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Residual neuromuscular blockade (rNMB) following general anesthesia can impair pulmonary mechanics and place patients at an increased risk to develop postoperative pulmonary complications (PPCs) (Saagar et al., 2019). PPCs are associated with increased readmission rate, hospital length of stay and overall morbidity and mortality (Kirmeier et al., 2019). Current literature suggests that clinicians play a pivotal role in the reduction of rNMB through the accurate assessment and interpretation of neuromuscular blockade with a peripheral nerve stimulator (PNS) (Thilen & Bhananker, 2016). For this project, a survey was distributed to anesthesia providers at a level-1 trauma center. Nine questions regarding neuromuscular blockade monitoring were included; two questions assessed current practice and seven questions assessed literature-based knowledge. The survey results revealed that while some content areas reflected up-to-date practice and knowledge by the practitioners, others did not align with current literature. For example, only 12.9% of survey participants correctly identified the most important and reliable use of the train-of-four count (TOFC), the most commonly used mode of the PNS. The identified areas of educational needs were identified via the survey and included on a cognitive aid to be used as an intra-operative reference tool. This quality improvement project recommends continuing the evaluation and analysis of current practice trends as new literature and management modalities evolve.
There are a variety of distractions that can occur in the operating room during the induction of anesthesia. A review of the literature revealed that common distractions include: noise, music, cell phones and pagers, production pressure, and unnecessary conversations. This project is part of a larger quality improvement project investigating anesthesia providers’ perceptions of the frequencies and types of distractions occurring during induction at three different sites: an ambulatory surgery center, a mid-sized, suburban hospital, and a level one trauma center. This project focuses on identifying distraction severity and frequency at an ambulatory surgery center. An anonymous, electronic survey was distributed to physician anesthesiologists, certified registered nurse anesthetists (CRNAs), and student registered nurse anesthetists (SRNAs), at these three different clinical locations within a large healthcare system. The survey asked providers to rate perceived frequency and severity of selected distractions on a modified Likert scale. A total of thirteen anesthesia providers working at the ambulatory surgery center responded to the survey. The results show that conversations were found to be the most severely distracting while music and equipment alarms were equally found to be the least distracting. Females found music, conversations, and personal cell phone use to be more distracting than males. Younger anesthesia providers found equipment alarms to be more distracting than older anesthesia providers. Across the three site locations, survey comparison found no difference between results. The aim of this project is to discover what is distracting to anesthesia providers during anesthetic induction so that future projects can begin to mitigate the occurrence of these distractors and promote increased patient safety during the induction of anesthesia.
ABBY CATHERINE SANDERS. Risk Factors and Nausea Prophylaxis in the Gynecological (GYN), Urological, and Ear, Nose and Throat (ENT) Surgical Population at an Urban Surgery Center
(Under the Direction of DR. STEPHANIE WOODS PHD)
This is a quality improvement (QI) project that examines post-op nausea and vomiting prophylaxis (PONV) and PONV in the Post Anesthesia Care Unit (PACU) in an Urban Hospital system. The clinical question for this QI project is: In the population of Gynecological (GYN), Urological, and Ear, Nose, and Throat (ENT) surgical patients 18 years and older, how does patient, anesthetic, and surgical risk factors for PONV and the delivery of antiemetics affect the incidence of PONV in the Urban setting?
The purpose of this project was to compare anesthetic, surgical, and patient risk factors with the number of antiemetics given, in order to determine anesthesia providers compliance with the Fourth Consensus Guidelines. Data related to patient, anesthetic, and surgical risk factors, and PONV in the PACU was collected via chart review. Data analyses were conducted to determine patient, anesthetic, and surgical risk factors, and PONV prophylaxis administration.
The Apfel score was not significantly associated with actual antiemetics. There was also no significant association between patient, anesthesia, and surgical risk factors and the risk for PONV. The percent of PONV at the Urban facility was 14.29%. Overall, 42.9% of patients did not receive the correct number of antiemetics. Education to improve the knowledge gap between understanding of the Fourth Consensus Guidelines and the application of its antiemetic interventions into practice is recommended to improve adherence to guidelines.
