Refugee women face many challenges to obtaining maternal, reproductive, and sexual health post-resettlement including the language barrier, navigating the healthcare system, finding childcare to attend appointments, and cultural mismatches between their beliefs and practices around the prenatal, childbirth, and postpartum periods and that of the healthcare system in which they resettle into. This cultural barrier poses a challenge to healthcare providers as well as it necessitates that they respect their patients’ cultural beliefs while still providing them with the highest standard of care. Cultural competency training has been used to assist providers in understanding and responding to cultural differences, but gaps still exist when it comes to navigating specific scenarios. The objective of this research was to conduct a literature review of studies pertaining to refugee maternal, reproductive, and sexual healthcare post-resettlement to investigate the following questions: how tensions between biomedically accepted best practices and cultural norms present themselves in these healthcare fields, how healthcare providers take into consideration their patients’ cultural beliefs and norms when providing maternal, reproductive, and sexual healthcare to refugee women, and what can be done to continue to improve the provision of culturally appropriate care to refugee women. Findings from twenty different studies that focused primarily on eight cultural groups identified that Cesarean sections, inductions, and certain family planning methods are significant points of contention regarding cultural norms for refugee women and that they prefer certain foods, birthing positions, and other cultural practices during the delivery. Healthcare providers consider their refugee patients’ cultural beliefs by creating relationships with them built on trust, utilizing community liaisons, and through attempts to accommodate cultural practices when possible. Some potential improvements offered to improve cultural competency were improved cultural competency training that focused on how healthcare providers ask questions and interact with their patients, increased partnership with refugee communities, and an emphasis on patient education surrounding interventions and procedures related to maternal and reproductive health that could cause hesitations. The results of this literature review accentuated the importance of relationships within the field of refugee women’s healthcare, between both refugee patients and their providers and refugee communities and the healthcare systems. Providing refugee women access to more culturally competent healthcare can increase their trust in the healthcare systems of the countries they resettle in and healthcare utilization that can contribute to improved health outcomes for refugee women and their children.

In the US, underrepresented racial and ethnic minorities receive less than adequate health care in comparison to White Americans. This is attributed to multiple factors, including the long history of structural racism in the US and in the medical field in particular. A factor that is still prevalent today is the lack of diversity within the healthcare workforce. Racial and ethnic minorities are underrepresented in most healthcare occupations. Moreover, many physicians may continue to harbor implicit biases that may interfere with giving adequate care to patients of different backgrounds. We propose that diversity in healthcare should be increased through educational programs and a revamp of existing systems such as medical schools. The increased diversity would mitigate some of the health disparities that exist amongst minorities, as medical professionals are more likely to give adequate care to those who are members of the same community. Increased diversity would also help to increase the cultural competency of physicians as a whole.

Quantum computing is an emerging and promising alternative to classical computing due to its ability to perform rapidly complex computations in a parallel manner. In this thesis, we aim to design an audio classification algorithm using a hybrid quantum-classical neural network. The thesis concentrated on healthcare applications and focused specifically on COVID-19 cough sound classification. All machine learning algorithms developed or implemented in this study were trained using features from Log Mel Spectrograms of healthy and COVID-19 coughing audio. Results are first presented from a study in which an ensemble of a VGG13, CRNN, GCNN, and GCRNN are utilized to classify audio using classical computing. Then, improved results attained using an optimized VGG13 neural network are presented. Finally, our quantum-classical hybrid neural network is designed and assessed in terms of accuracy and number of quantum layers and qubits. Comparisons are made to classical recurrent and convolutional neural networks.

The United States spends far more on healthcare than other developed countries, and it is increasing at a rapid pace that places intense financial pressure on the American public. The high levels of spending are not attributable to increased quality of care or a healthier general population. Rather, the culprits are a combination of uniquely American social and cultural factors that increase the prevalence of chronic illness coupled with a large and complex healthcare industry that has a multitude of stakeholders, each with their own motivations and expense margins that inflate prices. Additionally, rampant lack of transparency, overutilization and low-quality care contribute to unnecessarily frequent and expensive payments. Public and private institutions have implemented legislation and programs that provide temporary relief, but powerful lobbying efforts by healthcare-related organizations and a general American aversion to high government involvement have prevented the United States from creating effective, long-lasting reform.