Due to the COVID-19 pandemic, pre-health individuals around the world encountered a range of challenges. Research and internship opportunities were cancelled, clinical experience was unreachable, and prerequisites became more demanding in a remote setting. I myself was working in a research lab in Switzerland when the pandemic was declared, resulting in my career-altering internship to be cut short six months. My life-long friend, Alejandra, had the same experience and reached out to me with an extraordinary idea to unite and empower pre-health individuals on a national level. With my skills in event planning combined with her vision, we built the National Pre-Health Conference (NPHC): a 3-day virtual event for pre-health individuals to explore medical careers and learn how to pursue their professional goals, particularly during these uncertain times. We held our inaugural conference with the theme A Future in Medicine in 2020 with over 1000 attendees from around the country. In 2021, we held our second-annual conference with the theme Unity in Healthcare with over 1000 attendees as well. In addition to planning the second-annual NPHC, I employed pre-event and post-event surveys to assess the confidence level of attendees before and after the conference in healthcare experience, research experience, standardized testing, community service, academics, essay writing, and completing graduate/professionals school applications. We found that NPHC improved the confidence level of attendees in all categories. Overall, understanding how NPHC benefits pre-health students will help our team improve for future conferences.

A patient's adherence to their treatment plan is crucial for management of chronic disease. The literature supports the fact that adherence is low, often at or below 50%. In order to adhere to one’s treatment plan, a patient must have accurate recall of this plan. A large body of research has established that patient recall is poor, and there is a growing body of research examining ways to improve recall, and thus, treatment outcomes. The present study examines differing delivery methods of the After Visit Summary in order to improve adherence, treatment outcomes, and patient satisfaction. It also evaluates the impact of visit modality (virtual vs. face-to-face visits) on patient recall for treatment information.

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.

Artificial intelligence (AI) and machine learning (ML) is rapidly evolving with enormous impact on a wide range of individual and societal matters including in health care, now and in the future. The goal of this research project is to assess the current knowledge level of AI and ML in health care among healthcare professionals and the lay public. Results from this research will identify knowledge gaps and educational opportunities to improve future use and applications of AI and ML in health care.

This project discusses what Artificial Intelligence (AI) is and how it is beneficial for society. The project is in favor of AI and talks about how AI is becoming apparent in everyday use cases, along with technology such as phones and cars. The majority of the thesis shows how AI is helpful for healthcare and can assist physicians and nurses do their jobs. Also, how AI helps with medical imaging, drug discovery, dieting, medical devices, and other applicable cases.

In recent years, artificial intelligence (AI) has become an increasingly important resource for individuals and corporations. In the health care industry, there is a growing demand for AI and related technologies to assist in everything from surgery to janitorial duties. While there is the usual skepticism surrounding AI, it is important to understand how it works, its benefits, and its risk. Medically speaking, AI has the potential to aid physicians in diagnosis and treatment recommendations. The technology, however, presents issues surrounding data privacy as well as embedded biases in the algorithms used for intelligent systems. Mitigating these potential risks will be important to the successful implementation of AI in a health care setting. As artificial intelligence becomes more prominent in this space, there is a valid fear that it will result in severe job displacement and force many people out of their fields. This transition towards a more automated hospital will require many medical personnel to learn new skills and move towards jobs that require a more significant amount of empathy to thrive in the new economy. For decades, people have been worried about the effects of more automation and machinery, but we have seen that where some jobs are replaced with technology, other jobs are created. The findings of this thesis show that while AI is likely to replace some human workers, there is minimal reason to worry about complete job displacement in the near future. Long-term, the significance of AI in job replacement is more of an unknown. However, with knowledge about how artificial intelligence could be impacting us now, patients, physicians, and hospitals can better prepare and understand the impact that AI will have on each of them specifically.

Substance use disorders account for billions of dollars annually in emergency and inpatient healthcare, not taking into account the healthcare costs of the disorders with which substance use disorders are associated with increased risks of developing. However, while treatment for these disorders shows a decreasing action on health costs, a low percentage of affected individuals receive treatment, despite many insurance payers providing coverage for treatments of this nature. Thus, this maintains the issues under the current healthcare system of mitigatable, generally higher, healthcare costs and increased health risks for individuals with substance use disorders.

Artificial intelligence is one of the biggest topics being discussed in the realm of Computer Science and it has made incredible breakthroughs possible in so many different industries. One of the largest issues with utilizing computational resources in the health industry historically is centered around the quantity of data, the specificity of conditions for accurate results, and the general risks associated with being incorrect in an analysis. Although these all have been major issues in the past, the application of artificial intelligence has opened up an entirely different realm of possibilities because accessing massive amounts of patient data, is essential for generating an extremely accurate model in machine learning. The goal of this project is to analyze tools and algorithm design techniques used in recent times to accelerate data processing in the realm of healthcare, but one of the most important discoveries is that the standardization of conditioned data being fed into the models is almost more important than the algorithms or tools being used combined.

For most women, pregnancy is the period in which they will have more interaction with the healthcare field than any other period in their lives. The quality and accessibility of obstetric care varies greatly throughout the United States, and health disparities in this field have the largest impact on African American women. Black mothers in the U.S. are three to four times more likely than white mothers to die as a result of pregnancy related complications. The increased risk of maternal morbidity and mortality seen in the African American population is largely due to preventable causes. This thesis project includes three case studies which analyze the most prevalent and preventable sources of health disparity affecting Black mothers: preeclampsia, hemorrhage, and cesarean section. Possible solutions to each of these disparities are explored on an individual, institutional, and societal scale.

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.