof of GPS location fabrication. Employee E18's sustained eight-minute visit pattern across 1,441 visits and four procedure codes including licensed skilled nursing is statistically impossible as a naturally occurring clinical pattern. The estimated $246,610 in potential financial exposure over five months illustrates the scale of program integrity risk operating within apparently compliant EVV systems. The EVV Compliance Paradox - confirmed by direct vendor communication - demonstrates that compliance rates in GPS-based systems may reflect exception management sophistication rather than care delivery integrity, including the step by step exception center correction workflow that verifies a patient visit with clear original GPS mismatch. The 0% research participation rate across 21 Massachusetts agencies approached, including one that explicitly cited concern about its own EVV data, suggests widespread institutional awareness of compliance vulnerabilities. GPS-based EVV is necessary but structurally insufficient. Hardware-anchored verification requiring physical presence inside the patient's home, supervised biometric enrollment, and cryptographic visit records are the architectural requirements that GPS-based systems cannot meet. Six f

Open access
Geriatric Care and Nursing Homes
Telemedicine and Telehealth Implementation
Healthcare Policy and Management
Original source
May 21, 2026·Studies in health technology and informatics
0 cites
‘The stupid thing is, it’s all about money’: Clinician-Innovators’ Perspectives on Financial Sustainability of Digital Health Innovations in a Large Dutch Hospital1

Zahra Niazkhani, Iris Wallenburg, Johanna Hendriks, Rik Wehrens

In the context of increasing healthcare digitalization, hospital-based clinicians are developing and implementing decentralized digital health innovations (DHIs) tailored to their patient and clinical needs. However, achieving financial sustainability remains one of their challenges. We explored clinician innovators' perspectives on these challenges during the implementation and scale-up of their DHIs in a Dutch academic hospital using qualitative methods. Key challenges identified included funding gaps to cover transition costs, misaligned institutional financial incentives and reimbursement structures, short-term logics of funders overshadowing long-term value in DHI financing, and commercialization pressures. Findings provide insights into the financial and operational challenges faced by such context-driven internal innovations, highlighting the need for coordinated project-and institution-level strategies to support sustainable integration into routine care.

Open access
Healthcare Policy and Management
Telemedicine and Telehealth Implementation
Interprofessional Education and Collaboration
Original source
Mar 25, 2026·Zenodo (CERN European Organization for Nuclear Research)
0 cites
SMART INTER-HOSPITAL COORDINATION NETWORK FOR DISTRIBUTED RESOURCE MANAGEMENT IN RURAL HEALTH SYSTEMS

Heymi Katherine Cerda Reyes

Abstract Rural health systems are networks, which are geographically disseminated and resource limited, in which inefficient inter-hospital coordination has a strong influence on patient outcomes, operational stability and surgical resilience. Regardless of the development of smart hospital technologies, such as 5G-enabled communication opportunities, the integration of digital coordination centers, and telemedicine, the current frameworks are more focused on streamlining intra-hospital processes instead of the inter-hospital distribution of resources. This structural disintegration leads to slow shifts, poor use of bed space, inaccessibility of specialists, and poor responsiveness to surges. This paper suggests Smart Inter-Hospital Representation Network (SIHCN) to be a rural hospital ecosystem distributed systems architecture. The framework combines a granted blockchain based resource registry, real-time capacity monitoring strategies, specialist allocation registries, and adaptive routing logic into a coordination infrastructure. The proposed architecture will be able to guarantee decentralized system control against centralized command models, fault tolerance, and scalable interoperability among autonomous hospital nodes. The paper introduces a conceptual systems model that specifies the network topology, operational data flow, distributed resource synchronization and performance evaluation metrics. The simulation modeling is based on a scenario simulation that assesses the system performance when under routine and emergency surge conditions, showing that the transfer latency, resource balancing, and coordination efficiency is improved. The results make distributed ledger-based coordination a potential engineering technique in enhancing the resilience of rural health networks. This study also addresses the Healthcare Systems Engineering field by re-conceptualizing rural hospital coordination as a distributed resource optimization problem and suggesting an architecture-layer solution that can be applied to low-density, high-variability healthcare settings.

Open access
2 source records
Wireless Body Area Networks
Healthcare Operations and Scheduling Optimization
Telemedicine and Telehealth Implementation
Original source
Jan 1, 2026·International Journal of Preventive Medicine
1 cites
Applying Blockchain in Telemedicine: A Systematic Review

Asghar Ehteshami, Mohammad Sattari

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.

