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- Creators: Department of Psychology
Description
For more than twenty years, clinical researchers have been publishing data regarding incidence and risk of adverse events (AEs) incurred during hospitalizations. Hospitals have standard operating policies and procedures (SOPP) to protect patients from AE. The AE specifics (rates, SOPP failures, timing and risk factors) during heart failure (HF) hospitalizations are unknown. There were 1,722 patients discharged with a primary diagnosis of HF from an academic hospital between January 2005 and December 2007. Three hundred eighty-one patients experienced 566 AEs, classified into four categories: medication (43.9%), infection (18.9%), patient care (26.3%), or procedural (10.9%). Three distinct analyses were performed: 1) patient's perspective of SOPP reliability including cumulative distribution and hazard functions of time to AEs; 2) Cox proportional hazards model to determine independent patient-specific risk factors for AEs; and 3) hospital administration's perspective of SOPP reliability through three years of the study including cumulative distribution and hazard functions of time between AEs and moving range statistical process control (SPC) charts for days between failures of each type. This is the first study, to our knowledge, to consider reliability of SOPP from both the patient's and hospital administration's perspective. AE rates in hospitalized patients are similar to other recently published reports and did not improve during the study period. Operations research methodologies will be necessary to improve reliability of care delivered to hospitalized patients.
ContributorsHuddleston, Jeanne (Author) / Fowler, John (Thesis advisor) / Montgomery, Douglas C. (Thesis advisor) / Gel, Esma (Committee member) / Shunk, Dan (Committee member) / Arizona State University (Publisher)
Created2012
Description
Mathematical modeling and decision-making within the healthcare industry have given means to quantitatively evaluate the impact of decisions into diagnosis, screening, and treatment of diseases. In this work, we look into a specific, yet very important disease, the Alzheimer. In the United States, Alzheimer’s Disease (AD) is the 6th leading cause of death. Diagnosis of AD cannot be confidently confirmed until after death. This has prompted the importance of early diagnosis of AD, based upon symptoms of cognitive decline. A symptom of early cognitive decline and indicator of AD is Mild Cognitive Impairment (MCI). In addition to this qualitative test, Biomarker tests have been proposed in the medical field including p-Tau, FDG-PET, and hippocampal. These tests can be administered to patients as early detectors of AD thus improving patients’ life quality and potentially reducing the costs of the health structure. Preliminary work has been conducted in the development of a Sequential Tree Based Classifier (STC), which helps medical providers predict if a patient will contract AD or not, by sequentially testing these biomarker tests. The STC model, however, has its limitations and the need for a more complex, robust model is needed. In fact, STC assumes a general linear model as the status of the patient based upon the tests results. We take a simulation perspective and try to define a more complex model that represents the patient evolution in time.
Specifically, this thesis focuses on the formulation of a Markov Chain model that is complex and robust. This Markov Chain model emulates the evolution of MCI patients based upon doctor visits and the sequential administration of biomarker tests. Data provided to create this Markov Chain model were collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The data lacked detailed information of the sequential administration of the biomarker tests and therefore, different analytical approaches were tried and conducted in order to calibrate the model. The resulting Markov Chain model provided the capability to conduct experiments regarding different parameters of the Markov Chain and yielded different results of patients that contracted AD and those that did not, leading to important insights into effect of thresholds and sequence on patient prediction capability as well as health costs reduction.
The data in this thesis was provided from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). ADNI investigators did not contribute to any analysis or writing of this thesis. A list of the ADNI investigators can be found at: http://adni.loni.usc.edu/about/governance/principal-investigators/ .
Specifically, this thesis focuses on the formulation of a Markov Chain model that is complex and robust. This Markov Chain model emulates the evolution of MCI patients based upon doctor visits and the sequential administration of biomarker tests. Data provided to create this Markov Chain model were collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The data lacked detailed information of the sequential administration of the biomarker tests and therefore, different analytical approaches were tried and conducted in order to calibrate the model. The resulting Markov Chain model provided the capability to conduct experiments regarding different parameters of the Markov Chain and yielded different results of patients that contracted AD and those that did not, leading to important insights into effect of thresholds and sequence on patient prediction capability as well as health costs reduction.
The data in this thesis was provided from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). ADNI investigators did not contribute to any analysis or writing of this thesis. A list of the ADNI investigators can be found at: http://adni.loni.usc.edu/about/governance/principal-investigators/ .
ContributorsCamarena, Raquel (Author) / Pedrielli, Giulia (Thesis advisor) / Li, Jing (Thesis advisor) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2018
Description
Influenza is a deadly disease for which effective vaccines are sorely lacking. This is largely due to the phenomena of antigenic shift and drift in the influenza virus's surface proteins, hemagglutinin (HA) and neuraminidase (NA). The ectodomain of the matrix 2 protein (M2e) of influenza A, however, has demonstrated high levels of conservation. On its own it is poorly immunogenic and offers little protection against influenza infections, but by combining it with a potent adjuvant, this limitation may be overcome. Recombinant immune complexes, or antigens fused to antibodies that have been engineered to form incredibly immunogenic complexes with one another, were previously shown to be useful, immunogenic platforms for the presentation of various antigens and could provide the boost in immunogenicity that M2e needs to become a powerful universal influenza A vaccine. In this thesis, genetic constructs containing geminiviral replication proteins and coding for a consensus sequence of dimeric M2e fused to antibodies featuring complimentary epitopes and epitope tags were generated and used to transform Agrobacterium tumefaciens. The transformed bacteria was then used to cause Nicotiana benthamiana to transiently express M2e-RICs at very high levels, with enough RICs being gathered to evaluate their potency in future mouse trials. Future directions and areas for further research are discussed.
