Medicine and Health Sciences Commons^™

Mathematical Modeling For Dental Decay Prevention In Children And Adolescents, Mahdiyeh Soltaninejad

Dissertations

The high prevalence of dental caries among children and adolescents, especially those from lower socio-economic backgrounds, is a significant nationwide health concern. Early prevention, such as dental sealants and fluoride varnish (FV), is essential, but access to this care remains limited and disparate. In this research, a national dataset is utilized to assess sealants' reach and effectiveness in preventing tooth decay, particularly focusing on 2nd molars that emerge during early adolescence, a current gap in the knowledge base. FV is recommended to be delivered during medical well-child visits to children who are not seeing a dentist. Challenges and facilitators in …

Mining High Impact Combinations Of Conditions From The Medical Expenditure Panel Survey, Arjun Mohan

Masters Theses

The condition of multimorbidity — the presence of two or more medical conditions in an individual — is a growing phenomenon worldwide. In the United States, multimorbid patients represent more than a third of the population and the trend is steadily increasing in an already aging population. There is thus a pressing need to understand the patterns in which multimorbidity occurs, and to better understand the nature of the care that is required to be provided to such patients.

In this thesis, we use data from the Medical Expenditure Panel Survey (MEPS) from the years 2011 to 2015 to identify …

Detecting Pathobiomes Using Machine Learning, Valerie Jackson, Valerie Jackson

Industrial Engineering Undergraduate Honors Theses

Machine learning is a field with high growth potential due to the overall continuous progressions, developments, advancements, and improvements caused by the way it is used to help interpret and use large amounts of data [1]. One type of data that can be collected and analyzed by these machine learning models is data that is associated with DNA and information that the DNA gives. The research will be focusing specifically on using machine learning technology to detect pathobiomes indicative of salmonella pork. The pathobiome associated with salmonella is very similar to others, and this causes a problem for classification/detection with …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Digital Patient Engagement At A Perioperative Surgical Home Implemented Community Hospital, Srinivasan Sridhar, Amy Mount Hunter, Bernadette Mccrory

Patient Experience Journal

Patients in rural areas typically require more perioperative ‘optimization’ for surgery. The rural healthcare systems often overwhelmed with coordinating perioperative services and deliver less than optimal surgical outcomes. This is due to limited supporting microsystems and ability to effectively engage and track patients over the 120-day perioperative period to limit post-surgical complications. The study assessed longitudinal patient engagement within a newly established Perioperative Surgical Home (PSH) at a rural community hospital serving 10+ surrounding counties to identify barriers and best practices for engagement. A digital patient engagement platform was implemented and used to assess longitudinal patient outcomes and engagement from …

Introduction To Bioaerosols Assessment And Control, 2nd Edition, Cheri Marcham, John (Jack) Springston

Publications

• Risk Assessment
• Assessment for the Presence of Bioaerosols
• Sampling
• Purpose/ Necessity
• Interpretation Controls
  • Ventilation
  • Other Controls

A Machine Learning Approach For Early Diagnosis Of Transthyretin Amyloid Cardiomyopathy Among Heart Failure Patients, Tanjim Ahmed

Graduate Theses, Dissertations, and Problem Reports

Transthyretin Amyloid Cardiomyopathy (ATTR-CM) is a rare, progressive, and fatal disease. Prevalence of ATTR-CM ranges from 4 to 17 per 100000 cases where the mean survival time is less than 4 years. It has a history of being underdiagnosed and misdiagnosed. The diagnosis delay has a weighted mean of 6.1 years for wild-type ATTR-CM. Low awareness, the necessity of invasive procedures, and lack of treatment are the key reasons for delayed diagnosis. But, with the introduction of non-invasive tests like nuclear scintigraphy with ^99mTC-PYP and the disease modifying drug Tafamidis, the diagnosis delay signifies a missed opportunity to increase …

Models And Algorithms For Trauma Network Design., Sagarkumar Dhirubhai Hirpara

Electronic Theses and Dissertations

Trauma continues to be the leading cause of death and disability in the US for people aged 44 and under, making it a major public health problem. The geographical maldistribution of Trauma Centers (TCs), and the resulting higher access time to the nearest TC, has been shown to impact trauma patient safety and increase disability or mortality. State governments often design a trauma network to provide prompt and definitive care to their citizens. However, this process is mainly manual and experience-based and often leads to a suboptimal network in terms of patient safety and resource utilization. This dissertation fills important …

Eagle Medical Tray Denesting & Debris Removal Process, Nicholas Allen Ungefug, Noah Chavez, Susana Shu-Lin Okhuysen, Michael Augustine Pennington