Open access
Blockchain Technology Applications and Security
Telemedicine and Telehealth Implementation
Mobile Health and mHealth Applications
Original source
Apr 24, 2024·Web3 Journal ML in Health Science
0 cites
Xavatar: A Web3 Metaverse Application as a support for Patients with Mobility Disorders

Jason P. Rothberg, Colin Keogh, Yury Rusinovich

Xavatar is a media, educational, and therapeutic platform specializing in immersive virtual reality (VR) and augmented reality (AR) content, as well as seamless interconnectivity across various devices such as mobiles, tablets, and computers. It is aimed at improving the lives of patients with chronic mobility and communication disorders, including dementia, Alzheimer's, autism, chronic immobility, isolation, and long-term hospitalization. The project represents a fusion of digital technologies including the Metaverse, artificial intelligence (AI), and Web3, all designed to enhance healthcare interactions and patient support. This opinion piece explores the transformative potential of Xavatar, highlighting its role in shaping future healthcare landscapes through innovative, empathetic, and engaging digital solutions.

Open access
Artificial Intelligence in Healthcare and Education
Virtual Reality Applications and Impacts
Telemedicine and Telehealth Implementation
Original source
Dec 17, 2023·2023 IEEE International Conference on Blockchain (Blockchain)
9 cites
An Evaluation Framework for Assessing IPFS Performance within a Blockchain-Based Healthcare System

Ghassan Al-Sumaidaee, Rami Alkhudary, Željko Žilić, Andraws Swidan

Blockchain applications require metadata to be associated with the blockchain ledger. Metadata is often stored in centralized cloud servers, which limits the decentralization of the blockchain. Alternatively, metadata can be integrated into distributed storage systems to achieve full decentralization of blockchain networks. However, evaluating the performance of distributed storage systems is often neglected. To address this gap, we present a framework that includes a set of technical indicators. We specifically focus on the InterPlanetary File System (IPFS) as an illustrative distributed storage system and provide a practical use case to demonstrate the application of our framework.

Telemedicine and Telehealth Implementation
Original source
Jan 1, 2023·IEEE Access
93 cites
MedMetaverse: Medical Care of Chronic Disease Patients and Managing Data Using Artificial Intelligence, Blockchain, and Wearable Devices State-of-the-Art Methodology

Dileep Kumar Murala, Sandeep Kumar Panda, Sujata Priyambada Dash

The Metaverse is an online universe that combines virtual reality and augmented reality, linked together via a network.It has generated novel experiences that are fully engaging and transpire in real time, facilitating interpersonal communication and dialogue. Virtual environments with 3D space and avatars can boost patient-facing platforms, operational utilisation, digital education, diagnostics, and treatment choices in medicine and ophthalmology. Globally, there is an increasing prevalence of chronic diseases, with an estimated 25 percent of individuals presently contending with multiple chronic health issues. The management of chronic diseases is currently being rethought in light of the development of technology known together as "Smart Healthcare." A prime example is state-of-the-art wearable technology that incentivizes people to embrace healthier lifestyles through the monitoring of physiological indicators and metabolic processes. With better data organisation and analysis, chronic disease patients may benefit from improved health, privacy, and quality of life. Through the examination of physiological data acquired from wearable devices on a patient, Artificial Intelligence (AI) has the capability to generate informed recommendations pertaining to the diagnosis and treatment of illness. These recommendations can be provided by AI. The adoption of blockchain technology (BC) has the potential to significantly advance healthcare in a variety of ways, including decentralised data sharing, user privacy, user empowerment, and dependability in data administration. The potential impact of Wearable Technologies (WT), Artificial Intelligence (AI), and Blockchain Technology (BC) on Chronic Disease Management (CDM) could be a transition in emphasis from the hospital to the patient. This article provides a patient-centered technical framework for controlling chronic diseases using artificial intelligence, blockchain, and wearable technologies. Our proposed architecture depends on Metaverse environment. In order to participate in the Metaverse, both patients and physicians need to sign up on the Blockchain network. After entering, customers will be accompanied by avatars throughout the experience. A comprehensive record of all information gathered during doctor-patient consultations, including text, videos, images, audio, and clinical data, will be compiled, uploaded to the blockchain, and stored in perpetuity. Explainable Artificial Intelligence (XAI) algorithms examine these particulars in order to diagnose and forecast the progression of diseases. We conclude with a discussion of the constraints of this novel paradigm and recommendations for future research.

Open access
Telemedicine and Telehealth Implementation
Virtual Reality Applications and Impacts
Digital Mental Health Interventions
Original source
May 11, 2022·Trends in Cardiovascular Medicine
177 cites
CardioVerse: The cardiovascular medicine in the era of Metaverse

Ioannis Skalidis, Olivier Müller, Stéphane Fournier

The recent pandemic launched an acceleration in adopting telemedicine by cardiovascular health and triggered the flourishing of technological advancements, such as the metaverse, which is a novel interactive mix of digital worlds that leverages augmented reality with virtual reality. The CardioVerse represents a theoretical term for the embracement of the metaverse by cardiovascular medicine, encompassing the endless possibilities as well as the challenges that it holds and introduces new dimensions to disease education, prevention and diagnosis. Its applications are numerous, notably in enhancing medical visits, assisting cardiovascular interventions and reshaping the way medical education is provided. Although obstacles are expected in diverse domains such as security, technical, legislative and regulatory, the utilization of non-fungible tokens as a security asset for patient data appears as potential solution.