Keywords: PONV, gynecologic, ENT, Urologic, surgery, urban, anesthesia
This is a quality improvement (QI) project that examines post-op nausea and vomiting prophylaxis (PONV) and PONV in the Post Anesthesia Care Unit (PACU) in a Suburban hospital that is part of a large hospital system. Post operative nausea and vomiting (PONV) causes negative health sequelae, increases the financial burden, and decreases patient satisfaction. The clinical question for this QI project is: In the population of Gynecological (GYN), Urological, and Ear, Nose, and Throat (ENT) surgical patients 18 years and older, how do patient, anesthetic, and surgical risk factors for PONV and the delivery of antiemetics affect the incidence of PONV in a Suburban Hospital setting?
Data related to patient anesthesia, and surgical risk factors, and PONV in the PACU was collected via chart review. Data analysis was conducted to determine patient, anesthetic, and surgical risk factors, and PONV prophylaxis administration. The relationship between the Apfel score and the number of antiemetic medications administered during the intraoperative period was determined to not be predictive of antiemetic administration. Patient, anesthetic, and surgical risk factors did not predict PONV. The percentage of PONV was 14.29% at the Suburban hospital location. 60% of the patients in this sample did not receive the appropriate antiemetic prophylaxis, including under and over-administration. Education on patient, anesthetic, and surgical risk factors, and appropriate PONV prophylaxis administration per the Fourth Consensus Guidelines is recommended to improve practice.
Keywords: PONV, gynecologic, ENT, Urologic, surgery, suburban hospital, community hospital, anesthesia
Social disparities and implicit bias are detrimental to patient care and exist among providers. Research has shown that implicit bias hinders rapport between patient and provider, leading to patients becoming resistant to medical advice and treatment protocols and lead to providers to misinterpret or misunderstand patients. Therefore, it is crucial to identify levels of implicit bias among healthcare providers and the ramifications that implicit bias could induce. This quality project aims to assess and establish baseline levels of existing implicit bias among anesthesia providers in a healthcare system located in a large southeastern city.
Anesthesia providers from four hospitals were asked to complete the Harvard Implicit Bias Association test. Three hundred and seventy-four providers and thirty-two student registered nurse anesthetists received the email with instructions to complete the test. In addition, participants provided demographic information about their practice location, age, race, and anesthesia title. The results were scored using the Harvard IAT D-score ‘slight’ (.15), ‘moderate’ (.35), and ‘strong’ (.65). A total of forty-six individuals completed the survey: 26 certified registered nurse anesthetists, 18 students registered anesthetists and two anesthesiologists. There was no statistical significance at 95% confidence that showed the difference in provider bias based on race, location, or title.
The incidence of residual neuromuscular blockade following general anesthesia is as high as 60% (Saager, 2019). Residual neuromuscular blockade impairs pulmonary mechanics and places patients at an increased risk to develop postoperative pulmonary complications (PPCs) (Kheterpal et al., 2020; Rudolph et al., 2018; Leslie et al., 2021; Saager et al., 2019). PPCs are associated with an increased readmission rate, hospital length of stay and overall morbidity and mortality. A quality improvement project (QI) was conducted to examine anesthesia providers’ knowledge of clinical recommendations and to assess their current practice habits using neostigmine to reverse neuromuscular blockade. A survey was distributed to all anesthesia providers at a level-1 trauma center and data was collected anonymously during a one-month period. While 96.1% of respondents correctly identified the mechanism of action of neostigmine, about half failed to recognize the correct peak effect of neostigmine. The survey results also revealed an inaccurate understanding of the dosing recommendations for neostigmine according to the number of twitches elicited using a peripheral nerve stimulator in the train-of-four mode. After comparing the survey results to the evidence-based guidelines identified in the literature review and analysis, knowledge deficits from the survey were incorporated to create an intraoperative cognitive aid to guide the reversal of muscle paralysis using neostigmine. This QI project recommends ongoing evaluation and analysis of practice trends to promote best practices that are consistent with contemporary literature.
