The University of Texas at Tyler
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DNP Final Report: Effects of Open-Access Scheduling on Patient No-Show Rates in an Outpatient Clinic
Full text linkNo-show rates in a South Texas outpatient clinic have been as high as 16% to 20% which increases wait times to be seen in the clinic and decreases patient access to outpatient care. This no-show rate data has continued despite multiple interventions that have been implemented in an academic health science center. Physical, socio-economic, geographic, and health/lifestyle factors affecting no show or missed appointments are crucial to determining the most appropriate interventions to alleviate this issue. No-show rates are important metrics to improve because it directly affects the organization\u27s revenue, access to care, and appointment wait times. Research evidence regarding interventions for improving no show rates include text messaging, appointment call reminders, patient portal, telehealth, and template optimization. Applying open-access scheduling in an outpatient clinic could potentially decrease no-show rates, increase patient care access, and increase patient satisfaction
DNP Final Report: Increasing Rapid Response Activations
Full text linkIn 2008, facilities were encouraged to develop an emergency response system. A system in which nurses could activate a team of specialists directed to the bedside of a patient with a deteriorating condition. Despite this initiative, nurses and hospital staff have failed to recognize deterioration and correctly activate a rapid response. The clinical problem: Nurses are failing to recognize patient deterioration and activate a rapid response. The practice question was, what will increase rapid response activations? This DNP Project focused on increasing the identification of patient deterioration and activation of the rapid response team. A systematic review of the literature, a critical analysis of the yielded studies, and the fit and feasibility of the facility revealed that the most appropriate intervention was a one-hour education on detecting deterioration followed by unfolding case studies. A quiz was given to the nurses as a pre-and post-education evaluation. The facility continued to collect data for six months post-intervention. The evaluation revealed a 28% increase in the quiz scores, a 28.5% increase in Rapid Response activations, and a 28.7% decrease in Code Blue activations. This project intervention has significantly impacted patient care in the host facility. Sustainability recommendations to the facility are to educate staff by having them review the recorded education and provide flyers of the activation criteria to staff, patients, and visitors. Carry out mock Rapid Response activations with staff quarterly
A MULTI-DIRECTIONAL SMART HIP IMPLANT WITH WIRELESS CONNECTIVITY FOR ENHANCED HEALTH MONITORING
No full textThe thesis presents the culmination of the smart hip implant project, which signifies a significant stride in orthopedic technology. By integrating piezoelectric and triboelectric systems into conventional implants, this study demonstrates the feasibility and effectiveness of creating intelligent implants. Through a meticulous design process and rigorous testing, novel configurations were developed to optimize energy harvesting efficiency and enable precise detection of mechanical loads experienced during various physical activities. The application of Finite Element Analysis provided critical insights into the localization of contact points, informing the strategic placement of harvesters within the implant for enhanced performance. Utilizing a cam follower and motor allowed for the realistic simulation of daily movements, validating the implants’ ability to detect loads and generate proportional electrical signals. Furthermore, the successful implementation of wireless data transmission highlights the potential for remote monitoring and personalized patient care. Overall, the findings of this thesis represent a significant advancement in orthopedic treatment modalities, promising improved patient outcomes and a higher quality of life for individuals with hip implants
The clinical application of incisional negative pressure wound therapy in severe subcutaneous emphysema: A case series
Full text linkSevere subcutaneous emphysema (SSE) is the presence of a high-volume accumulation of air in the subcutaneous tissue caused by traumatic injuries, infections, iatrogenic causes, or can also manifest spontaneously. A variety of techniques have been reported, with varying levels of success.
