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**Abstract:**



AMA Research Challenge 2023

Attitudes toward Remote Medical Education at an Urban Allopathic Medical School During the COVID-19 Pandemic

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Introduction: The AAMC Core Competencies require graduating medical students to be able to counsel patients on sensitive conversations, yet many graduates feel unprepared to apply these skills in a clinical setting. The University of Connecticut has introduced virtual patient encounters into our preclinical curriculum to augment medical students' ability to counsel on sensitive topics. Methods: We developed a didactic module including pre-class reading, a virtual encounter on firearm ownership, and a team-based learning session for first-year medical students. Students completed live standardized patient (SP) encounters before and after completing the module. SP encounters were assessed using the Master Interview Rating Scale (MIRS). To assess the impact of the virtual patient encounter, MIRS scores before and after the didactic module were compared between the intervention group and control group, who did not complete the virtual module. Results: Compared to the control group, students completing the virtual encounter demonstrated a statistically significant improvement in MIRS scoring associated with the following criteria: types of questions asked (p<0.001), verbal facilitation (p=0.003), empathy (p<0.001), motivation for change (p=0.001), and shared decision making (p=0.002) during SP encounters. Both groups showed similar scores on these MIRS criteria before the virtual curriculum was implemented; the control group did not demonstrate a significant improvement on their second attempt. Discussion: Our findings suggest virtual patient encounters are an effective method for teaching medical students to counsel on sensitive topics. Medical schools should consider incorporating virtual patients into preclinical curricula to model challenging conversations in a cost-effective and standardized manner.

Closing the Gap in Medical Student Counseling: A Virtual Curriculum

Background: 
25-hydroxyvitamin D (vitamin D) inadequacy has been shown to be associated with an increased risk of progressing from prediabetes to diabetes. Although clinical trials have demonstrated vitamin D supplementation can lower the risk of developing diabetes for prediabetic patients, the actual factors associated with vitamin D supplementation usage for prediabetic individuals have yet to be fully elucidated. The goal of this study is to investigate demographic and socioeconomic factors associated with vitamin D supplement usage among prediabetic individuals in the United States to better understand the barriers this population faces in supplement access and utilization.

Methods:
In this cross-sectional study, the National Health and Nutrition Examination Survey results between 2011 and 2018 were analyzed. 3,424 prediabetic adults over the age of 20 without liver or kidney disease were isolated. The outcome of vitamin D supplement intake level was classified as “Low” (<400 International Units [IU]), “Medium” (400-800 IU), or “High” (>800 IU). An ordinal logistic regression was performed with the predictor variables of age, gender, race, education, insurance, and family income to poverty ratio while controlling for serum vitamin D concentration, vitamin D dietary intake, and body mass index. 

Results:
Significant predictors of higher levels of vitamin D supplementation included being female (Odds Ratio [OR]: 1.735, 95% Confidence Interval [CI]: 1.409 – 2.135), and income (OR: 1.148, 95% CI: 1.049 – 1.257). Furthermore, increases in education level were correlated with greater odds of higher vitamin D supplementation levels: High school (HS) graduates OR: 1.696, 95% CI: 1.109 – 2.594), Individuals with at least some college experience (OR: 1.752, 95% CI: 1.124 – 2.730), and College graduates (OR: 1.778, 95% CI: 1.129 – 2.800).

Conclusion:
Although the cross-sectional nature of the analysis precludes drawing causative conclusions, these findings suggest that being female, greater family income, and increased education level may be associated with higher levels of vitamin D supplementation in the prediabetic population in the United States. Further investigations may uncover reasons behind these relationships and the differential utilization of vitamin D supplementation. Understanding the drivers and barriers for vitamin D supplementation among prediabetic patients can guide public health efforts in protecting against the progression from prediabetes to diabetes.

Factors Associated With Vitamin D Supplementation in the Prediabetic Population

Background: Over the past few decades, pharmaceutical drug prices have fluctuated for a variety of reasons, such as inflation, manufacturer changes, and legislative policies. The purpose of this study is to track price changes for a specific set of drugs commonly prescribed to a large portion of the adult patient population in order to analyze historical factors contributing to pricing trends, as well as to serve as an informative tool for future and current pharmaceutical consumers. 

