The Correlation Between Perceptions of Safety and Perceived Stress Among Residents of the Somerset Neighborhood of Kensington, Philadelphia

Background: The Somerset neighborhood of Kensington, Philadelphia is affected by economic, environmental, and social issues that come with disinvestment. The average median income for Somerset is $26,015 per year which is much lower than Philadelphia’s city-wide income of$36, 957. This study evaluated the connection between perceptions of safety and perceived stress among residents of the Somerset neighborhood. Methods: This study was a secondary data analysis from a cross-sectional study in the Somerset neighborhood. The data included self-reported surveys from Somerset residents that were completed at their homes. The surveys were completed using an electronic (tablet) format which took approximately 20 to 30 minutes to complete. Trained members of the neighborhood collected the data from July to December 2017. We used SPSS to quantify relationships between perceptions of safety and perceived stress using Spearman’s Rank Order Correlation for each of our 12 perceptions of safety variables and stress. Our final model was created using a multivariable linear regression model. Results: We had 328 adults with an average age of 48 years old in our study sample. We found that most of the residents were female, 35.3% were Latino, predominantly single, and mainly employed full-time. Additionally, over half of the residents owned their home and 16 years was the average amount of time lived in the neighborhood. We found that the average score on the stress scale was a 5.18 (range 0-16). In our final model, we found 4 variables to be statistically significant (α= .10) age, years lived in the community, police should spend more time working with community members and groups to solve problems, and members of my community are interested in crime prevention activities. Discussion: Overall, the mean stress levels were lower than we expected. We found associations between demographics and perceptions of safety variables specifically, as age increased, stress decreased and as the years lived in the community increased, stress increased. Our results also indicated as police spent more time working with community members and as crime prevention activities increased in the community, stress decreased. The strongest predictor of stress was the variable: “police should spend more time working with community members and groups to solve problems.” Collaborations between police officers and community members have the potential to improve health and may also help residents feel safer and less stressed in the neighborhood

The Association Between Opioid-Related Industry Payments and Opioid Prescribing at the Individual and Ecological Level in Pennsylvania

Objective: to understand how industry payments related to opioid products are associated with opioid prescribing in Pennsylvania. Methods: we merged the Open Payments data, Medicare Part D public use file, and Dartmouth Hospital Atlas of Health Care Hospital Service Areas from 2015 to analyze relationships between opioid related payments and opioid prescribing. We used a binomial regression model to investigate individual-level trends and a log-linear model to investigate Hospital Service Area-level trends. We mapped the distribution of opioid-related payments in Pennsylvania using GIS software. Results: One additional payment to a physician was associated with 4.2% higher opioid-prescribing rate (OR = 1.0418, 95% CI 1.0416-1.0420, Chi-Square(1) = 122678, p Conclusions: We found a positive association between opioid-related payments to physicians and opioid prescribing. Policy makers and administrators should consider revising rules related to pharmaceutical company marketing tactics and promote judicious opioid prescribing

Understanding Differences in Medical Versus Surgical Patients Alerted by the Modified Early Warning Score (MEWS) at Jefferson Hospital

An Early Warning Score (EWS) is a risk-management tool to identify patients experiencing clinical deterioration early, therefore allowing timely treatment to occur. Although EWS scores are recommended for all in-patients, more data is available for patients under general medical services compared to surgical services. This study aims to understand differences between medical versus surgical in-patients who receive a red alert from the Modified Early Warning Score (MEWS) at Jefferson hospital. Patients who received a red MEWS alert during admission and discharged between June 2017 to March 2018 (N=812) were categorized as medical or surgical patients. Patient characteristics were compared using an independent samples t-test (age, alert count) or chi-square test (sex, race, admission source, insurance). Patient outcomes were compared using a binary logistic regression (in-hospital mortality, RRT, sepsis diagnosis, ICU transfer, intubation, discharge to hospice) or a Cox regression model (length of stay), controlling for age, sex, and race. Compared to medical patients, surgical patients were younger by 2.7 years (p=0.026) and more likely to have a Commercial and/or Medicare category of insurance (OR=1.568, p=0.005). Surgical patients were more likely to have ICU transfer (OR=1.487, p=0.013) and intubation post-alert (OR=2.470, p=0.006), while less likely to be discharged early (HR=0.675,