We present a multicenter case series detailing four patients who developed SSE and were treated with Incisional Negative Pressure Wound Therapy (INPWT). All patients significantly improved with the INPWT treatment within 6 to 48 h. Our experience suggests INPWT is a valuable procedure available for treating SSE and recommend prospective randomized studies be conducted to determine targeted patient selection and clinical application of INPWT among the SSE patient population
SMART ZONING CONTROL FOR AIR CONDITIONING SYSTEMS
Full text linkNearly 45% of the energy consumed in residential buildings goes for Heating, Ventilation, and Air Conditioning (HVAC). Typical HVAC systems are mostly controlled by one thermostat that is usually located in the living room. This means that the HVAC system is running without consideration of the thermal conditions in the other rooms (zones), which might be colder (or warmer). Colder zones in the summer indicate that a lot of energy is wasted, and warmer zones mean that the HVAC system can’t produce a good comfort level. Therefore, zoning was introduced into relatively recent HVAC systems. Zoning in HVAC systems uses motorized dampers to regulate the airflow rate in specific home zones. This should help to deliver more air to the occupied zones for comfort or to reduce the air share for the unoccupied zones for ultimately reducing energy consumption. The main challenge that faces zoning systems is how to find the air flow rate for each zone that will satisfy both dynamic conditions of comfort and low energy consumption. This project aims to design and test a smart Zoning system that can find the optimal air volume flow rate for each zone. The Zoning system is designed to operate autonomously based on real-time measurements from sensors. Model predictive control (MPC) is used as a basis for this work to evaluate the required airflow rate for each zone given conditions such as the time during the day, number of occupants, etc. MPC is an optimal control strategy that allows calculating the airflow rate values based on the minimization of the temperature error (difference between actual and desired value) combined with minimizing energy consumption.
In order to implement an MPC, a thermal model of the zones was developed. In the development process, the main focus was to design a model that provides acceptable results, while being simple enough to minimize the workload for the controller. Since a higher complexity of the model will result in an increased susceptibility to disturbances and error, and a slower controller response. For that reason, the model was developed by focusing on the main sources of energy such as conduction from adjacent zones, outside conditions, and estimated internal loads. Additionally, this work included the investigation of the use of Artificial Intelligence (AI) algorithms like Reinforcement Learning (RL) to design smart zoning control systems as an enhanced strategy that would allow to take into consideration more factors without compromising the controller’s performance The results show that MPC zoning can reduce energy consumption by 40% on a typical summer day. Moreover, the temperature distribution in all zones is guaranteed to be as desired
INVESTIGATING THE CELLULAR MECHANISMS OF INTRACELLULAR pH REGULATION DURING EXPOSURE TO HIGH CO2.
Full text linkThere are at least two different strategies of pH regulation among fish. The first is coupled pH regulation (CPR), where regulation of blood pH facilitates tissue pH regulation; and the second is preferential intracellular pH (pHi) regulation (PPR), where tissue pH remains tightly regulated despite a sustained reduction in blood pH. The cellular and molecular mechanisms underlying the differences in pHi regulation are currently unknown. I investigated the mechanisms of pH regulation in fishes using Rainbow Trout (Oncorhynchus mykiss) and Channel Catfish (Ictalurus punctatus) which use CPR and PPR, respectively. Fish were exposed to elevated CO2 for either 3 or 24 h, then blood and tissues were collected and examined for molecular responses. Real Time-quantitative Polymerase Chain Reaction (Rt-qPCR) showed upregulation of slc4a4a, slc4a5 and slc4a7 by 24 h in heart and gill tissue of the catfish. Where the same isoforms had no significant changes in regulation within the trout heart but were down regulated in gill tissue. No significant changes were seen in expression of these three genes in catfish liver or muscle from the same tissue for trout. Expression time and localization of NBCe1 (slc4a4’s protein) was consistent with the mRNA expression in catfish tissue. This demonstrates that sodium-bicarbonate transporters may be important for PPR at the tissue level but may not have the same importance for fish using CPR
DISPARITIES IN COGNITIVE DECLINE ALONG THE TEXAS-MEXICO BORDER: INSIGHTS FROM THE 2021 BRFSS
Full text linkThe aging global population has brought increased attention to cognitive health and early detection of cognitive decline. Subjective Cognitive Decline (SCD), defined as self-reported memory or thinking problems, is an early marker of neurodegenerative diseases. Despite growing research, gaps remain in understanding how geographic disparities influence SCD prevalence and contributing factors. The Texas-Mexico border region, predominantly Hispanic and facing unique socioeconomic and health care challenges, offers a unique context to explore these influences. The purpose of this study was to examine the prevalence of SCD and related functional limitations in Texas-Mexico border counties versus non-border counties, using 2021 Behavioral Risk Factor Surveillance System data. Methods: A cross-sectional analysis of adults aged 45+ was conducted, focusing on demographic characteristics, chronic health conditions, health care access, and health behaviors as SCD predictors. Logistic regression models were used to