Comparative Analysis of the Hypergraph Transfer Protocol & Layer-2 Scalability Protocol

Description

Through my work with the Arizona State University Blockchain Research Lab (BRL) and JennyCo, one of the first Healthcare Information (HCI) HIPAA - compliant decentralized exchanges, I have had the opportunity to explore a unique cross-section of some of the…

Through my work with the Arizona State University Blockchain Research Lab (BRL) and JennyCo, one of the first Healthcare Information (HCI) HIPAA - compliant decentralized exchanges, I have had the opportunity to explore a unique cross-section of some of the most up and coming DLTs including both DAGs and blockchains. During this research, four major technologies (including JennyCo’s own systems) presented themselves as prime candidates for the comparative analysis of two models for implementing JennyCo’s system architecture for the monetization of healthcare information exchanges (HIEs). These four identified technologies and their underlying mechanisms will be explored thoroughly throughout the course of this paper and are listed with brief definitions as follows: Polygon - “Polygon is a “layer two” or “sidechain” scaling solution that runs alongside the Ethereum blockchain. MATIC is the network’s native cryptocurrency, which is used for fees, staking, and more” [8]. Polygon is the scalable layer involved in the L2SP architecture. Ethereum - “Ethereum is a decentralized blockchain platform that establishes a peer-to-peer network that securely executes and verifies application code, called smart contracts.” [9] This foundational Layer-1 runs thousands of nodes and creates a unique decentralized ecosystem governed by turing complete automated programs. Ethereum is the foundational Layer involved in the L2SP. Constellation - A novel Layer-0 data-centric peer-to-peer network that utilizes the “Hypergraph Transfer Protocol or HGTP, a DLT known as a [DAG] protocol with a novel reputation-based consensus model called Proof of Reputable Observation (PRO). Hypergraph is a feeless decentralized network that supports the transfer of $DAG cryptocurrency.” [10] JennyCo Protocol - Acts as a HIPAA compliant decentralized HIE by allowing consumers, big businesses, and brands to access and exchange user health data on a secure, interoperable, and accessible platform via DLT. The JennyCo Protocol implements utility tokens to reward buyers and sellers for exchanging data. Its protocol nature comes from its DLT implementation which governs the functioning of on-chain actions (e.g. smart contracts). In this case, these actions consist of secure and transparent health data exchange and monetization to reconstitute data ownership to those who generate that data [11]. With the direct experience of working closely with multiple companies behind the technologies listed, I have been exposed to the benefits and deficits of each of these technologies and their corresponding approaches. In this paper, I will use my experience with these technologies and their frameworks to explore two distributed ledger architecture protocols in order to determine the more effective model for implementing JennycCo’s health data exchange. I will begin this paper with an exploration of blockchain and directed acyclic graph (DAG) technologies to better understand their innate architectures and features. I will then move to an in-depth look at layered protocols, and healthcare data in the form of EHRs. Additionally, I will address the main challenges EHRs and HIEs face to present a deeper understanding of the challenges JennyCo is attempting to address. Finally, I will demonstrate my hypothesis: the Hypergraph Transfer Protocol (HGTP) model by Constellation presents significant advantages in scalability, interoperability, and external data security over the Layer-2 Scalability Protocol (L2SP) used by Polygon and Ethereum in implementing the JennyCo protocol. This will be done through a thorough breakdown of each protocol along with an analysis of relevant criteria including but not limited to: security, interoperability, and scalability. In doing so, I hope to determine the best framework for running JennyCo’s HIE Protocol.

Date Created
2023-05
Agent

Navigational Complexity Framework for EHR-Mediated Workflow in Perioperative Care

162000-Thumbnail Image.png
Description
Usability problems associated with electronic health records can adversely impact clinical workflow, leading to inefficiencies, error, and even clinician burnout. The work presented in this dissertation is concerned with understanding and improving clinical workflow. Towards that end, it is necessary…

Usability problems associated with electronic health records can adversely impact clinical workflow, leading to inefficiencies, error, and even clinician burnout. The work presented in this dissertation is concerned with understanding and improving clinical workflow. Towards that end, it is necessary to model physical and cognitive aspects of task performance in clinical settings. Task completion can be significantly impacted by the navigational efficiency of the electronic health record (EHR) interface. Workflow modeling of the EHR-mediated workflow could help identify, diagnose and eliminate problems to reduce navigational complexity. The research goal is to introduce and validate a new biomedical informatics methodological workflow analysis framework that combines expert-based and user-based techniques to guide effective EHR design and reduce navigational complexity. These techniques are combined into a modified walkthrough that aligns user goals and subgoals with estimated task completion time and characterization of cognitive demands. A two-phased validation of the framework is utilized. The first is applied to single EHR-mediated workflow tasks, medication reconciliation (MedRec), and medication administration records (MAR) to refine individual aspects of the framework. The second phase applied the framework to a pre/post EHR implementation comparative analysis of multiple workflows tasks. This validation provides evidence of the framework's applicability and feasibility across several sites, systems, and settings. Analysis of the steps executed within the interfaces involved to complete the medication administration and medication reconciliation and patient order management tasks have provided a basis for characterizing the complexities in EHR navigation. An implication of the work presented here is that small tractable changes in interface design may substantially improve EHR navigation, overall usability, and workflow. The navigational complexity framework enables scrutinizing the impact of different EHR interfaces on task performance and usability barriers across different sites, systems, and settings.
Date Created
2021
Agent

