Browsing by Author "Li, Meng-Hao"
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Item Multi-state Markov Models for the Analysis of EMRs Diffusion in Healthcare(2022) Li, Meng-Hao; Li, Meng-Hao; Schintler, LauriePrior studies on diffusion of innovations typically research the same units of analysis, top-down diffusion, bottom-up diffusion, spatial proximity or network analysis, paying little or no attention to the effect of bottom-up networks on the multilevel diffusion process. The adoption decision is formed at the organizational level, but the factors that formulate the decision possibly result from either inter- or intra-organizational networks, or mixed effects of inter- and intra-organizational networks. It remains unclear how individuals and organizations respectively are exposed to adoption information in their networks and collectively form an adoption decision at the organizational level. Using data (2009-2015) from the hospital’s adoption of Electronic Medical Records (EMRs), individual healthcare provider referral networks, and hospital system networks, this study applies multi-state Markov models to examine how the mixed effect of intra- and inter-hospital networks influences the process of bottom-up EMRs diffusion. The findings suggest that hospital system networks, individual provider networks within and between hospitals, and proximity of hospital locations play different roles in the transitions between EMRs states (i.e., non-adopters, basic adopters, intermediate adopters, and comprehensive adopters). The results enrich our understanding of how individuals (bottom) in an organization interact with internal and external environments to influence the organization’s decisions (up) collectively. This study further offers four network-based policy intervention strategies for facilitating the adoption of advanced EMRs and suggests devising an EMRs incentive scheme based on hospital EMRs states.Publication Project 4: Gut Microbiome and Kidney Transplant(George Mason University, 2023-08) Cho, Minseo; Herdrich, Kyle; Jung, Isaac; Liu, Jiahui; Li, Meng-HaoBackground: The gut microbiota, comprising the entire population of microorganisms that colonize the colon, has evolved over time to establish a symbiotic relationship with the human body, yielding mutual benefits [1]. This microbiome plays a pivotal role in critical bodily functions, including biosynthesis, short-chain fatty acid (SCFA) production, gut regulation, and immune system function. Under normal circumstances, these gut bacteria are referred to as indigenous microbiota, performing their customary functions; however, in the presence of disturbances, detrimental or opportunistic bacteria emerge, known as pathobionts [2]. Imbalances within the gut microbiota have been associated with various diseases, including obesity, metabolic disorders, inflammatory bowel diseases, colorectal cancer, allergies, and autoimmune disorders [1]. Of particular concern is the impact of immunosuppressants and antibiotics administered after kidney transplant surgeries, as they disrupt the patients' gut microbiome, alter indigenous microbiota, and promote the proliferation of pathobionts, resulting in a condition known as dysbiosis. Dysbiosis, in turn, may facilitate the development of acute kidney injury (AKI) by modifying SCFA composition and generating elevated levels of toxins. Both AKI and pathobionts can contribute to the progression of atherosclerosis, cardiovascular diseases, inflammation, and chronic kidney disease (CKD). If left untreated, CKD can escalate to infections and even rejection of the newly transplanted kidney by the recipient's immune system [2]. Objective: This project aims to 1) examine the degree of change occurred in the abundance and diversity of the gut microbiome, before and after kidney transplantation, and 2) identify treatments that support the microbiome in returning to its healthy, stable state.Publication Project 7: Viruses and Host Membranes(George Mason University, 2023-08) Jacob, Riya; Kefale, Mikael; Khanna, Jahnavi; Kim, Andrew Jacob; McLaughlin, Madison; Li, Meng-HaoBackground: Rabies is a zoonotic disease caused by an unsegmented RNA virus of the Lyssavirus genus. It spreads between animals and humans through contact with mucosal membranes, abrasions, or the saliva of an infected animal, most commonly a dog. The rabies virus travels through the body's signal transmission pathways to reach the central nervous system and brain. Once it has entered the host, it attaches itself to nerve cells and begins to replicate. The virus then spreads throughout the body through neuronal pathways until it reaches the brain. The incubation period varies widely depending on the location of the bite and the severity of the infection. Once the virus reaches the brain, symptoms increase in severity, starting from flu-like symptoms to hydrophobia and delirium. The infected person enters the prodromal phase, during which they experience significant behavioral and physical changes, such as heightened aggression and pupil dilation. Progression to the "excited" or "furious" rabies phase leads to autonomic dysfunction and vicious, erratic behavior. The infected person may die in this phase or progress to the final stage, paralytic rabies, where they will eventually die. Objective: This project aims to develop a comprehensive understanding of mechanisms for infectivity (attachment and entry) by defining the landscape of rabies virus research through bibliometric analysis.