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- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
This thesis concerns the adoption of health information technology in the medical sector, specifically electronic health records (EHRs). EHRs have been seen as a great benefit to the healthcare system and will improve the quality of patient care. The federal government, has seen the benefit EHRs can offer, has been advocating the use and adoption of EHR for nearly a decade now. They have created policies that guide medical providers on how to implement EHRs. However, this thesis concerns the attitudes medical providers in Phoenix have towards government implementation. By interviewing these individuals and cross-referencing their answers with the literature this thesis wants to discover the pitfalls of federal government policy toward EHR implementation and EHR implementation in general. What this thesis found was that there are pitfalls that the federal government has failed to address including loss of provider productivity, lack of interoperability, and workflow improvement. However, the providers do say there is still a place for government to be involved in the implementation of EHR.
ContributorsKaldawi, Nicholas Emad (Author) / Lewis, Paul (Thesis director) / Cortese, Denis (Committee member) / Jones, Ruth (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2013-05
Description
We seek a comprehensive measurement for the economic prosperity of persons with disabilities. We survey the current literature and identify the major economic indicators used to describe the socioeconomic standing of persons with disabilities. We then develop a methodology for constructing a statistically valid composite index of these indicators, and build this index using data from the 2014 American Community Survey. Finally, we provide context for further use and development of the index and describe an example application of the index in practice.
ContributorsTheisen, Ryan (Co-author) / Helms, Tyler (Co-author) / Lewis, Paul (Thesis director) / Reiser, Mark (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
College athletics are a multi-billion dollar industry featuring hard-working student-athletes competing at a high level for national championships across a variety of different sports. Across the college sports landscape, coaches and players are always seeking an edge they can gain in order to obtain a competitive advantage over their opponents. While this may sound nefarious, the vast amounts of data about these games and student-athletes can be used to glean insights about the sports themselves in order to help student-athletes be more successful. Data analytics can be used to make sense of the available data by creating models and using other tools available that can predict how student-athletes and their teams will do in the future based on the data gathered from how they have performed in the past.
Colleges and universities across the country compete in a vast array of sports. As a result of these differences, the sports with the largest amounts of data available will be the more popular college sports, such as football, men’s and women’s basketball, baseball and softball. Arizona State University, as a member of the Pac-12 conference, has a storied athletic tradition and decades of history in all of these sports, providing a large amount of data that can be used to analyze student-athlete success in these sports and help predict future success. However, data is available from numerous other college athletic programs that could provide a much larger sample to help predict with greater accuracy why certain teams and student-athletes are more successful than others.
The explosion of analytics across the sports world has resulted in a new focus on utilizing statistical techniques to improve all aspects of different sports. Sports science has influenced medical departments, and model-building has been used to determine optimal in-game strategy and predict the outcomes of future games based on team strength. It is this latter approach that has become the focus of this paper, with football being used as a subject due to its vast popularity and massive supply of easily accessible data.
ContributorsLindstrom, Trent (Author) / Schneider, Laurence (Thesis director) / Wilson, Jeffrey (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Politics and Global Studies (Contributor)
Created2022-05