992 research outputs found
FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data
Secure and scalable data sharing is essential for collaborative clinical
decision making. Conventional clinical data efforts are often siloed, however,
which creates barriers to efficient information exchange and impedes effective
treatment decision made for patients. This paper provides four contributions to
the study of applying blockchain technology to clinical data sharing in the
context of technical requirements defined in the "Shared Nationwide
Interoperability Roadmap" from the Office of the National Coordinator for
Health Information Technology (ONC). First, we analyze the ONC requirements and
their implications for blockchain-based systems. Second, we present FHIRChain,
which is a blockchain-based architecture designed to meet ONC requirements by
encapsulating the HL7 Fast Healthcare Interoperability Resources (FHIR)
standard for shared clinical data. Third, we demonstrate a FHIRChain-based
decentralized app using digital health identities to authenticate participants
in a case study of collaborative decision making for remote cancer care.
Fourth, we highlight key lessons learned from our case study
DESIGN AND EXPLORATION OF NEW MODELS FOR SECURITY AND PRIVACY-SENSITIVE COLLABORATION SYSTEMS
Collaboration has been an area of interest in many domains including education, research, healthcare supply chain, Internet of things, and music etc. It enhances problem solving through expertise sharing, ideas sharing, learning and resource sharing, and improved decision making.
To address the limitations in the existing literature, this dissertation presents a design science artifact and a conceptual model for collaborative environment. The first artifact is a blockchain based collaborative information exchange system that utilizes blockchain technology and semi-automated ontology mappings to enable secure and interoperable health information exchange among different health care institutions. The conceptual model proposed in this dissertation explores the factors that influences professionals continued use of video- conferencing applications. The conceptual model investigates the role the perceived risks and benefits play in influencing professionals’ attitude towards VC apps and consequently its active and automatic use
Neuroadaptive incentivization in healthcare using Blockchain and IoT
Financially incentivizing health-related behaviors can improve health record outcomes and reduce healthcare costs. Blockchain and IoT technologies can be used to develop safe and transparent incentive schemes in healthcare. IoT devices, such as body sensor networks and wearable sensors, etc. connect the physical and digital world making it easier to collect useful health-related data for further analysis. There are, however, many security and privacy issues with the use of IoT. Some of these IoT security issues can be alleviated using Blockchain technology. Incorporating neuroadaptive technology can result in more personalized and effective therapies using machine learning algorithms and real-time feedback. The research investigates the possibilities of neuroadaptive incentivization in healthcare using Blockchain and IoT on patient health records. The core idea is to incentivize patients to keep their health parameters within standard range thereby reducing the load on healthcare system. In summary, we have presented a proof of concept for neuroadaptive incentivization in healthcare using Blockchain and IoT and discuss various applications and implementation challenges
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