Methods: The IBM Micromedex® Redbook was queried to obtain the manufacturers and prices of five generic drugs (warfarin, atorvastatin calcium, amlodipine besylate, alprazolam, levothyroxine sodium) and four of their respective trade name drugs, excluding warfarin (Lipitor, Norvasc, Xanax, Synthroid). The Average Wholesale Price (AWP) and corresponding dates of these drugs’ production and sales were graphed on a scatter plot, with a trendline included to visualize the behavior of price changes over time.

Results: The AWP unit price of warfarin increased 236% from 1988 to 2020. The AWP unit price of Lipitor™ increased 659% from 1998 to 2021, while its generic counterpart atorvastatin calcium increased 5% from 2011 to 2022. The AWP unit price of Norvasc™ increased 644% from 1992 to 2022, while its generic counterpart amlodipine besylate decreased 0.03% from 2007 to 2020. The AWP unit price of Xanax™ increased 1811% from 1988 to 2022 while its generic counterpart alprazolam increased 3069% from 1993 to 2018. The AWP unit price of Synthroid™ increased 1654% from 1988 to 2022 while its generic counterpart levothyroxine sodium increased 1046% from 1991 to 2020. 

Conclusion: The rate of increase in these drugs’ AWP unit prices, notably for the trade name counterparts, exceeds that of the corresponding inflation rate in the United States for their specific manufacturing and sale time periods. The larger than expected increase in price could be attributed to legislative policy changes rather than microeconomic changes and inflation. However, this study is limited in the choice of drugs studied and database utilized, as the IBM Micromedex® Redbook only provides information on products approved by the U.S. Food and Drug Administration. Future studies could expand the studied drug selection or compare rate of increase in the U.S. to that of other countries. Overall, AWP unit prices for trade name drugs commonly prescribed to adult populations are increasing at a rate greater than natural inflation. 


Historical Analysis of Generic and Trade-Name Pharmaceutical Drug Prices

Background: Effective and efficient communication between physicians and patients is a major component of healthcare. As the U.S. population continues to grow, the Limited English Proficiency (LEP) population also continues to grow. Language barriers play a role in health disparities among LEP populations. LEP patients tend to report decreased patient satisfaction, they are less likely to obtain the recommended preventive care services and/or testing such as mammograms, pap smears, colon cancer screenings, and influenza vaccinations. Although LEP patients are less likely to have regular preventive screenings, they are more likely to have unnecessary testing when at the emergency department, more likely to be hospitalized, and have longer hospital stays when compared to English-speaking patients. They have a decreased understanding of diagnosis and treatment options, poorer adherence to treatment and follow-up for chronic illnesses, and increased medication complications. Therefore, LEP populations are at higher risk of poorer health outcomes. Furthermore, due to a language barrier, physicians may misunderstand a LEP patient’s symptoms, which may lead to diagnostic tests that are unnecessary. The purpose of this review was to explore interventions aimed at improving healthcare access and preventive screening services among LEP populations in the U.S.

Methods: A systematic literature search was performed from 1995 to 2020 using online medical, public health, and social science databases. These databases included: PubMed, JSTOR, Access Medicine, Google Scholar, OVID (MEDLINE), and Clinical Key. Older literature was used to understand if there have been any changes in language accessible services throughout the last 25 years. A total of 24 articles were utilized for this review.

Results: An analysis of the literature revealed past interventions focused on increasing healthcare education among LEP patients, increasing patient-physician communication by using bilingual physicians, increasing access to language services with mobile translation applications, and adapting evidence-based interventions as well as the P3 (Practice-, Provider-, and Patient level) Model.

Conclusion: Effective interventions working to increase language accessible services and build rapport with LEP patients by using bilingual physicians and mobile translating applications have been shown to increase healthcare access among LEP populations. It is essential that physicians take these findings into consideration to avoid adverse outcomes. Current research has not considered the impact of communication barriers on cancer diagnosis and treatment among LEP populations. Future efforts should focus on understanding how language barriers impact health outcomes among LEP cancer patients.

