Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- All Subjects: healthcare
- Creators: O'Flaherty, Katherine
- Creators: Boscovic, Dragan
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.
This research paper focuses on how the idea of suffering has evolved over time in the United States healthcare system. Different aspects like long vs short-term illnesses, bias, and more were inspected to determine how they play a part in increased or decreased patient suffering. The final determination of how suffering in the system has evolved and what to do with this information is also discussed.