Infectious diseases pose a significant threat to public health worldwide as evidenced by the recent coronavirus 2019 (COVID-19) pandemic. Despite significant human losses, the advent of web-accessed, map-based “data dashboards” that can monitor disease outbreaks, proved essential in managing public health responses. In many cases, the backend of these dashboards employs basic mapping functionality, displaying counts or rates. As the pandemic advanced, the identification of elevated rates was increasingly important in the geographical allocation of public health resources. However, such maps miss the opportunity to provide accurate information to policy decision makers such as the rate of disease spread, cyclicity, direction, intensity, and the risk of diffusion to new regions. Space-time geoanalytics, when coupled with rich visualizations, can address these shortcomings. Moreover, when implemented over the web, such functionality can be accessed from virtually anywhere.
This dissertation presents a web-based geographic framework for detecting and visualizing explicit space-time clusters of infectious diseases. First, I conduct a systematic review of the literature around the theme of space-time cluster detection for infectious diseases to identify state-of-the-art techniques that should be included in the proposed web-based framework. Second, I develop a tightly coupled, web-based analytical framework for the detection of clusters of infectious diseases using interactive and animated 3D visualizations to aid epidemiologists in readily and adequately uncovering the characteristics of space-time clusters. As a proof of concept, I populate the framework with COVID-19 county-level data for the 48 contiguous states in the US, and demonstrate data retrieval and storage, space-time cluster detection analysis, and 3D visualization within an open source WebGIS environment. Third, I evaluate the prototype in two steps: 1) present this and two existed COVID-19 systems to a group of infectious diseases experts and solicit feedback, 2) and evaluate functionalities on the prototype by conducting a user study with graduate students in a setting of online surveys.
This tightly coupled approach facilitates the detection of space-time clusters of diseases in a computationally acceptable timeframe. The characteristics of this framework (generic, open source, highly accurate, modifiable) will enable low-cost monitoring of the spatial and temporal trends of diseases causing high risks of infection.
Organizations often struggle to engage their workforces despite various known benefits and predictors of employee engagement. The current study examined a new approach to promote employee engagement—1:1 meetings—which are commonly occurring, theoretically grounded, and understudied. Leveraging job-demands resources and self-determination theories, it was hypothesized that the quantity (i.e., frequency) and quality (i.e., presence of manager task- and relations-oriented behaviors) of 1:1 meetings promote direct report engagement by satisfying direct reports’ basic psychological needs. The proposed moderated mediation model was tested with data collected from two time-separated online surveys (N = 303). Results suggest that 1:1 meeting quality—particularly manager relations-oriented behaviors—plays a stronger role in promoting direct report engagement as compared to 1:1 meeting quantity—with the important caveat that these meetings happen at least monthly. Results also suggest that 1:1 meetings are conceptually distinct from and can promote direct report engagement above and beyond other manager-direct report meetings and interactions by better supporting direct reports in a synchronous and individualized manner. Together, the current study supports 1:1 meetings as a critical tool managers can leverage to promote their direct reports’ engagement, while also contributing to both the meeting science and engagement literatures.
With the evolution of gear design requirements for new applications, classical gear inspection based on a time-consuming line-oriented tactile measurement must be replaced with a more rapid, areal inspection that can capture complex modern gear modifications. Triangulation-based optical instruments provide a promising path to meet new gear metrology demands with respect to access to the gear flanks and having sufficient speed and accuracy. In triangulation sensor measurement, the image position of a laser line strip on the sensor is analyzed to find the measured geometry. This image of the line on the sensor is calculated through a peak detection algorithm that produces a 'ridge line,' which is the line in the x-y sensor domain with the highest light intensity.
