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- Creators: Arizona State University
Description
Overcrowding of Emergency Departments (EDs) put the safety of patients at risk. Decision makers implement Ambulance Diversion (AD) as a way to relieve congestion and ensure timely treatment delivery. However, ineffective design of AD policies reduces the accessibility to emergency care and adverse events may arise. The objective of this dissertation is to propose methods to design and analyze effective AD policies that consider performance measures that are related to patient safety. First, a simulation-based methodology is proposed to evaluate the mean performance and variability of single-factor AD policies in a single hospital environment considering the trade-off between average waiting time and percentage of time spent on diversion. Regression equations are proposed to obtain parameters of AD policies that yield desired performance level. The results suggest that policies based on the total number of patients waiting are more consistent and provide a high precision in predicting policy performance. Then, a Markov Decision Process model is proposed to obtain the optimal AD policy assuming that information to start treatment in a neighboring hospital is available. The model is designed to minimize the average tardiness per patient in the long run. Tardiness is defined as the time that patients have to wait beyond a safety time threshold to start receiving treatment. Theoretical and computational analyses show that there exists an optimal policy that is of threshold type, and diversion can be a good alternative to decrease tardiness when ambulance patients cause excessive congestion in the ED. Furthermore, implementation of AD policies in a simulation model that accounts for several relaxations of the assumptions suggests that the model provides consistent policies under multiple scenarios. Finally, a genetic algorithm is combined with simulation to design effective policies for multiple hospitals simultaneously. The model has the objective of minimizing the time that patients spend in non-value added activities, including transportation, waiting and boarding in the ED. Moreover, the AD policies are combined with simple ambulance destination policies to create ambulance flow control mechanisms. Results show that effective ambulance management can significantly reduce the time that patients have to wait to receive appropriate level of care.
ContributorsRamirez Nafarrate, Adrian (Author) / Fowler, John W. (Thesis advisor) / Wu, Teresa (Thesis advisor) / Gel, Esma S. (Committee member) / Limon, Jorge (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the United States, under the provisions set forth by a policy known as community benefit, nonprofit hospitals receive special tax exemptions from government in exchange for providing a wide range of health care services to the communities in which they are located. In recent years, nonprofit hospitals have claimed billions of dollars as community benefit justifying their tax-exempt status. However, growing criticism by numerous stakeholders has questioned the extent to which the level of community benefit claimed by nonprofit hospitals reflects the exemptions they receive. In addition, a dearth of research exists to understand the relationship between community benefit claims and the impact they have on improving the health of communities. In an effort to better understand the relationship between community benefit claims, tax status, and community health outcomes this study examines the community benefit policies of a nonprofit healthcare system representing hospitals in California, Nevada, and Arizona. It does so by reviewing materials produced by the system, her hospitals, vested stakeholders, and government that have shaped the development, implementation, and assessment of community benefit policy processes. Findings of the study suggest that the majority of nonprofit hospital community benefit claims are consumed by shortfalls reported between costs associated with providing care to Medicare and Medicaid patients and the compensation nonprofit hospitals receive from government. Results of the study also demonstrate that community benefit policies do positively impact the health of communities. However, future community benefit policies need to be refined to include measures that capture the magnitude of community health improvement if the relationship between policy and health outcomes is to be fully realized.
ContributorsMartz, Mark Patrick (Author) / Cayer, Joseph (Thesis advisor) / Glaser, Mark (Committee member) / Corley, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2013
Description
Critical infrastructures in healthcare, power systems, and web services, incorporate cyber-physical systems (CPSes), where the software controlled computing systems interact with the physical environment through actuation and monitoring. Ensuring software safety in CPSes, to avoid hazards to property and human life as a result of un-controlled interactions, is essential and challenging. The principal hurdle in this regard is the characterization of the context driven interactions between software and the physical environment (cyber-physical interactions), which introduce multi-dimensional dynamics in space and time, complex non-linearities, and non-trivial aggregation of interaction in case of networked operations. Traditionally, CPS software is tested for safety either through experimental trials, which can be expensive, incomprehensive, and hazardous, or through static analysis of code, which ignore the cyber-physical interactions. This thesis considers model based engineering, a paradigm widely used in different disciplines of engineering, for safety verification of CPS software and contributes to three fundamental phases: a) modeling, building abstractions or models that characterize cyberphysical interactions in a mathematical framework, b) analysis, reasoning about safety based on properties of the model, and c) synthesis, implementing models on standard testbeds for performing preliminary experimental trials. In this regard, CPS modeling techniques are proposed that can accurately capture the context driven spatio-temporal aggregate cyber-physical interactions. Different levels of abstractions are considered, which result in high level architectural models, or more detailed formal behavioral models of CPSes. The outcomes include, a well defined architectural specification framework called CPS-DAS and a novel spatio-temporal formal model called Spatio-Temporal Hybrid Automata (STHA) for CPSes. Model analysis techniques are proposed for the CPS models, which can simulate the effects of dynamic context changes on non-linear spatio-temporal cyberphysical interactions, and characterize aggregate effects. The outcomes include tractable algorithms for simulation analysis and for theoretically proving safety properties of CPS software. Lastly a software synthesis technique is proposed that can automatically convert high level architectural models of CPSes in the healthcare domain into implementations in high level programming languages. The outcome is a tool called Health-Dev that can synthesize software implementations of CPS models in healthcare for experimental verification of safety properties.