Industrial and Manufacturing Engineering

Eagle Medical Incorporated is a contract medical device packaging and sterilization company. The company purchases thermoformed medical packaging trays, which maintain the sterility of medical devices, from various manufacturers. To ensure packaging quality and to prevent cleanroom contamination, Eagle Medical inspects and sterilizes each blister tray that they order. This process is an essential non-value-added activity that creates a bottleneck. Cleanroom employees must stop packaging medical devices and attend to the processing of blister trays and packaging solutions. The blister trays arrive at Eagle’s facility in nested stacks. Vibration and movement during shipping further compresses the stacks, which makes separation …

Supplier Performance Scorecard Utilization In The Medical Device Manufacturing Healthcare Supply Chain, Justin Cardisco

Theses and Dissertations

The medical device manufacturing industry has a deficiency in determining how to improve supplier performance for the components and systems they purchase. Many complex medical devices require components from superb suppliers. But how does a medical device manufacturer (MDM) impartially assess supplier performance to know which suppliers to continuing with (or even boost purchase volumes) and which suppliers they should exit? This study describes which supplier-specific metrics are most important to medical device manufacturers (MDMs) so they can utilize this supplier performance scorecard backed by real-world inputs. This research will focus on five categories to measure MDM supplier performance (Quality, …

Examining The Impact Of Design Features Of Electronic Health Records Patient Portals On The Usability And Information Communication For Shared Decision Making, Rong Yin

All Dissertations

The use of the Electronic Health Records (EHR) patient portal has been shown to be effective in generating positive outcomes in patients’ healthcare, improving patient engagement and patient-provider communication. Government legislation also required proof of its meaningful use among patients by healthcare providers. Typical patient portals also include features such as health information and patient education materials. However, little research has examined the specific use of patient portals related to individuals with specific diseases such as inflammatory bowel diseases (IBDs). IBDs are life-long, not curable, chronic diseases that can impact the whole population. Individuals with IBDs may have higher needs …

Resident Doctor Duty Shift Scheduling In Tarragona, Spain, Anna Daniel Fuentes

Theses and Dissertations

The goal of this thesis is to create a computer algorithm to schedule family care resident doctors’ duty shifts in Tarragona, Spain. The algorithm considers European Working Time Directive regulations which limit the number of hours any worker can work in a year. Furthermore, each health center has different work time and staffing requirements, and the medical training program requirements change based on a resident’s level of experience also known as rank of residency. Fair scheduling is essential to healthcare workers’ rights to have time to recover between shifts while satisfying all the training requirements and regulations. Integer programming is …

Investigations Of External Resources And The Impact Of Imaging On Patient Flow In The Emergency Department, Marisa Shehan

All Theses

The problems associated with Emergency Department (ED) crowding are numerous, varied, and complex. Though overcrowded Emergency Departments are frequently attributed to overcrowded hospitals, crowding is also impacted by bottlenecks in patient flow. While discrete-event simulation (DES) is commonly used to model ED flow, external resources are typically excluded from these models due to their complexity and the limited amount of known information for these processes. Instead, external resources such as consults, labs, and imaging are modeled using estimation and/or educated guesswork. In this study, the impact of imaging on patient flow was assessed through data analysis of specific imaging factors, …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

Inpatient Discharge-By-Noon: Are Fewer Better Than All?, Nicholas Ballester, Pratik J. Parikh, Kara Combs, Jordan S. Peck

Journal of Maine Medical Center

Introduction: To address boarding in hospital emergency departments, discharge-by-noon could free up inpatient beds earlier in the day. However, discharging all patients by noon can heavily burden inpatient units and may not be feasible. In this study, we determine the number of discharges after which the benefits of an additional discharge-by-noon diminish.

Methods: We conducted a simulation analysis to quantify how occupancy rate, mean daily number of discharges, and peak discharge time impact upstream boarding time in an inpatient neurology unit at Maine Medical Center. Using a day-of-discharge simulation model with one year of retrospective data, we assessed configurations approximating …

Assessing Patient Safety Culture In United States' Hospitals, Abdulmajeed Azyabi

Electronic Theses and Dissertations, 2020-

Patient safety is founded on continuous learning because there is an urgent need to report and learn from errors, accidents, near misses, and adverse events. The traditional approach to patient safety, based on forming mortality committees and investigating accidents, will no longer be effective. Frameworks, surveys, and assessment tools have been developed over the last decade to assist organizations in measuring and understanding their culture. This a retrospective cross-sectional study included 67,010 respondents from Agency for Health care Research and Quality (AHRQ) 2018 comparative database was analyzed using partial least squares structural equation modeling (PLS-SEM). This research explored whether the …

Developing Artificial Intelligence Tools To Investigate The Phenotypes And Correlates Of Chronic Kidney Disease Patients In West Virginia, Marzieh Amiri Shahbazi

Graduate Theses, Dissertations, and Problem Reports

ABSTRACT

Developing Artificial Intelligence tools to investigate the phenotypes and correlates of Chronic Kidney Disease patients in West Virginia