ContributorsFavre, Brandon Chetan (Author) / Mason, Hugh (Thesis director) / Mor, Tsafrir (Committee member) / Diamos, Andrew (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation study. This research seeks to determine the acquisition processes that contribute significantly to total simulated program time in the acquisition system for all programs reaching Milestone C. Specifically, this research examines the effect of increased scope management, technology maturity, and decreased variation and mean process times in post-Design Readiness Review contractor activities by performing additional simulation analyses. Potential policies are formulated from the results to further improve program acquisition completion time.
ContributorsWorger, Danielle Marie (Author) / Wu, Teresa (Thesis director) / Shunk, Dan (Committee member) / Wirthlin, J. Robert (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
Telemedicine is a multipurpose tool that allows medical professionals to use technology as a means to evaluate, diagnose, and treat patients remotely. This paper focuses on the challenges that developing telemedicine programs face, specifically discussing target population, user experience, and physician adoption. Various users of telemedicine share their experiences overcoming such challenges with the greater goal of this paper being to facilitate the growth of telemedicine programs.
ContributorsPalakodaty, Shivani Venkatasri (Author) / Liss, Julie (Thesis director) / Berisha, Visar (Committee member) / School of International Letters and Cultures (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
While the transition from sectarian to allopathic medicine was almost entirely beneficial due to our perceived value in the type of evidence and transparency that science provides, key values within sectarian practice were lost in this transition. Attention to these values helps us better understand the role and treatment of patients in modern medicine. Modern scientific physicians have proven the inefficacy of sectarian treatments by scientific practices, but the efficacy of exact sectarian remedies may not have bearing on the importance of sectarian values. These values were: medical simplicity, harmlessness in treatment, independence from physicians and accessibility of treatment. A more in-depth analysis of sectarian values allows us to understand that while the values of allopathic medicine have become ubiquitous, it has not always been that way. It is time to consider the validity in the sectarian values we have abandoned; this analysis was one of many on medicine's imminent developmental horizon. This realization allows us to call into question the importance of our current practicing values, and the necessity that they continue to stand alone.
ContributorsAyala, Erik Richard (Author) / Brian, Jennifer (Thesis director) / Ross, Christian (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
From 2019, a severe acute respiratory coronavirus 2, SARS-CoV-2, began to be a global pandemic. Many high income countries developed different strategies in response. This analysis intends to highlight how the COVID-19 became a global pandemic and the strategies that account for successes and failures. In identifying key policy differences, the high income countries of the United States, New Zealand and France were examined. The analysis found that New Zealand had proactive elimination strategies that proved highly effective, whereas the United States and France both struggled with mitigation factors that resulted in disproportionately higher confirmed cases and mortality rates. The analysis highlights how the airborne virus became a pandemic and then followed public policies’ effectiveness in terms of existing political institutions,and then their ability to be successful in preventing the spread of the virus.
ContributorsNavas, Natalia (Author) / Wilson, Natalia (Thesis director) / Niebuhr, Robert (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / School of Politics and Global Studies (Contributor)
Created2022-05
Description
Nonalcoholic Steatohepatitis (NASH) is a severe form of Nonalcoholic fatty liverdisease, that is caused due to excessive calorie intake, sedentary lifestyle and in the
absence of severe alcohol consumption. It is widely prevalent in the United States
and in many other developed countries, affecting up to 25 percent of the population.
Due to being asymptotic, it usually goes unnoticed and may lead to liver failure if
not treated at the right time.
Currently, liver biopsy is the gold standard to diagnose NASH, but being an
invasive procedure, it comes with it's own complications along with the inconvenience
of sampling repeated measurements over a period of time. Hence, noninvasive
procedures to assess NASH are urgently required. Magnetic Resonance Elastography
(MRE) based Shear Stiffness and Loss Modulus along with Magnetic Resonance
Imaging based proton density fat fraction have been successfully combined to predict
NASH stages However, their role in the prediction of disease progression still remains
to be investigated.
This thesis thus looks into combining features from serial MRE observations to
develop statistical models to predict NASH progression. It utilizes data from an experiment
conducted on male mice to develop progressive and regressive NASH and
trains ordinal models, ordered probit regression and ordinal forest on labels generated
from a logistic regression model. The models are assessed on histological data collected
at the end point of the experiment. The models developed provide a framework
to utilize a non-invasive tool to predict NASH disease progression.
ContributorsDeshpande, Eeshan (Author) / Ju, Feng (Thesis advisor) / Wu, Teresa (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2021
Description
Homeless populations are often disproportionately impacted by several diseases due to factors such as overcrowding, unsanitary conditions, lack of access to healthcare and most importantly lack of education. The purpose of this project was to decrease a part of this health gap by spreading awareness of certain illnesses impacting Arizona’s homeless population and to increase the use plausible prevention methods. This was done through the creation of three simplified brochures that contained information regarding influenza, hepatitis, and schizophrenia. Two surveys were distributed to a local homeless population; the first survey was given prior to handing out the brochures and the second survey was given a week later after the participants had some time to read the information from the brochures. The data from the surveys supported the goal of the project by showing an increase in overall awareness of the diseases as well as an increase in behavioral changes that would lead to the increase of plausible prevention methods.
ContributorsBanuelos, Jason (Author) / Quaranta, Kimberly (Thesis director) / Szeli, Eva (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05