Medical Devices Digital Threads and their Supply-Chain Management on Blockchain

161388-Thumbnail Image.png
Description
Blockchain technology is defined as a decentralized, distributed ledger recording the origin of a digital asset and all of its updates without the need of any governing authority. In Supply-Chain Management, Blockchain can be used very effectively, leading to a…

Blockchain technology is defined as a decentralized, distributed ledger recording the origin of a digital asset and all of its updates without the need of any governing authority. In Supply-Chain Management, Blockchain can be used very effectively, leading to a more open and reliable supply chain. In recent years, different companies have begun to use blockchain to build blockchain-based supply chain solutions. Blockchain has been shown to help provide improved transparency across the supply chain. This research focuses on the supply chain management of medical devices and supplies using blockchain technology. These devices are manufactured by the authorized device manufacturers and are supplied to the different healthcare institutions on their demand. This entire process becomes vulnerable as there is no track of individual product once it gets shipped till it gets used. Traceability of medical devices in this scenario is hardly efficient and not trustworthy. To address this issue, the paper presents a blockchain-based solution to maintain the supply chain of medical devices. The solution provides a distributed environment that can track various medical treatments from production to use. The finished product is stored in the blockchain through its digital thread. Required details are added from time to time which records the entire virtual life-cycle of the medical device forming the digital thread. This digital thread adds traceability to the existing supply chain. Keeping track of devices also helps in returning the expired devices to the manufacturer for its recycling. This blockchain-based solution is mainly composed of two phases. Blockchain-based solution design, this involves the design of the blockchain network architecture, which constitutes the required smart contract. This phase is implemented using the secure network of Hyperledger Fabric (HLF). The next phase includes the deployment of the generated network over the Kubernetes to make the system scalable and more available. To demonstrate and evaluate the performance matrix, a prototype solution of the designed platform is implemented and deployed on the Kubernetes. Finally, this research concludes with the benefits and shortcomings of the solution with future scope to make this platform perform better in all aspects.
Date Created
2021
Agent

Behavioral Health Providers’ Perspectives on Granular Information Sharing

132047-Thumbnail Image.png
Description
Granular information sharing allows patients to have more control over their medical records by giving them the choice of what information to share and with whom. Numerous studies have focused on patients’ perspectives, but this study focuses on the provider…

Granular information sharing allows patients to have more control over their medical records by giving them the choice of what information to share and with whom. Numerous studies have focused on patients’ perspectives, but this study focuses on the provider views of granular information sharing. Twenty-eight behavioral health providers (n=3 prescribers, n=25 non-prescribers) from two different integrated healthcare facilities participated in a 2-hour focus group and took a survey at the beginning and at the end of the focus group. The survey responses were analyzed using descriptive analysis to understand how the providers' preferences changed from the pre-study to the post-study. Most providers changed their view about granular information sharing, as 30% of providers “were OK with patients having control over who sees what information in their electronic health record”, previously 83%. Overall, health care providers had concerns that granular information sharing because they feared that it would lead to increased costs, patient safety issues involving drug-drug interactions, and poor provider-patient relationships.
Date Created
2019-12
Agent

Systematic Literature Review of Prescription Drug Monitoring Programs

133692-Thumbnail Image.png
Description
Prescription opioid abuse has become a serious national problem. To respond to the opioid epidemic, states have created prescription drug monitoring programs (PDMPs) to monitor and reduce opioids use. We conducted a systematic literature review to better understand metrics used…

Prescription opioid abuse has become a serious national problem. To respond to the opioid epidemic, states have created prescription drug monitoring programs (PDMPs) to monitor and reduce opioids use. We conducted a systematic literature review to better understand metrics used to quantify the effect that PDMPs have had on reducing opioid abuse, and solutions and challenges related to the integration of PDMPs with EHRs. Lessons learned can help guide federal and state-based efforts to better respond to the current opioid crisis.
Date Created
2018-05
Agent

Behavioral Health Provider Perspectives on Health Data Sharing

134042-Thumbnail Image.png
Description
Integrating behavioral and physical health is the key to value-based care. Little is known about data sharing preferences and consent practices for individuals with behavioral health conditions. This study focuses on identifying behavioral health provider perceptions about patient data sharing…

Integrating behavioral and physical health is the key to value-based care. Little is known about data sharing preferences and consent practices for individuals with behavioral health conditions. This study focuses on identifying behavioral health provider perceptions about patient data sharing practices, preferences and perceived impact on care resulting from enhanced patient control of record types during consent for data sharing.
Date Created
2017-12
Agent
Subscribe to Grando, Adela