Kennedy, Ashley

This thesis investigates the ethical implications surrounding the sudden death of a 46-year-old male patient from glioblastoma, a highly aggressive brain tumor. The analysis focuses on the intricate details of the case, dissecting the events that transpired, and identifying the medical and ethical mistakes that were made. Further, this thesis critically examines the decisions made by both the healthcare professionals and the patient, and the deficiencies in diagnosis, communication, and treatment strategy in the case. Because of delayed diagnosis and inadequate treatment, the patient suffered an untimely death. By unraveling the complexities of this case, this thesis seeks to contribute a nuanced perspective to the discourse on medical ethics, by offering insights into areas that demand improvement, both in this particular case, and in medicine more generally. Failures at multiple levels resulted in the patient deteriorating rapidly and missing the chance to say goodbye to his loved ones. In this thesis, I suggest that by fostering a compassionate and patient-centered approach to healthcare, we can provide more optimal care to individuals facing glioblastoma and similar formidable conditions.

As medical research expands to include a vast variety of new treatments and the world becomes increasingly interconnected, the ethics involving patient care and treatment plan development also become extremely important to consider. One of the most novel and widely unexplored fields of reproductive health is oncofertility, a field of medicine that aims to minimize the negative impacts of cancer treatment on fertility. For many childhood cancer patients, cancer treatment involves oncofertility-related discussions that involve their families, physicians, and many other people. This paper serves primarily to evaluate the quality of educational and clinical resources available to childhood cancer patients regarding fertility preservation, the current approach to these cases from an ethical perspective, and to propose a procedure for treatment plan development and decision making that carefully considers the values and beliefs of the patient, his/her family members, physicians, and ethics board members involved with the case to help standardize the process.

Cassava is the third-largest source of food carbohydrates in the tropics and is a major staple food among developing countries. Cassava contains cyanogenic glycosides which turn into cyanide and are toxic to the body when ingested in a high content. Cyanide poisoning causes many symptoms including severe abdominal pain which is also one of the symptoms occurring in patients with pancreatitis. Tropical diabetes or fibrocalculous pancreatitis diabetes mellitus is secondary to tropical pancreatitis which is a form of non-alcoholic chronic calcific pancreatitis found primarily in tropical regions. The symptoms include severe abdominal pain. In this study, I will hypothesize that there is a link between early life ingestion of cassava, inadequate protein intake, tropical chronic pancreatitis and tropical diabetes.

According to the Center for Disease Control and Prevention (CDC), 47,000 individuals died in 2017 due to an opioid overdose. Further, dentists are more likely to prescribe immediate-release opioids than other healthcare providers. In the late 1990s, dentists were responsible for 15.5% of prescriptions for immediate-release opioids, and 8% of these prescriptions in 2009. In this thesis I examine the reasons for this, including the ways in which a patient’s sex, age, race, and ethnicity play a role in dental prescriptions, and conclude that dentists do not consistently use the Prescription Drug Monitoring Program (PDMPs) or the guidelines set by the American Dental Association. I argue that to help to prevent opioid misuse and abuse dentists should do a risk assessment before prescribing opioids.

The practice of medicine is changing with the development of new Artificial Intelligence (AI) methods of machine learning. Coupled with rapid improvements in computer processing, these AI-based systems are already improving the accuracy and efficiency of diagnosis and treatment across various specializations. The increasing focus of AI in radiology has led to some experts suggesting that someday AI may even replace radiologists. These suggestions raise the question of whether AI-based systems will eventually replace physicians in some specializations or will augment the role of physicians without actually replacing them. To assess the impact on physicians this thesis seeks to better understand this technology and how it is transforming medicine. To that end this thesis researches the role of AI-based systems in performing medical work in specializations including radiology, pathology, ophthalmology, and cardiology. It concludes that AI-based systems will augment physicians and are unlikely to replace the traditional physician–patient relationship.

The nursing field is rapidly changing, and the role nurses play is expanding as they gain more autonomy. This in turn may affect the accuracy of current titles as they potentially neglect to regard experience and only represent education. This study will attempt to determine if titles affect how nurses at different levels are treated by colleagues. Through analysis of prior studies and interviews with individuals currently in the nursing field, the overall experiences will be evaluated as well as any programs that have been or could be implemented to facilitate a positive and productive workplace environment. While it is unrealistic to change education-based titles, programs can be implemented within the workplace to foster positive professional relationships and give employees a better understanding of each individual’s role so that the nursing environment is a team effort and not a competition

This thesis addresses the level of uncertainty in medical evidence and practice and asks if this level is acceptable. Current medical standards consider randomized controlled trials (RCTs) as the best, and most certain, form of evidence. Similarly, medical practice largely relies on differential diagnosis and diagnostic testing to diagnose patients. I will argue that RCTs as well as differential diagnosis and diagnostic testing contribute to uncertainty in medical practice. In the former, uncertainty stems from lack of representation, elimination of confounding factors, among other issues; while in the latter, uncertainty originates from technological limitations, similarity or variability in presentation, and number of diagnostic possibilities. I will argue that uncertainty in medical evidence and practice can and should be reduced. This can be done by expanding RCT testing and improving it by adding required mechanistic evidence, and by furthering research into better diagnostic technology and training.

There are still diseases in our current society such as pain in which the diagnosis is heavily reliant on the information that is given by the patient. With that much trust in just the patient, there is a possibility of the patients not being able to describe the symptoms properly or leaving information out from their history leading to an incorrect diagnosis. The most common form of treatment for pain is prescribing opioids, a schedule II controlled substance. In this essay, opioid mechanisms, guidelines for prescribing opioids and addiction as a result will be discussed. The current prescribing federal and state laws will be evaluated. In this thesis, I will argue that in order for patients suffering from pain to lead a healthier and safer life not only should prescribing laws be altered in which alternatives to opioids are heavily considered, multiple doctors should be consulted before a the prescription is written and a better patient monitoring/screening system should be in place.

Despite efforts by the United Nations, UNICEF, and the International Labor Organization (ILO), among others, child labor remains a widespread concern. In 2016,
152 million children were in child labor worldwide. Though child labor is widely recognized as a global health problem, research on the health effects of child labor is limited. Summary measures of population health provide a way to present information about both mortality and morbidity of a given population as a single metric. This project utilized gretl, an open-source statistical package, to model the data using ordinary least squares (OLS) in order to determine if there is a correlation between health, which was quantified using summary measures of population health, and child labor. The regression analysis showed that there is a significant correlation between child labor and health adjusted life expectancy (HALE) at birth, but not between child labor and disability adjusted life years (DALYs).

When investigating the relationship between clinical trials and antibiotic resistance, I realized the need for data on the growth of antibiotic resistance. There needs to be data that can clearly draw the line between antibiotic exposure and the growth of antibiotic resistance. To construct the data, scientists need to test various antibiotics against various bacteria and closely monitor the growth and spread of antibiotic resistance. The data set should include data on the types of antibiotics tested, the species of bacteria used for experimentation, the dosage of the antibiotics used, and the time it takes for the growth of resistance. Furthermore, this data set could also provide a better understanding of the interactions between different classes of antibiotics and different species of bacteria. The data set will produce information that will help develop alternative methods to combat antibiotic resistance.