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Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012
Description
Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well.
ContributorsVankipuram, Mithra (Author) / Greenes, Robert A (Thesis advisor) / Patel, Vimla L. (Thesis advisor) / Petitti, Diana B. (Committee member) / Dinu, Valentin (Committee member) / Smith, Marshall L. (Committee member) / Arizona State University (Publisher)
Created2012
Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
Description
I conducted a qualitative, comparative study on the nursing education systems in the United Kingdom and the United States, focusing on two universities—Arizona State University in Phoenix, Arizona and Leeds Beckett University in Leeds, England. The goals of my thesis included comparing the educational, economic, and cultural aspects of the countries and how those aspects impact nursing students on both sides of the pond. The educational and economic aspects were compared by utilizing existing literature and open data sources such as the university websites and publications from comparative education journals, while the cultural differences were evaluated by conducting short, one-on-one interviews with students enrolled in the Adult Health courses at both universities. The findings from the interviews were transcribed and coded, and findings from the sites were compared. While there is an extensive amount of research published regarding comparative education, there has not been much published comparing these developed countries. While there is a significant difference in the structure and cost of the nursing programs, there are more similarities than differences in culture between nursing students interviewed in the US and those interviewed in the UK.
ContributorsTahiliani, Shreja (Author) / Hagler, Debra (Thesis director) / Allen, Angela (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The goal of this creative project is to explain the different roles of advanced practice nursing as well as the role of a registered nurse. Advanced practice nursing roles include Certified Nurse Practitioner, Certified Registered Nurse Anesthetist, Certified Clinical Nurse Specialist, and Certified Nurse Midwife. The role of the registered nurse is included in this website because this role is the foundation for becoming an advanced practice nurse and is an equally important role. The target audience for the website is potential nursing students, current nursing students, and licensed nurses who desire to advance their career and are looking for more information about each role. This comprehensive website includes the scope of practice, salary, educational programs, and an interview with a nurse in each role. The description of each advanced practice role includes audio and visual aids to appeal to different types of learners. In depth education regarding advanced practice nursing roles will make current and future nurses more aware of the endless possibilities of a career in nursing. Nurses provide education to patients every day, but there is rarely adequate education provided to nurses regarding their profession or professional advancement opportunities. Nursing is a patient-focused career and sometimes nurses forget to focus on their own personal growth while caring for others. This one-stop website promotes nurse to nurse education by thoroughly explaining each advanced practice role. All of the information in this website is publically available through the internet and this website is meant solely for educational purposes.
ContributorsThompson, Rachel (Co-author) / Banchik, Jennifer (Co-author) / Peterson, Katherine (Thesis director) / Kriz, Lindsey (Committee member) / Spahr, Nancy (Committee member) / School of Community Resources and Development (Contributor) / School of Social Transformation (Contributor) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Colorectal cancer (CRC) is the third most prevalent form of cancer in both genders and second highest cause of cancer-related death in the United States. Despite the availability of preventative CRC screening, Latinos as a group are of particular concern for CRC as they tend to have a lower screening rate, contributing to the possibility of late-stage diagnosis or even death. However, little is known about the perceptions of CRC screening and factors which contribute to beliefs about CRC in Latinos. Most studies are quantitative and rarely include a qualitative approach focusing on cultural aspects and communication with physicians. The purpose of this study was to explore participants' perceived facilitators and barriers to CRC screening, as well as perspectives on physician recommendation and fatalism, using a qualitative approach. A convenience and snowball sampling were used to collect the data. Eight English-speaking Latino individuals (M age=56 years; 75% female) in the Phoenix, Arizona area were invited to 60-90 minute in-depth interviews on perceptions of the colorectal cancer screening process. Ten major themes emerged from the interviews: (1) lacking awareness and knowledge of CRC screening, (2) attitude toward CRC and screening, (3) availability of preventive care, (4) physician trust, (5) fear, (6) desire for increased information, (7) personal learning, (8) lifestyle factors, (9) cultural impact, and (10) willingness to change lifestyle. Results indicated varying levels of perceived knowledge of colorectal cancer, little perceived risk of diagnosis, desire for more information, and a high level of physician trust. Implications for nursing included increased need for CRC screening educational resources, as well as further investigation of the influence of fatalistic belief in CRC screening compliance for the Latino population.
ContributorsMagdaleno, Claire Rose (Author) / Kim, Sunny (Thesis director) / McNulty, Julie (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
This past summer, I met a young lady named Ashley (name has been changed) who has been diagnosed with chronic Lyme disease. Upon researching this condition in greater detail, I learned that many medical providers who base their practice on the best evidence do not support treating patients for a chronic Lyme infection, the existence of which has not been substantially supported with research. I inquired about the process that led her to seek treatment for chronic Lyme disease at Jemsek Specialty Clinic. I learned that after many inaccurate diagnoses and years of unhelpful treatments, Ashley finally rejected the help offered by traditional medical doctors because she felt they were uncaring and inattentive, and went somewhere she felt heard. What she deserved, however, was both care that was based in scientific research and care that felt compassionate, as has been promoted by the nursing field. Despite the lack of a confirmed medical diagnosis, Ashley's day to day symptoms and struggles could be addressed with nursing care. I then constructed a nursing care plan to be implemented by Ashley's family and friends to help her feel her best and live a fulfilling life despite chronic disease. Patients should not have to choose between a healthcare provider who utilizes the strongest scientific evidence and one they feel understands them, though many do. Nursing can unite these mindsets by alleviating the daily challenges patients face. Please see the website http://careplanforashley.blogspot.com
ContributorsKnochel, Amanda Marie (Author) / Panchmatia, Bella (Thesis director) / Mishark, Kenneth (Committee member) / Barrett, The Honors College (Contributor) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor)
Created2014-05