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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


"Too often, people in pain are stuck in limbo. With no diagnosis there is no prognosis. They feel that without knowing what is wrong, there is no way to make it right" (Lewandowski, 2006, p. ix). Research has shown that environmental factors, such as views of nature, positive distractions and natural light can reduce anxiety and pain (Ulrich, 1984). Patients with chronic, painful diseases are often worried, anxious and tired. Doctor's appointments for those with a chronic pain diagnosis can be devastating (Gilron, Peter, Watson, Cahill, & Moulin, 2006). The research question explored in this study is: Does the layout, …

Contributors
Draper, Heather Rashid, Bender, Diane, Shraiky, James, et al.
Created Date
2012

The analysis of clinical workflow offers many challenges to clinical stakeholders and researchers, especially in environments characterized by dynamic and concurrent processes. Workflow analysis in such environments is essential for monitoring performance and finding bottlenecks and sources of error. Clinical workflow analysis has been enhanced with the inclusion of modern technologies. One such intervention is automated location tracking which is a system that detects the movement of clinicians and equipment. Utilizing the data produced from automated location tracking technologies can lead to the development of novel workflow analytics that can be used to complement more traditional approaches such as ethnography …

Contributors
Vankipuram, Akshay, Patel, Vimla L, Wang, Dongwen, et al.
Created Date
2018