Tinnitus is a conscious perception of phantom sounds in the absence of external acoustic stimuli, and masking is one of the popular ways to treat it. Due to the variation in the perceived tinnitus sound from patient to patient, the usefulness of masking therapy cannot be generalized. Thus, it is important to first determine the feasibility of masking therapy on a particular patient, by quantifying the tinnitus sound, and then generate an appropriate masking signal. This paper aims to achieve this kind of individual profiling by developing interactive software -Tinnitus Analyzer, based on clinical approach. The developed software has been proposed to be used in place of traditional clinical methods and this software (as a part of the future work) will be implemented in the practical scenario involving real tinnitus patients. / by Bashali Chaudbury. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Discrimination is not only a human and civil rights offense, but also a detrimental influence on the health outcomes of affected populations. The Muslim population in the United States is a growing religious minority increasingly encountered by health care professionals in the clinical setting. This group has been subject to heightened discrimination since the tragic events of September 11, 2001 and often is misunderstood within the context of American society today. While research has been conducted on discrimination against Muslims in the employment and educational segments of society, more studies are needed which quantify the extent and type of discrimination faced by this group in the health care setting. This inquiry focused on the crossover of anti-Muslim discrimination from society to the health care setting. A newly developed tool to measure anti-Muslim discrimination in health care and an established perceived discrimination scale were used to create the questionnaire employed in this investigation. The items of this newly created tool addressed culturally congruent care practices based on the principles of cultural safety within the nurse-patient relationship and the cultural care beliefs of the Muslim patient/family to ascertain discriminatory occurrences in the health care setting. Ray’s (2010) transcultural caring dynamics in nursing and health care model served as a framework for this quantitative, univariate, descriptive, cross-sectional design. Findings revealed that nearly one-third of Muslim subjects perceived they were discriminated against in the health care setting in the United States. Being excluded or ignored was the most frequently conveyed type of discrimination, followed by problems related to the use of Muslim clothing; offensive or insensitive verbal remarks; and problems related to Islamic holidays, prayer rituals, and physical assault, respectively. Age was positively correlated with perceived anti-Muslim discrimination in society. Education was negatively correlated with perceived discrimination in both society and the health care setting. Findings revealed that three out of five of those surveyed reported that they wear Muslim clothing; the most frequently reported of which was the hijab, the most popular Muslim garment reported to be worn. Participants who wore Muslim clothing, especially females, reported more anti-Muslim discrimination than those who did not. Scores for self-reported perceived anti-Muslim discrimination were found to be higher after the Boston Marathon bombings, April 15, 2013, an act perpetrated by Muslims, which occurred during the time of data collection. The number one Muslim care preference reported was same sex caregiver followed by respect for modesty, prayer rituals, respect for privacy, family involvement in care, and dietary concerns. Implications for practice, policy, education, political science, and recommendations for further research are discussed. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2013.

This dissertation examines factors with influence on the organizational cultural competence of Emergency Medical Services (EMS) systems. The purpose of this study was to draw on theories of representative bureaucracy and transformational leadership to assess cultural competence in Emergency Medical Services systems from the perspective of EMS leadership, within careful consideration of the external environment in which EMS systems operate. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2015 / FAU Electronic Theses and Dissertations Collection

Thesis. 1976. Ph.D.--Massachusetts Institute of Technology. Dept. of Urban Studies and Planning. / Microfiche copy available in Archives and Rotch. / Bibliography: leaves 484-485. / Ph.D.

Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by David Howard Turkel. / B.S.

Thesis. 1979. M.C.P.--Massachusetts Institute of Technology. Dept. of Urban Studies and Planning. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. / Bibliography: leaves 93-95. / M.C.P.

Thesis. 1975. M.C.P.--Massachusetts Institute of Technology. Dept. of Urban Studies and Planning. / Bibliography: leaves 103-109. / by Georgia A. Lovett. / M.C.P.

Thesis. 1975. M.S.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management. / Bibliography: leaves 138-140. / M.S.

Significant out-of-pocket spending to afford medications to control blood glucose in elderly people with diabetes is one of the chief challenges to medication adherence. In an effort to reduce the financial burden of prescription drugs on the elderly, Medicare Part D was created and went into effect in 2006. However, one in four Medicare Part D beneficiaries experiences a coverage gap where they must pay 100% of total prescription drug costs. Approximately a quarter of those individuals discontinued their drugs when they reached the coverage gap. Currently, with the Patient Protection and Affordable Care Act of 2010, the coverage gap will be eliminated by 2020. This dissertation examines which factors affect medication adherence in adults with diabetes (Aim 1) and whether the recent policy effort of Medicare Part D effectively decreases the financial burden of prescription drugs on the elderly with diabetes (Aim 2). Chapter One provides the significance of out-of-pocket costs for medication adherence in elderly individuals with diabetes as well as background information on Medicare Part D and its coverage gap. Chapter Two reviews the literature to synthesize current knowledge that has informed the methodology for this dissertation. This chapter also identifies gaps in this body of work. These include comparing advantages and disadvantages of medication adherence as measured by patient self-report, pharmacy refills, and electronic lids on medication containers. Two systematic reviews are conducted in order to determine the most commonly used measurements and definitions of medication adherence measured by pharmacy claims data, and to identify barriers to and facilitators of medication adherence among adult diabetes patients. Lastly, previous studies that focused on the impact of Medicare Part D and its coverage gap on out-of-pocket pharmacy costs and medication adherence are reviewed. Chapter Three describes the methodologies to address Aims 1 and 2 including the study design, information on the data source, sample descriptions, a conceptual framework, study variables and analytic plans. Chapter Four presents key findings of this study, and Chapter Five concludes with summaries and interpretations of the findings, implications for practice and policy, and recommendations for future research.

The increasing adoption of electronic health records (EHRs) has led to an unprecedented amount of patient health information stored in an electronic format. The ability to comb through this information is imperative, both for patient care and computational modeling. Creating a system to minimize unnecessary EHR data, automatically distill longitudinal patient information, and highlight salient parts of a patient’s record is currently an unmet need. However, summarization of EHR data is not a trivial task, as there exist many challenges with reasoning over this data. EHR data elements are most often obtained at irregular intervals as patients are more likely to receive medical care when they are ill, than when they are healthy. The presence of narrative documentation adds another layer of complexity as the notes are riddled with over-sampled text, often caused by the frequent copy-and-pasting during the documentation process. This dissertation synthesizes a set of challenges for automated EHR summarization identified in the literature and presents an array of methods for dealing with some of these challenges. We used hybrid data-driven and knowledge-based approaches to examine abundant redundancy in clinical narrative text, a data-driven approach to identify and mitigate biases in laboratory testing patterns with implications for using clinical data for research, and a probabilistic modeling approach to automatically summarize patient records and learn computational models of disease with heterogeneous data types. The dissertation also demonstrates two applications of the developed methods to important clinical questions: the questions of laboratory test overutilization and cohort selection from EHR data.