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University of Tennessee, Knoxville

2023

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Articles 1 - 4 of 4

Full-Text Articles in Analytical, Diagnostic and Therapeutic Techniques and Equipment

Implementation Of Standardized Patient Education To Improve Adherence With Colonoscopy For Colorectal Cancer Screening, Melissa Leal Hearn, Melissa M. Hessock, Tara L. Hahn Nov 2023

Implementation Of Standardized Patient Education To Improve Adherence With Colonoscopy For Colorectal Cancer Screening, Melissa Leal Hearn, Melissa M. Hessock, Tara L. Hahn

Graduate Publications and Other Selected Works - Doctor of Nursing Practice (DNP)

BACKGROUND: Colorectal cancer (CRC) is the third leading cause of cancer deaths among men and women in the U.S. CRC is preventable and manageable when detected early. Approximately 30% of average-risk Americans are overdue for colonoscopy screening. Colonoscopy screenings can reduce death by 67%. Current evidence suggests CRC screening education improves screening uptake among men and women at average-risk age.

LOCAL PROBLEM: The setting of this practice improvement project was a private colorectal surgery practice in South Texas, serving primarily Hispanic/Latino and Caucasian patients. Cancellation rates before colonoscopy were 16.8%, and there was no standardized education for CRC …


Decreasing Perioperative Medication Errors With Standardized Labeling Education, Stephanie Mccain, Emily Almond, Anna Wong, Julie Bonom Nov 2023

Decreasing Perioperative Medication Errors With Standardized Labeling Education, Stephanie Mccain, Emily Almond, Anna Wong, Julie Bonom

Graduate Publications and Other Selected Works - Doctor of Nursing Practice (DNP)

BACKGROUND: Medication errors are prevalent within the perioperative setting (Wahr et al., 2017). The anesthesia provider is the sole professional in charge of the medication process in the operating room, which results in fewer safety checks than in other healthcare settings (Nanji et al., 2016).

LOCAL PROBLEM: The proposed scholarly project aimed to reduce medication errors at an academic medical center in the Southeast using an educational module focused on standardized narcotic syringe labeling. The participants were anesthesia providers in the operating room at the project site.

METHODS: The Evidence-Based Practice Improvement model was used to guide the development, implementation, …


Implementation Of A Single-Patient-Use Airway Taping Product In The Operating Room, Savannah Sierra Nicole Craig, Kaitlin D. Burrell, Jennifer Patrick Oct 2023

Implementation Of A Single-Patient-Use Airway Taping Product In The Operating Room, Savannah Sierra Nicole Craig, Kaitlin D. Burrell, Jennifer Patrick

Graduate Publications and Other Selected Works - Doctor of Nursing Practice (DNP)

BACKGROUND: Anesthesia providers use adhesive tape to secure advanced airway devices. Rolls of adhesive tape serve as reservoirs for pathogens. Rolls of tape do not have instructions on how they are to be reused, cannot be disinfected, and should not be repurposed. The re-use of rolls of tape poses a risk to patient safety.

LOCAL PROBLEM: The project facility was an academic medical center in the Southeast region of the United States. The facility does not have taping practice guidelines in place. Rolls of tape are handled without gloves, used by several providers, placed on multiple patients’ faces, and stored …


A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb May 2023

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 …