Open access
Artificial Intelligence in Healthcare and Education
Telemedicine and Telehealth Implementation
COVID-19 diagnosis using AI
Original source
Aug 18, 2021·Journal of Medical Internet Research
33 cites
Blockchain Technology Projects to Provide Telemedical Services: Systematic Review

Konstantin Koshechkin, Georgy Lebedev, G.P. Radzievsky, Ralf Seepold · 5 authors

BACKGROUND: One of the most promising health care development areas is introducing telemedicine services and creating solutions based on blockchain technology. The study of systems combining both these domains indicates the ongoing expansion of digital technologies in this market segment. OBJECTIVE: This paper aims to review the feasibility of blockchain technology for telemedicine. METHODS: The authors identified relevant studies via systematic searches of databases including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar. The suitability of each for inclusion in this review was assessed independently. Owing to the lack of publications, available blockchain-based tokens were discovered via conventional web search engines (Google, Yahoo, and Yandex). RESULTS: Of the 40 discovered projects, only 18 met the selection criteria. The 5 most prevalent features of the available solutions (N=18) were medical data access (14/18, 78%), medical service processing (14/18, 78%), diagnostic support (10/18, 56%), payment transactions (10/18, 56%), and fundraising for telemedical instrument development (5/18, 28%). CONCLUSIONS: These different features (eg, medical data access, medical service processing, epidemiology reporting, diagnostic support, and treatment support) allow us to discuss the possibilities for integration of blockchain technology into telemedicine and health care on different levels. In this area, a wide range of tasks can be identified that could be accomplished based on digital technologies using blockchains.

Open access
Blockchain Technology Applications and Security
Telemedicine and Telehealth Implementation
Mobile Health and mHealth Applications
Original source
Sep 19, 2020·International Journal of Medical Informatics
277 cites
The role of blockchain technology in telehealth and telemedicine

Raja Wasim Ahmad, Khaled Salah, Raja Jayaraman, Ibrar Yaqoob · 6 authors

<div><b>Objectives: </b>Telehealth and telemedicine systems aim to deliver remote healthcare services to mitigate the spread of COVID‐19. Also, they can help to manage scarce healthcare resources to control the massive burden of COVID-19 patients in hospitals. However, a large portion of today's telehealth and telemedicine systems are centralized and fall short of providing necessary information security and privacy, operational transparency, health records immutability, and traceability to detect frauds related to patients' insurance claims and physician credentials.</div><div><b>Methods: </b>The current study has explored the potential opportunities and adaptability challenges for blockchain technology in telehealth and telemedicine sector. It has explored the key role that blockchain technology can play to provide necessary information security and privacy, operational transparency, health records immutability, and traceability to detect frauds related to patients' insurance claims and physician credentials.</div><div><b>Results: </b>Blockchain technology can improve telehealth and telemedicine services by offering remote healthcare services in a manner that is decentralized, tamper-proof, transparent, traceable, reliable, trustful, and secure. It enables health professionals to accurately identify frauds related to physician educational credentials and medical testing kits commonly used for home-based diagnosis.</div><div><b>Conclusions: </b>Wide deployment of blockchain in telehealth and telemedicine technology is still in its infancy. Several challenges and research problems need to be resolved to enable the widespread adoption of blockchain technology in telehealth and telemedicine systems.</div><div> </div><div><br></div>

Open access
4 source records
Blockchain Technology Applications and Security
Organizational and Employee Performance
Internet of Things and AI
Original source
Aug 18, 2020·Journal of Medical Internet Research
26 cites
Proposed Implementation of Blockchain in British Columbia’s Health Care Data Management

Danielle Cadoret, Tamara Kailas, Pedro Elkind Velmovitsky, Plinio Pelegrini Morita · 5 authors