ContributorsBanerjee, Ayan (Author) / Gupta, Sandeep K.S. (Thesis advisor) / Poovendran, Radha (Committee member) / Fainekos, Georgios (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2012
Description
Parkinson's disease, the most prevalent movement disorder of the central nervous system, is a chronic condition that affects more than 1000,000 U.S. residents and about 3% of the population over the age of 65. The characteristic symptoms include tremors, bradykinesia, rigidity and impaired postural stability. Current therapy based on augmentation or replacement of dopamine is designed to improve patients' motor performance but often leads to levodopa-induced complications, such as dyskinesia and motor fluctuation. With the disease progress, clinicians must closely monitor patients' progress in order to identify any complications or decline in motor function as soon as possible in PD management. Unfortunately, current clinical assessment for Parkinson's is subjective and mostly influenced by brief observations during patient visits. Thus improvement or decline in patients' motor function in between visits is extremely difficult to assess. This may hamper clinicians while making informed decisions about the course of therapy for Parkinson's patients and could negatively impact clinical care. In this study we explored new approaches for PD assessment that aim to provide home-based PD assessment and monitoring. By extending the disease assessment to home, the healthcare burden on patients and their family can be reduced, and the disease progress can be more closely monitored by physicians. To achieve these aims, two novel approaches have been designed, developed and validated. The first approach is a questionnaire based self-evaluation metric, which estimate the PD severity through using self-evaluation score on pre-designed questions. Based on the results of the first approach, a smart phone based approach was invented. The approach takes advantage of the mobile computing technology and clinical decision support approach to evaluate the motor performance of patient daily activity and provide the longitudinal disease assessment and monitoring. Both approaches have been validated on recruited PD patients at the movement disorder program of Barrow Neurological Clinic (BNC) at St Joseph's Hospital and Medical Center. The results of validation tests showed favorable accuracy on detecting and assessing critical symptoms of PD, and shed light on promising future of implementing mobile platform based PD evaluation and monitoring tools to facilitate PD management.
ContributorsPan, Di (Author) / Petitti, Diana (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Dhall, Rohit (Committee member) / Arizona State University (Publisher)
Created2013
Description
Nurses are using health information technology during patient care activities in acute care at an unprecedented rate. Previous literature has presented nurses' response to technology obstacles as a work-around, a negative behavior. Using a narrative inquiry in one hospital unit, this dissertation examines nurses' interactions when they encounter technology obstacles from a complexity science perspective. In this alternative view, outcomes are understood to emerge from tensions in the environment through nonlinear and self-organizing interactions. Innovation is a process of changing interaction patterns to bring about transformation in practices or products that have the potential to contribute to social wellbeing, such as better care. Innovation was found when nurses responded to health information technology obstacles with self-organizing interactions, sensitivity to initial conditions, multidirectionality, and their actions were influenced by a plethora of sets of rules. Nurses self-organized with co-workers to find a better way to deliver care to patients when using technology. Nurses rarely told others outside their work-group of the obstacles that occurred in their everyday interactions, including hospital-wide process improvement committees. Managers were infrequently consulted when nurses encountered technology obstacles, and often nurses did not find solutions to their obstacles when they contacted the Help Desk. Opportunities exist to facilitate interactions among nurses and other members of the organization to realize better use of health information technology that improves quality and safety while decreasing cost in the patient experience.
ContributorsLalley, Catherine (Author) / Malloch, Kathy (Thesis advisor) / Fleury, Julie (Committee member) / Danzig, Arnold (Committee member) / Arizona State University (Publisher)
Created2013
Description
Health and healing in the United States is in a moment of deep and broad transformation. Underpinning this transformation is a shift in focus from practitioner- and system-centric perspectives to patient and family expectations and their accompanying localized narratives. Situated within this transformation are patients and families of all kinds. This shift's interpretation lies in the converging and diverging trails of biomedicine, a patient-centric perspective of consensus between practitioner and patient, and postmodern philosophy, a break from prevailing norms and systems. Lending context is the dynamic interplay between increasing ethnic/cultural diversity, acculturation/biculturalism, and medical pluralism. Diverse populations continue to navigate multiple health and healing paradigms, engage in the process of their integration, and use health and healing practices that run corollary to them. The way this experience is viewed, whether biomedically or philosophically, has implications for the future of healthcare. Over this fluid interpenetration, with its vivid nuance, loom widespread health disparities. The adverse effects of static, fragmented healthcare systems unable to identify and answer diverse populations' emergent needs are acutely felt by these individuals. Eradication of health disparities is born from insight into how these populations experience health and healing. The resulting strategy must be one that simultaneously addresses the complex intricacies of patient-centered care, permits emergence of more localized narratives, and eschews systems that are no longer effective. It is the movement of caregivers across multiple health and healing sources, managing care for loved ones, that provides this insight and in which this project is keenly interested. Uncovering the emergent patterns of caregivers' management of these sources reveals a rich and nuanced spectrum of realities. These realities are replete with opportunities to re-frame health and healing in ways that better reflect what these diverse populations of caregivers and care recipients need. Engaging female Mexican American caregivers, a population whose experience is well-suited to aid in this re-frame, this project begins to provide that insight. Informed by a parent framework of Complexity Science, and balanced between biomedical and postmodern perspectives, this constructivist grounded theory secondary analysis charts these caregivers' processes and offers provocative findings and recommendations for understanding their experiences.