A Review of Interventions Addressing Ways to Improve Healthcare Access and Preventative Screening Services among Limited English Proficiency Population in the United States

Introduction
The CDC’s “Adult Obesity Maps in 2022” suggests that the southern parts of the United States (US) have the highest prevalence rates of obesity(1). Similarly, the Health Resources and Services Administration identifies the Southern states as having the highest numbers of medically underserved areas(2).
The health implications of obesity are numerous, with some affecting reproductive ability in both genders. With infertility on the rise, studies have examined the numerous modalities that implicate obesity in female infertility. One such route associates the increased adipose tissue with reduced oocyte maturation by promoting functional hyperandrogenism and hyper-estrogenism, which triggers anovulation(3).
This study was devised to investigate the landscape across the different regions in the US and detect correlations between female infertility and obesity. The hypothesis was that the southern region would have the highest correlation between female infertility and obesity compared to other regions across the US.
Methods
This cross-sectional study used the NIH’s ‘All of Us’ Researcher Workbench to first create a workspace titled “Incidence of female infertility due to obesity in US regions.” Next two cohorts were devised containing all ages, ethnicities, and races. The first group, the control cohort, included “female infertility” participants and excluded “sex assigned at birth – male” participants. The second group, the variable cohort, consisted of participants with both “obesity” and “female infertility” while excluding “sex assigned at birth – male” participants.
The US was divided into four regions based on zip code. The first three digits of each participant’s zip code were logged and localized to the Midwest, Northeast, South, or West. The Midwest consisted of participants from Wisconsin, Michigan, Iowa, Illinois, Indiana, and Ohio. The Northeast region had participants from Pennsylvania, New York, and the District of Columbia. The South had participants from Louisiana, Texas, Mississippi, Alabama, Georgia, Tennessee, South Carolina, Virginia, Florida, and Arkansas. The West region had participants from California, Washington, Colorado, Arizona, Utah, and New Mexico.
Two datasets were then created using the control cohort and the variable cohort, respectively, and then the zip code socioeconomic status data was extracted. The participant’s data was coded into the Python analysis software. Various data points were also recorded and analyzed. For each dataset consisting of one cohort, the length of the entire code was run, and for the control cohort and for the variable cohort. Next, a code was run to extract all zip codes with the number of participants included in each zip code. After all the data was extracted, each participant’s zip code was assigned to their appropriate region. All the data was then put into Microsoft Excel. The number of participants with both female infertility and obesity was then compared to the number of females with infertility only and compared against each region to establish a correlation percentage.
Statistical analysis used Chi-Square and focused on identifying degrees of freedom.
Results
In the control group, the number of participants who qualified for infertile females was 2,754, with 1,182 participants from the Midwest, 1,062 from the Northeast, 279 from the South, and 231 from the West. For the variable cohort, 1,198 participants were concurrently infertile and obese females. This data was also sub-grouped based on region: the Midwest with 481 participants, the Northeast with 491 participants, the South had 133 participants, and the West had 93 participants. Each variable group number was subsequently divided by its respective control group’s number of infertile female participants. The percentages for each region were: Midwest (28.9%), Northeast (31.6%), South (32.3%), and West (28.7%).
The results suggest that the Southern US region has the highest percentage of concurrently infertile and obese females compared to the rest of the country, while the lowest is the West. Chi-squared results yielded 467.376 with 3 degrees of freedom. These findings were statistically significant (two-tailed P value < 0.0001).
Conclusion
Our study utilized the NIH ‘All of Us’ Researcher Workbench to demonstrate the variation among the different United States regions and their correlations between females who are both obese and infertile. Knowing that the southern region of the United States has (A) the highest rates of obesity, (B) the highest rates of medically unserved communities, in addition to (C) the highest rate of concurrent female infertility and obesity, this study serves as a platform to stress the need for increased awareness of the implications of obesity. Increasing access to health education and medical care across the country, especially in the southern states, focusing on managing obesity may help improve infertility.