Marzieh Amiri Shahbazi

Chronic kidney disease (CKD) is responsible for disrupting the lives of 37 million people just in the USA, which is about 1 in 7 adults. CKD results in a gradual loss of kidney function over time. Sometimes CKD doesn’t produce any significant symptoms until it reaches an advanced stage. On the other hand, acute kidney injury (AKI) accounts for a sudden decline in the kidney’s function. As a result, the kidneys fail to filter waste materials from the …

Framework Of Big Data Analytics In Real Time For Healthcare Enterprise Performance Measurements, Ahmed Mohamed

Electronic Theses and Dissertations, 2020-

Healthcare organizations (HCOs) currently have many information records about their patients. Yet, they cannot make proper, faster, and more thoughtful conclusions in many cases with their information. Much of the information is structured data such as medical records, historical data, and non-clinical information. This data is stored in a central repository called the Data Warehouse (DW). DW provides querying and reporting to different groups within the healthcare organization to support their future strategic initiatives. The generated reports create metrics to measure the organization's performance for post-action plans, not for real-time decisions. Additionally, healthcare organizations seek to benefit from the semi-structured …

Drug-Based Therapeutic Strategies For Covid-19-Infected Patients And Their Challenges, Khatereh Zarkesh, Elaheh Entezar-Almahdi, Parisa Ghasemiyeh, Mohsen Akbarian, Marzieh Bahmani, Shahrzad Roudaki, Rahil Fazlinejad, Soliman Mohammadi-Samani, Negar Firouzabadi, Majid Hosseini, Fatemeh Farjadian

Manufacturing & Industrial Engineering Faculty Publications and Presentations

Emerging epidemic-prone diseases have introduced numerous health and economic challenges in recent years. Given current knowledge of COVID-19, herd immunity through vaccines alone is unlikely. In addition, vaccination of the global population is an ongoing challenge. Besides, the questions regarding the prevalence and the timing of immunization are still under investigation. Therefore, medical treatment remains essential in the management of COVID-19. Herein, recent advances from beginning observations of COVID-19 outbreak to an understanding of the essential factors contributing to the spread and transmission of COVID-19 and its treatment are reviewed. Furthermore, an in-depth discussion on the epidemiological aspects, clinical symptoms …

Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj

Dissertations

This dissertation focuses on developing new modeling and solution approaches based on multi-stage stochastic programming and reinforcement learning for tackling biological invasions in forests and human populations. Emerald Ash Borer (EAB) is the nemesis of ash trees. This research introduces a multi-stage stochastic mixed-integer programming model to assist forest agencies in managing emerald ash borer insects throughout the U.S. and maximize the public benets of preserving healthy ash trees. This work is then extended to present the first risk-averse multi-stage stochastic mixed-integer program in the invasive species management literature to account for extreme events. Significant computational achievements are obtained using …

Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin

Dissertations

This dissertation addresses the resource allocation challenges of fighting against infectious disease outbreaks. The goal of this dissertation is to formulate multi-stage stochastic programming and agent-based models to address the limitations of former literature in optimizing resource allocation for preventing and controlling epidemics and pandemics. In the first study, a multi-stage stochastic programming compartmental model is presented to integrate the uncertain disease progression and the logistics of resource allocation to control a highly contagious infectious disease. The proposed multi-stage stochastic program, which involves various disease growth scenarios, optimizes the distribution of treatment centers and resources while minimizing the total expected …

Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter

Graduate Theses and Dissertations

Despite tremendous efforts from governments and humanitarian organizations, millions of children in low- and low-middle-income countries (LICs and LMICs) are still excluded from the benefits of immunization. The vaccine distribution in LICs and LMICs is challenging for several reasons, such as limited cold chain capacities, vaccine wastage, uncertain demand, and lack of access to immunization services. A promising avenue to address these issues is the utilization of drones for vaccine delivery. Drones can fly at high speed on direct paths and could enable on-demand deliveries to mitigate limited storage capacities. Further, their independence of road networks could allow them reaching …

Analysis And Modeling Of Strategic Interactions In Health Systems To Improve Patient Care Access, Jorge A. Acuña Melo

USF Tampa Graduate Theses and Dissertations

Affordable health care access that provides well-coordinated and high-quality services on time is a goal that governments and health organizations strive for. Regrettably, most countries deal with access problems that affect the population's health, such as long waiting lists for specialized medical services, overcrowding of emergency departments, and high health prices. In the present doctoral dissertation, I model and analyze the strategic interactions that inhabit the health system machinery to uncover possible structural problems that led to the aforementioned issues. The study involves operation research, data science, and game theory techniques to address the health care access predicament.