ContributorsKrahe, Jennifer Anne Eve (Author) / Lamb, Gerri (Thesis advisor) / Evans, Bronwynne (Committee member) / Larkey, Linda (Committee member) / Arizona State University (Publisher)
Created2013
Description
Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. However, this process still requires that seizures are visually detected and marked by experienced and trained electroencephalographers. The motivation for the development of an automated seizure detection algorithm in this research was to assist physicians in such a laborious, time consuming and expensive task. Seizures in the EEG vary in duration (seconds to minutes), morphology and severity (clinical to subclinical, occurrence rate) within the same patient and across patients. The task of seizure detection is also made difficult due to the presence of movement and other recording artifacts. An early approach towards the development of automated seizure detection algorithms utilizing both EEG changes and clinical manifestations resulted to a sensitivity of 70-80% and 1 false detection per hour. Approaches based on artificial neural networks have improved the detection performance at the cost of algorithm's training. Measures of nonlinear dynamics, such as Lyapunov exponents, have been applied successfully to seizure prediction. Within the framework of this MS research, a seizure detection algorithm based on measures of linear and nonlinear dynamics, i.e., the adaptive short-term maximum Lyapunov exponent (ASTLmax) and the adaptive Teager energy (ATE) was developed and tested. The algorithm was tested on long-term (0.5-11.7 days) continuous EEG recordings from five patients (3 with intracranial and 2 with scalp EEG) and a total of 56 seizures, producing a mean sensitivity of 93% and mean specificity of 0.048 false positives per hour. The developed seizure detection algorithm is data-adaptive, training-free and patient-independent. It is expected that this algorithm will assist physicians in reducing the time spent on detecting seizures, lead to faster and more accurate diagnosis, better evaluation of treatment, and possibly to better treatments if it is incorporated on-line and real-time with advanced neuromodulation therapies for epilepsy.
ContributorsVenkataraman, Vinay (Author) / Jassemidis, Leonidas (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2012
Description
"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, seating and elements of positive distraction in the pain center waiting room relate to the patients experience of pain and distress? This study utilized a mixed-method approach. A purposive sample of 39 individuals participated in the study. The study employed the Positive and Negative Affect Schedule (PANAS), the Lewandowski Pain Scale (LPS) and a researcher developed Spatial Perception Instrument (SPI) rating the appearance and comfort of a pain center waiting room in a large metropolitan area. Results indicated that there were no significant correlations between pain, distress and the waiting room environment. It is intended that this study will provide a framework for future research in the area of chronic pain and distress in order to advance the understanding of research in the waiting area environment and the effect it may have on the patient.
ContributorsDraper, Heather (Author) / Bender, Diane (Thesis advisor) / Shraiky, James (Committee member) / Lamb, Gerri (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
ABSTRACT The massive number of baby boomers approaching retirement age has been termed the `gray tsunami.' As America's gray tsunami approaches, healthcare workers and social workers will become overwhelmed with requests for services and supports (St. Luke's Health Initiative, 2001; Bekemeier, 2009). This impact can be ameliorated by assisting aging individuals in maintaining or in some cases regaining independence. Individuals who live in assisted living facilities (AFLs) come from diverse backgrounds. Many of these individuals have lived in paternalistic environments such as prisons and mental health institutions. As a consequence of these disempowering conditions, residents of ALFs may experience increased depression, decreased self-esteem, and decreased locus of control (R. Hess, personal communication, September 30, 2010). These disabling conditions can severely limit residents' choice-making opportunities and control over their own lives. If programs can be created to provide empowering experiences and to teach self-advocacy skills, I hypothesize that residents will report an improved quality of life and display fewer depressive symptoms, increased self-esteem, and increased locus of control. Helping these individuals to maintain or regain independence will not only reduce the workload for care workers, it will enhance the lives of residents. The only hypothesis that was supported by the study was an improvement in residents' quality of life, and that hypothesis was only partially supported. Two of the five domains in the Residents' Quality of life questionnaire indicated an increase in quality of life. ii The Activities subscale of the Ferrans & Powers Quality also indicated that there was an increase in quality of life.
ContributorsHedgpeth, Jay (Author) / Napoli, Maria (Thesis advisor) / Gerdes, Karen (Committee member) / Bonifas, Robin (Committee member) / Arizona State University (Publisher)
Created2012