References
1. “Adult Obesity Prevalence Maps.” Centers for Disease Control and Prevention, 17 Mar. 2023, www.cdc.gov/obesity/data/prevalence-maps.html.
2. Map Gallery, https://data.hrsa.gov/maps/map-gallery.
3. Gambineri, A., Laudisio, D., Marocco, C. et al. Female infertility: which role for obesity?. Int J Obes Supp 9, 65–72 (2019).
https://doi.org/10.1038/s41367-019-0009-1
4. The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1
OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551;
1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196;
Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and
Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2
OD025276. In addition, the All of Us Research Program would not be possible without the partnership of its participants.

Female Infertility And Obesity Across The United States – A Geographic Cross–Sectional Analysis 


Background
The Pennsylvania Rural Health Model (PARHM) is a novel alternative payment model (APM) that began in 2019 and is slated to run through 2024. It is designed to test whether hospital global budgets and transformation plans can improve the financial viability of rural hospitals and the health of their patients. The expectation is that, when hospitals operate on a prospective budget, they have an incentive to reduce potentially avoidable hospitalizations (PAH) to control costs. Therefore, our objective was to assess the early impacts of PARHM on PAH for ambulatory care sensitive conditions.

Methods
We conducted a retrospective cohort study using a difference-in-differences (DID) with multiple time periods approach. Hospitals joined PARHM in three cohorts at different points in time (January 2019, 2020, and 2021), creating a natural policy experiment to study this program’s effects. The treated group included HSAs of 18 treated hospitals and the control group included HSAs of 43 eligible but not participating hospitals. We used visit-level inpatient discharge data from the Pennsylvania Health Care Cost Containment Council between 1/1/2016 and 5/31/2022. We measured PAH using the Agency for Healthcare Research and Quality Prevention Quality Indicators algorithm. Analyses were conducted at the hospital service area (HSA)-quarter level. We fit models using a doubly robust DID estimator that accounted for staggered treatment timing. All models were weighted using propensity scores and population size in each HSA.

Results
The introduction of PARHM was associated with 9.71 fewer PAHs per 100k residents per quarter (95% CI: 0.21 to 19.21) overall. This represents a 2.25% relative reduction in treated vs. control HSAs. However, when cohorts were analyzed separately, only PARHM Cohort 1 HSAs consistently a showed statistically significant (p<0.05) relative decreases in PAHs across overall, acute, chronic, and diabetes composite measures for PAH compared to changes in the control group. Results were similar across sensitivity and subgroup analyses.

Conclusion
Our findings on the early impacts of PARHM suggest that it is associated with fewer PAHs. Although, heterogeneous treatment effects by cohort were observed. This study addresses an important gap in the current literature regarding the impact of PARHM on health care utilization. Findings can be used to evaluate the success of PARHM and inform the development and implementation of future APMs across rural settings.

Pennsylvania Rural Health Model: Early Impacts on Potentially Avoidable Hospitalizations

Assessing the healthcare needs of migrants and improving continuity of care through portable health documents

This study aims to explore the relationship between bullying either in school or electronically and substance use including tobacco, alcohol, drugs, marijuana, and electronic vapor product use post-pandemic. Data was taken from the 2021 Youth Risk Behavior Surveillance System (YRBSS), which surveys a representative sample of high school students in grades 9-12 across the United States. Questions related to tobacco use, alcohol use, and drug use were combined into their respective categories. A weighted frequency was obtained to see the frequency of students who used certain substances. An adjusted odds ratio was run to explore the relationship between bullying and substance use (tobacco, alcohol drugs, marijuana, and electronic vapor products) adjusted for age, sex, and race/ethnicity. There were 17232 survey respondents with a representative sample based on age, grade, sex, and race/ethnicity. It was found that bullying was associated with an increased odds of using substances with a statistically significant result. Alcohol was the most frequently used substance. This study showed that the association between bullying and substance use is still a problem post-pandemic. This provides a useful indication for teachers, school administrators, and clinicians to be mindful of when dealing with a child who is a victim of bullying or is using substances.