Each research …

Strategies For Achieving The United States Health System's Quadruple Aim By Enhancing The Primary Care Level, Jennifer L. Mendoza-Alonzo

USF Tampa Graduate Theses and Dissertations

The quadruple aim is an approach to optimize the performance of the health system in the United States and consists of four dimensions. The main objective is to improve the population's health, followed by reducing cost, improving patients' experience, and increasing providers' satisfaction. In the present doctoral dissertation, I explore three strategies that help accomplish the quadruple aim at the primary care level. The analysis combines data science and operation research principles to address health system engineering questions.

Each strategy proposed in this document emphasizes one objective more than another; however, all of them in conjunction serve to attain the …

Engineering Controls For Bioaerosols In Non-Industrial/Non-Healthcare Settings, David Krause, Cheri Marcham, Bill Mele, Jack Springston, Rob Strode, Donald Weekes, Neil J. Zimmerman

Publications

The list of disease pathogens that can be transmitted in the air is extensive. This list includes the common cold, SARS, measles, Hansen’s disease (leprosy), polio, influenza, Legionella (Legionnaires’ disease and Pontiac fever), and tuberculosis (TB). TB, SARS-CoV-1, avian influenza, varicella, and now SARS-CoV-2 all have received public notice due not only to their known or assumed ability to be transmitted in the air rapidly from one individual to another, but also for their virulence. Other bioaerosols that can be transmitted through the air include bacteria, fungal spores and fragments, dust mites, and pollen. This document was developed to address …

Regression Analysis Of Pacing When Running A Marathon, Hawkin Starke

Industrial Engineering Undergraduate Honors Theses

Regression analysis can be an effective way of examining performance in the marathon event. By splitting up the race into segments or in runner terminology “splits” the significance of each segment as it relates to the total finish time can be explored. Because the idea of splits is already ingrained into the minds of runners, it makes intuitive sense to use these as the metrics to define a race. Additionally, marathons generally make participant age and gender date publicly available which can then be used to find trends within specific demographics. This tailors trends to smaller groups of people, making …

Physicians And Their Patience: Redefining Healthcare Relationships Through Readability Optimization, Rachel V. Ball

Honors Undergraduate Theses

The present study takes legibility research and extends it to the medical setting. Internal Medicine Physicians from UCF developed six passages of medical text detailing a History of Present Illness (HPI) Report from an emergency department as well as comprehension questions for the purpose of our study. In our study, we first presented non-medical passages and comprehension questions in six common fonts to identify participants' individual fastest and slowest fonts. We then gave participants medical passages in both their best and worst fonts while measuring reading speed and comprehension. This study was delivered to a population of Amazon Mechanical Turk …

Potential Production Of Theranostic Boron Nitride Nanotubes (64cu-Bnnts) Radiolabeled By Neutron Capture, Wellington Marcos Silva, Helio Ribeiro, Jaime Taha-Tijerina

Manufacturing & Industrial Engineering Faculty Publications and Presentations

In this work, the radioisotope 64Cu was obtained from copper (II) chloride dihydrate in a nuclear research reactor by neutron capture, (63Cu(n, )64Cu), and incorporated into boron nitride nanotubes (BNNTs) using a solvothermal process. The produced 64Cu-BNNTs were analyzed by TEM, MEV, FTIR, XDR, XPS and gamma spectrometry, with which it was possible to observe the formation of64Cu nanoparticles, with sizes of up to 16 nm, distributed through nanotubes. The synthesized of 64Cu nanostructures showed a pure photoemission peak of 511 keV, which is characteristic of gamma radiation. This type of emission is desirable for Photon Emission Tomography (PET scan) …

Smart Environments For Assisted Living: A Multidisciplinary Collaboration In Engineering And Architecture Education, Adriana Rios-Santiago, Anabel Pineda-Briseno, Jesus A. Gonzalez-Rodriguez, Uriel Saul Huerta

Manufacturing & Industrial Engineering Faculty Publications and Presentations

This paper presents a description of a collaborative project based on the integration of technology development in the built environment for assisted living. The multidisciplinary collaboration is developed as a cooperative commitment to provide support for cross-border, collective projects. It was initiated as a project-based learning setting between undergraduate engineering students, and four years later the program shifted to include undergraduate architecture students and engineering master’s students. The learning experience opens the gate to a completely new collaborative setting, yet to be established, independent from its predecessor setting of project-based learning, focusing now towards an interdisciplinarity setting in cross-border collaboration. …

Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang

USF Tampa Graduate Theses and Dissertations

The world’s population is rapidly aging and the increasing demand for home and health care services from this aging population brings unprecedented challenges to the economy and society. Ambient-assisted smart homes, residences equipped with ambient sensors to monitor the resident’s daily activities in a continuous and unobtrusive way, present great potential to manage the growing care service needs of this older population segment, and enable them to age-in-place.

Despite growing research, using ambient sensor data from private homes to monitor daily activities, health and wellness still faces significant challenges. To study ambient sensor data from private homes where annotated data …