BACKGROUND: There are several challenges such as information silos and lack of interoperability with the current electronic medical record (EMR) infrastructure in the Canadian health care system. These challenges can be alleviated by implementing a blockchain-based health care data management solution. OBJECTIVE: This study aims to provide a detailed overview of the current health data management infrastructure in British Columbia for identifying some of the gaps and inefficiencies in the Canadian health care data management system. We explored whether blockchain is a viable option for bridging the existing gaps in EMR solutions in British Columbia's health care system. METHODS: We constructed the British Columbia health care data infrastructure and health information flow based on publicly available information and in partnership with an industry expert familiar with the health systems information technology network of British Columbia's Provincial Health Services Authorities. Information flow gaps, inconsistencies, and inefficiencies were the target of our analyses. RESULTS: We found that hospitals and clinics have several choices for managing electronic records of health care information, such as different EMR software or cloud-based data management, and that the system development, implementation, and operations for EMRs are carried out by the private sector. As of 2013, EMR adoption in British Columbia was at 80% across all hospitals and the process of entering medical information into EMR systems in British Columbia could have a lag of up to 1 month. During this lag period, disease progression updates are continually written on physical paper charts and not immediately updated in the system, creating a continuous lag period and increasing the probability of errors and disjointed notes. The current major stumbling block for health care data management is interoperability resulting from the use of a wide range of unique information systems by different health care facilities. CONCLUSIONS: Our analysis of British Columbia's health care data management revealed several challenges, including information silos, the potential for medical errors, the general unwillingness of parties within the health care system to trust and share data, and the potential for security breaches and operational issues in the current EMR infrastructure. A blockchain-based solution has the highest potential in solving most of the challenges in managing health care data in British Columbia and other Canadian provinces.

Open access
Electronic Health Records Systems
Blockchain Technology Applications and Security
Telemedicine and Telehealth Implementation
Original source
Jan 1, 2020·PubMed
17 cites
Development of A Blockchain Framework for Virtual Clinical Trials.

Yan Zhuang, Lincoln Sheets, Xiyuan Gao, Yuanyuan Shen · 7 authors

Clinical trials are essential for discovering new treatments, but there are multiple challenges to patient recruitment, patient engagement, and cost containment. Virtual clinical trials (VCT) are an innovative approach that provides potential solutions by conducting home-based, rather than site-based, clinical trials. Virtual clinical trials are still the exception rather than general practice due to technical barriers. "Blockchain," a distributed ledger technology, is a perfect match for virtual clinical trials. Its peer-to-peer design, security settings, and data transparency meet the needs of many healthcare applications. The programmable "Smart Contract" feature makes blockchain more suitable and feasible for VCT by solving computational issues. Our previous work has shown the power of applying blockchain to clinical trial recruitment. This work develops a comprehensive blockchain framework, with simulations and case studies, including patient recruitment, patient engagement, and persistent monitoring modules.

Open access
Digital Mental Health Interventions
Blockchain Technology Applications and Security
Telemedicine and Telehealth Implementation
Original source
May 2, 2018·Telehealth and Medicine Today
10 cites
Using Telehealth as a Model for Blockchain HIT Adoption

Brennan Bennett

Telemedicine and blockchain technology share a core philosophy of empowering the individual. Blockchain solutions that focus on empowering patients and enhancing the workflows for the providers who treat them continue to make big headlines, as does enterprise investment and adoption of telehealth. Both models focus on direct-to-consumer health services, with a personalized care experience designed from the ground up to save time and money for everyone involved. The typical binding factor between the telehealth and HIT (health information technology) blockchain adoption is a patient centric, value-based care model. Therefore, it is as no coincidence that value-based care is at the center of the fastest growing (and operational) part of HIT blockchain adoption. For this reason, telehealth can demonstrate adoption synergies than most other lines of business in healthcare cannot.

Open access
Telemedicine and Telehealth Implementation
Original source
Jun 1, 2016·CHEST Journal
0 cites
Response

Gulrukh Zaidi

No abstract is available for this record.

Open access
Ultrasound in Clinical Applications
Telemedicine and Telehealth Implementation
Radiology practices and education
Original source
Sep 10, 2008·Proceedings of the 2008 Euro American Conference on Telematics and Information Systems
4 cites
A flexible web oriented telehealth platform using a RIM-HL7 based model

César Sánchez, Edwin Triana, Eduardo Romero

This article presents a web oriented telehealth platform adapted to the social and economic conditions of a developing country like Colombia. The platform aims to satisfy health care needs integrating modules for telemedicine, where medical processes are modelled following the HL7 Reference Information Model which has allowed easy inclusion of many specialities such as dermatology, radiology, cardiology, pathology and infection diseases, among others. The system implements many security mechanisms such as Digital Signature and Zero Knowledge Proof for authentication. A telecare real-time module measures patient's vital signs such as blood pressure, electrocardiogram, oxygen saturation and sends them over the network to monitor patient's health. After 19 months of service, the system processed 4.751 actual telemedicine cases from 31 remote stations with an average response time of 1, 3 days, showing flexibility, security and scalability.

Healthcare Systems and Technology
Electronic Health Records Systems
Telemedicine and Telehealth Implementation
Original source