Employing qualitative methods and drawing from an intersectional framework which focuses on the multiple identities we all embody, this dissertation focuses on oppressions and resistance strategies employed by women of color in Xbox live, an online gaming community. Ethnographic observations and narrative interviewing reveal that women of color, as deviants within the space, face intersecting oppressions in gaming as in life outside the gaming world. They are linguistically profiled within the space based off of how they sound. They have responded with various strategies to combat the discrimination they experience. Some segregate themselves from the larger gaming population and many refuse to purchase games that depict women in a hyper-sexualized manner or that present people of color stereotypically. For others, the solution is to "sit-in" on games and disrupt game flow by 'player-killing' or engage in other 'griefing' activities. I analyze this behavior in the context of Black feminist consciousness and resistance and uncover that these methods are similar to women who employ resistance strategies for survival within the real world.

As much as SARS-CoV-2 has altered the way humans live since the beginning of 2020,<br/>this virus's deadly nature has required clinical testing to meet 2020's demands of higher<br/>throughput, higher accuracy and higher efficiency. Information technology has allowed<br/>institutions, like Arizona State University (ASU), to make strategic and operational changes to<br/>combat the SARS-CoV-2 pandemic. At ASU, information technology was one of the six facets<br/>identified in the ongoing review of the ASU Biodesign Clinical Testing Laboratory (ABCTL)<br/>among business, communications, management/training, law, and clinical analysis. The first<br/>chapter of this manuscript covers the background of clinical laboratory automation and details<br/>the automated laboratory workflow to perform ABCTL’s COVID-19 diagnostic testing. The<br/>second chapter discusses the usability and efficiency of key information technology systems of<br/>the ABCTL. The third chapter explains the role of quality control and data management within<br/>ABCTL’s use of information technology. The fourth chapter highlights the importance of data<br/>modeling and 10 best practices when responding to future public health emergencies.

For our project, we explored the growth of the ASU BioDesign Clinical Testing Laboratory (ABCTL) from a standard university research lab to a COVID-19 testing facility through a business lens. The lab has pioneered the saliva-test in the Western United States. This thesis analyzes the laboratory from various business concepts and aspects. The business agility of the lab and it’s quickness to innovation has allowed the lab to enjoy great success. Looking into the future, the laboratory has a promising future and will need to answer many questions to remain the premier COVID-19 testing institution in Arizona.

For our project, we explored the growth of the ASU BioDesign Clinical Testing Laboratory (ABCTL) from a standard university research lab to a COVID-19 testing facility through a business lens. The lab has pioneered the saliva-test in the Western United States. This thesis analyzes the laboratory from various business concepts and aspects. The business agility of the lab and it’s quickness to innovation has allowed the lab to enjoy great success. Looking into the future, the laboratory has a promising future and will need to answer many questions to remain the premier COVID-19 testing institution in Arizona.

Social media sites focusing on health-related topics are rapidly gaining popularity among online health consumers, also known as "e-patients". The increasing adoption of social media by e-patients and their demand for reliable health information has prompted several health care organizations (HCOs) to establish their social media presence. HCOs are using social media to connect with current and potential e-patients, and improve patient education and overall quality of care. A significant benefit for HCOs in using social media could potentially be the improvement of their quality of care, as perceived by patients. Perceived quality of care is a key determinant of patients' experience and satisfaction with health care services, and has been a major focus of research. However, there is very little research on the relationship between patients' online social media experience and their perceived quality of care. The objective of this research was to evaluate e-patients' online experience with an HCO's social media sites and examine its impact on their perceived quality of care. Research methodology included a combination of qualitative and quantitative approaches. Data for this study was collected from Mayo Clinic's social media sites through an online survey. Descriptive statistics were used to identify basic demographic profiles of e-patients. Linear regression analysis was used to examine the relationship between online experience and perceived quality of care. Qualitative data was analyzed using thematic analysis. Results showed a positive relationship between online experience and perceived quality of care. Qualitative data provided information about e-patients' attitudes and expectations from healthcare social media. Overall, results yielded insights on design and management of social media sites for e-patients, and integration of these online applications in the health care delivery process. This study is of value to HCOs, health communicators and social media designers, and will also serve as a foundation for subsequent studies in the area of health care social media.

As much as SARS-CoV-2 has altered the way humans live since the beginning of 2020, this virus's deadly nature has required clinical testing to meet 2020's demands of higher throughput, higher accuracy and higher efficiency. Information technology has allowed institutions, like Arizona State University (ASU), to make strategic and operational changes to combat the SARS-CoV-2 pandemic. At ASU, information technology was one of the six facets identified in the ongoing review of the ASU Biodesign Clinical Testing Laboratory (ABCTL) among business, communications, management/training, law, and clinical analysis. The first chapter of this manuscript covers the background of clinical laboratory automation and details the automated laboratory workflow to perform ABCTL’s COVID-19 diagnostic testing. The second chapter discusses the usability and efficiency of key information technology systems of the ABCTL. The third chapter explains the role of quality control and data management within ABCTL’s use of information technology. The fourth chapter highlights the importance of data modeling and 10 best practices when responding to future public health emergencies.

This project is designed as part of the multi-student ASU Biodesign Clinical Testing Laboratory (ABCTL) thesis project sponsored and organized by Dr. Carolyn Compton, professor of Life Sciences at ASU and medical director with the ABCTL. This project divides students into teams with Business, Law, Laboratory, IT, and Documentary focused groups, with the goal of providing a comprehensive overview of the operations of the ABCTL as a reference for other institutions and to produce a documentary film about the laboratory. As a member of the IT team, this writeup will focus on quality control throughout the transfer of data in the testing process, security and privacy of data, HIPAA and regulatory compliance, and accessibility of data while maintaining such restrictions.

As much as SARS-CoV-2 has altered the way humans live since the beginning of 2020, this virus's deadly nature has required clinical testing to meet 2020's demands of higher throughput, higher accuracy and higher efficiency. Information technology has allowed institutions, like Arizona State University (ASU), to make strategic and operational changes to combat the SARS-CoV-2 pandemic. At ASU, information technology was one of the six facets identified in the ongoing review of the ASU Biodesign Clinical Testing Laboratory (ABCTL) among business, communications, management/training, law, and clinical analysis. The first chapter of this manuscript covers the background of clinical laboratory automation and details the automated laboratory workflow to perform ABCTL’s COVID-19 diagnostic testing. The second chapter discusses the usability and efficiency of key information technology systems of the ABCTL. The third chapter explains the role of quality control and data management within ABCTL’s use of information technology. The fourth chapter highlights the importance of data modeling and 10 best practices when responding to future public health emergencies.