The physics of optical measurement dictates that speckles and scattered light exist during an optical inspection. As a result, when a triangulation sensor is used, the deflection of the scattered light may cause inaccurate peak detection and, therefore, large form deviations in the reconstructed (measured) geometry. In addition, multiple light reflections that influence point calculations from an optical measurement must be detected, eliminated, or remedied. This research provides an improved mathematical approach to ridge line detection in each sensor frame, to detect the peak position of that frame even more accurately. This algorithm is used to measure four reference geometries to evaluate its influence on point clouds from surface measurements when compared to the embedded (OEM) algorithm.
This dissertation offers the improved fidelity of triangulation sensor measurements for optical inspection by developing a novel mathematical approach. It can be used in the future closed-loop control process where the new gear production processes require fast-optical measurement and evaluation processes to trace back from the produced gear geometry to the manufacturing process. This can be achieved by equipping the manufacturing machine with suitable optical measuring devices, an appropriate evaluation strategy, and an inline inspection.
All-solid-state batteries (ASSBs) are considered promising candidates for next-generation batteries due to their excellent safety performance guaranteed by inorganic solid electrolytes (SEs) with the non-flammability nature, as well as the greatly increased energy density enabled by the adoption of lithium metal anode. Unlike conventional lithium-ion batteries (LIBs) using liquid electrolytes, all the components within the ASSBs system, including the composite cathode, lithium anode, and solid electrolyte, are solid-state. Solid-solid interfacial contacts within ASSBs, such as the dendrite-electrolyte interface and electrode-electrolyte interface, are the origin of interfacial instability issues. The interfacial instability problems mainly exhibit in the form of lithium dendrite growth-induced short circuits and interfacial debonding failure inside composite cathode, which are the major hurdles on the road towards the large-scale commercialization of ASSBs. Experimental characterizations are limited by the coupling of the solid nature of SE (vision overlap), and ultrasmall length scale. Therefore, versatile and physics-based models to describe the electrochemical behaviors of the ASSBs are in pressing need.
Herein, considering the highly multiphysics nature of ASSB behaviors, fully coupled electrochemo-mechanics models at different scales are developed to investigate the underlying mechanism of dendrite growth and interfacial failure. From the energy conservation perspective, the electrochemical-mechanical phase-field model at the electrolyte scale is firstly established to explore the dendrite growth behavior in polycrystalline SE. The newly formed crack and the grain boundary are found to be the preferential dendrite growth paths, and stacking pressure affects the driving force for both dendrite growth and crack propagation. Next, the cell-scale multiphysics modeling framework integrating the battery model, mechanical model, phase-field model, and short-circuit model is developed to study the entire process from battery charging to dendrite growth and to the final short circuit. The governing effects from various dominant factors are comprehensively discussed. Further on, inspired by the “brick-and-mortar” structure, the strategy of inserting heterogeneous blocks into SEs is proposed to mitigate dendrite penetration-induced short circuit risk, and the overall dendrite mitigation mechanism map is given. Finally, the three-dimensional fully coupled electrochemical-mechanical model is developed to investigate the interfacial failure phenomena, taking into account the electrochemical reaction kinetics, Li diffusion within the particle, mechanical deformation, and interfacial debonding. The randomly distributed LiNi1/3Co1/3Mn1/3O2 primary particles result in the anisotropic Li diffusion and volume variation inside the secondary particle, leading to significant nonuniformity of the Li concentration, strain, and stress distributions. This also serves as a root cause for the internal cracks or particle pulverization. The particle volume shrinkage under the constraint of the surrounding SE triggers the interfacial debonding with increased interfacial impedance to degrade cell capacity. This study explores the dendritic issue and mechanical instability inside ASSBs from the multiphysics perspective at different scales, obtaining an in-depth understanding of the electrochemical-mechanical coupling nature as well as providing insightful mechanistic design guidance maps for robust and safe ASSB cells.