Association between bullying and substance use: A look at the 2021 YRBSS Data

Background
Differing health outcomes in maternal and child health among communities are the result of a multitude of factors. Despite considerable advancements in women’s reproductive health, social disparities continue to affect the health and well-being of mothers and infants. These racial and socioeconomic disparities become evident especially in medically underserved regions where health providers and resources are few. This study investigated the relationship between race and maternal and infant health outcomes in San Bernardino County compared to Los Angeles and Riverside Counties.

Methods
Public datasets were retrieved from the California Health and Human Services and California Department of Public Health, containing data on the state’s birth and death records and infant health indicators for 2010 to 2021. Only data from San Bernardino (SB), Los Angeles (LA), and Riverside (RS) Counties were included. Within each county, maternal and infant deaths and infant health measures such as birthweight and gestational age were further examined and stratified by race. To compare maternal mortality, a rate of pregnancy-related deaths per 1000 live births was calculated. ANOVA was performed to analyze for differences in maternal and infant mortality and infant health measure rates relative to race among the three counties, with significance level set at 0.05.

Results
Average pregnancy-related deaths in SB, LA, and RS Counties were 124, 300, and 55 per year, respectively, with Hispanics accounting for approximately 50% of maternal deaths across each county. After analyzing pregnancy-related mortality rates, there were significant differences between SB and LA (4.3 vs 2.4, p=0.009) and SB and RS (4.3 vs 2.0, p=0.003) among Hispanics and between SB and LA (8.5 vs 5.1, p=0.04) only among Blacks. Also, SB County had a significantly greater pregnancy-related mortality rate than LA and RS Counties (both p<0.001). Furthermore, SB had higher rates compared to RS for low birthweight (p=0.02), preterm status (p<0.001), and infant mortality (p<0.001). SB also had a higher infant mortality rate compared to LA (p<0.001).

Conclusion
SB County experienced higher rates of pregnancy-related mortality compared with its neighboring counties, with infant mortality and birth complications following a similar trend. Our findings suggest that racial disparities can contribute to health inequity, as predominantly Hispanic and Black communities were adversely affected. Further research is needed to understand the potential social barriers confronting underserved communities in San Bernardino. Identifying the root causes for racial disparities in health outcomes can help guide community health programming and policy-making to address gaps in maternal and infant health.

Examining Disparities in Maternal and Child Health: A Comparative Study of San Bernardino County and Its Neighbors

Background:
Anemia remains a major public health concern, especially in developing countries, despite various public health policies targeted for correction. With this study, the authors aim to underline the need for region-specific policies contrasting the correlates of anemia in non-pregnant females of East and West Uttar Pradesh (UP), India.

Methods:
A detailed secondary data analysis was performed on NFHS-5 data covering the socio-demographic correlates of East and West UP non-pregnant females. Various explanatory variables were tested against the outcome variable of anemia using binary and ordinal logistic regression. For variables whose proportional odds assumptions were not satisfied, binary categorization of the ordinal variables were done.

Results:
The study found a significant difference in correlates of anemia among non-pregnant females of East and West UP on a detailed analysis. The odds of being anemic were higher in women living in rural settings, especially in West UP. Further, in West UP, the odds of being anemic were higher in women who were alcoholics (OR=1.153; p=0.000), having heart disease (OR=1.155; p=0.000), younger, economically weak, illiterate (OR=1.335; p=0.000), or underweight (OR=1.523; p=0.012). While, in East UP, the odds of having anemia were found to be higher among women who were illiterate (OR=1.095, p=0.010), had age of last child ≤48 months (OR=1.296; p=0.000), were currently breastfeeding (OR=1.067, p=0.000), were alcoholics (OR=1.155, p=0.000), were hypertensive (OR=1.502, p=0.000) or were underweight (OR=1.523; p=0.012).

Conclusion:
In line with the demographic differences between East and West UP, a stark difference exists in socio-epidemiological correlates of anemia between both regions, and a blanket public health policy is not enough. In the age of precision medicine, we must evolve to a “Precision Public Policy” tailored specifically towards the regions allowing better implementation and outcomes.

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Attitudes toward Remote Medical Education at an Urban Allopathic Medical School During the COVID-19 Pandemic

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Closing the Gap in Medical Student Counseling: A Virtual Curriculum

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