assess these associations. Results: SCD prevalence was slightly higher in border counties (16.49%) than non-border counties (13.95%), but this difference was not statistically significant. However, SCD-related functional limitations were significantly more prevalent in border counties (66.21% vs. 46.31%, p = 0.0018), suggesting a greater impact on daily functioning. Significant SCD predictors included younger age, unemployment, depression, hypertension, heart disease, COPD, health care cost barriers, and physical inactivity. Conclusion: Findings highlight the need for targeted public health interventions in border counties, aimed at improving health care access, managing chronic conditions, and addressing socioeconomic disparities to reduce the functional impact of cognitive decline. These insights can guide efforts to reduce cognitive health disparities in underserved populations
Application of digital rock physics and machine learning to improve the understanding of fluid flow behavior through porous media
Full text linkAccurately estimating reservoir rock properties and understanding capillary trapping mechanisms are crucial for fluid storage and flow modeling in porous media, particularly for applications such as carbon dioxide sequestration (CCS) and underground hydrogen storage (UHS). This thesis presents a comprehensive workflow that combines machine learning techniques and pore-network modeling approach to predict petrophysical properties and assess the impact of microscopic pore structures on capillary trapping. In the first part, a convolutional neural network (CNN) framework is used to predict rock properties—such as porosity, throat area, and pore surface area—from micro-computed tomography (micro-CT) X-ray images. It has been observed that incorporating a greater variety of rock sample types during model training enhances the accuracy of predicting the properties of unknown rock samples. The model, trained on Bentheimer and Castlegate sandstone samples, achieved highest accuracy in predicting the properties of Leopard sandstone, with mean absolute percentage errors of 2.19%, 3.04%, and 6.08% for porosity, pore surface area, and throat area, respectively. Additionally, a regression model using extreme gradient boosting (XGBoost) predicted absolute permeability with an R² of 0.813 for Leopard sandstone, demonstrating the importance of pore network parameters like tortuosity in determining permeability. In the second part, this study evaluates the role of pore structures and networks in UHS by analyzing capillary trapping through a pore-network model and Land\u27s trapping coefficient. The Land constant showed a wide variation in the model constant, ranging from 0.2 to 2.7, depending on the pore properties of the rock sample. The analysis revealed that carbonate rocks exhibit higher Land’s constants compared to sandstone, implying lower hydrogen trapping efficiency in carbonate reservoirs. Field-scale reservoir simulations further quantified the fraction of injected hydrogen gas trapped due to capillary forces, linking pore-scale properties to reservoir-scale behavior. Together, these methods offer an efficient and scalable approach for predicting the morphological and flow properties of porous media, contributing valuable insights for selecting optimal sites for CCS and UHS
De-Colonizing and Enlivening Lifespan Development in Counselor Education with Experiential Exercises Across the Curriculum
Full text linkACA and IAMFC codes of ethics center culturally-affirming lifespan development skills as professional identity responsibilities specific to counselors. Despite the critical importance of lifespan, the training of CITs in this area is inadequate and grounded in research based on homogeneous samples and discriminatory practices. Counselor education is deeply in need of a lifespan curriculum that reflects diverse populations. The updated lifespan curriculum must be inclusive and consider the impact of context and culture on lifespan development. In this conceptual article, we call on counseling faculty to infuse updated developmental science with clinical skills development across their plans of study
A validated method for non-invasive urine collection in sodium polyacrylate-based diapers for PCR detection of uropathogens
Full text linkThis dataset provides information from a study that validates a method for non-invasive urine collection utilizing sodium polyacrylate-based diapers, designed for polymerase chain reaction (PCR) detection of uropathogens. The dataset includes samples from 17 participants, comprising seven clinically contrived samples inoculated with known uropathogens and ten samples collected from volunteers wearing sodium polyacrylate-based diapers. The study involved optimizing urine extraction from the diaper matrices, ensuring minimal loss of diagnostic sensitivity for downstream quantitative PCR (qPCR) analysis. The qPCR targeted 22 uropathogens, six fungal species, and 18 antimicrobial resistance (AMR) genes, providing comprehensive molecular characterization of urinary pathogens. Comparative analyses were performed between diaper-derived and standard urine samples, with data demonstrating high concordance in detection outcomes, despite a modest average reduction in qPCR sensitivity (ΔCt of -1.65). Matrix effects were evaluated to determine the impact of the diaper material on qPCR amplification efficiency. The dataset is valuable for further research into non-invasive diagnostic techniques for urinary tract infections (UTIs), particularly for populations unable to provide midstream urine samples, such as infants and elderly individuals. Potential reuse of this dataset includes evaluating non-invasive urine collection efficacy, exploring the interaction between sample matrices and molecular diagnostics, and assessing the scalability of diaper-based sampling methods in diverse clinical settings