Predictors of Youth Suicide: A U.S. Survey

Background: The suicide rate in the youth population of the United States has increased by over 50% in the last 10 years. Other countries have markedly reduced suicide rates through investment in research, education and treatment. The United States has been slow in implementing suicide prevention measures and U.S. data on suicide and risk factors remains limited. Objective: The aim of this research is to better understand the risk factors and warning signs for suicide in the youth population. This information could inform the development of prevention strategies to reduce the suicide rate in this population. Methods: Data was collected nationally from survivors of a suicide attempt, the ‘self’ dataset, and family members of those lost to suicide, the ‘other’ dataset. Data were collected on demographics and warning signs observed in 431 individuals aged 8 to 24 years. SAS statistics software was used to generate descriptive statistics and chi-squared tests were performed to compare the warning signs identified by survivors with those identified by family members. Results: The results showed that overall the individuals who had attempted or died from suicide were white (87.24%), male (62.18%), single (50.81%) in school (63.81%) and living at home with their families (85.15%). 80.51% identified as heterosexual and 19.49% as LGBTQ+. Almost a third had made previous suicide attempts (28.77%) and of those 66.94% had made 1 or 2 attempts. 67.52% had ever received psychiatric treatment but, of those, only 53.61% were receiving treatment at the time of the suicide or attempt. 32.71% had a history of suicide in their family and behavior changes were noticed in 59.16% of individuals. Overall the most commonly identified warning signs were emotional misery/pain (45.71%), insomnia (34.75) and hopelessness (34.57%). There were statistically significant differences in prevalence seen between the ‘self’ and ‘other’ datasets in 28 of the 42 warning signs. Conclusions: This research provides an overview of the most at-risk individuals in the youth population. It highlights that warning signs are not easy to identify in others so if there are concerns about an individual, conversations must be had to ascertain their mental state and provide help as needed. More research is needed to further evaluate and understand this topic

Normalized Healthcare Utilization Among Refugees Resettled in Philadelphia, 2007-2016

Background/Purpose: About 70,000 new refugees are resettled in the United States each year, of which approximately 600 are resettled in Philadelphia. This project seeks to better understand the patterns of healthcare utilization, including primary care, emergency, and hospitalization, among refugees resettled in Philadelphia, PA, between 2007 and 2016. Methods: Demographic and healthcare utilization data for 1,144 refugees seen at Jefferson Family Medical Associates were compiled from the Jefferson Longitudinal Refugee Health Registry. Descriptive statistics were used to describe the demographic characteristics of the refugee population. Negative binomial count regressions were used to test for significant correlations between major demographic variables and healthcare utilization. Results: Refugees had an average of 7.24 (SD = 9.35) and a median of 4 primary care visits. Visits rates were highest during the first eight months post resettlement and declined significantly after expiration of Refugee Medical Assistance. Country of origin and year of arrival were significantly associated with differing rates of healthcare utilization. Discussion: Overall, refugees utilized primary healthcare services at a slightly higher rate than the U.S. average. There are differences in utilization among various sub-populations within the refugee community. Future studies should further explore these differences in healthcare utilization patterns among recently resettled refugees

Challenges of Screening for Prostate Cancer: A Secondary Analysis Using HINTS Data

Prostate cancer is the second most common cancer among men after skin cancer; as well as being the third leading cause of death from cancer among men. The U.S. preventative services task force recommends that clinicians inform men ages 55 – 69 years of age about the potential benefits and harms associated with prostate cancer screening, specifically prostate-specific antigen (PSA) testing. This study was a secondary data analysis of the National Cancer Institute’s Health Information National Trends Survey or HINTS which includes national and regional data addressing factors associated with take-up of PSA screening. Survey respondents included 1500 men, mean age 59 (± 13.5) years, 75.2% self-identified as white and 40.2% reported having a college degree or higher. Analysis of these data revealed that men who have a college degree or higher were more likely to, have had a PSA test and to have been offered a PSA test by a healthcare provider. Additionally, men with a college education or higher were more likely to report understanding the efficacy of the PSA test when compared to high school graduates (OR = 2.82). Black males were less likely to receive a PSA test, been offered a PSA test by a healthcare provider, or report understanding the efficacy of the test when compared to their white counterparts (OR = 0.66). These finding can inform targeted interventions to increase appropriate use of PSA testing

Sleep Deprivation as a Treatment for Depression: Comparison of mood ratings and improving prediction of treatment response

Major Depressive Disorder (MDD), a major contributor to disability and disease burden, is a critical public health issue. Typical treatments for MDD include pharmacotherapy and office-based therapy. However, fewer than 60% of those with MDD respond to a single course of these treatments, and the relapse rate is nearly 50%. In contrast, acute sleep deprivation therapy (SD) yields an antidepressant effect in \u3c 24 hours with comparable response rates. Clinical practice has not widely adopted the use of SD due in-part to its transient effects and inconvenience to patients. This study examined the utility self-administered baseline PANAS, POMS-SF, and VAS mood measures and baseline demographics to predict a participant’s response to SD. Depressed participants (N = 37) underwent ~36 hr of sleep deprivation. An antidepressant response was defined as a ≥ 30% decrease in HDRS-NOW score from baseline to post-sleep deprivation. Odds ratios of experiencing a response were calculated utilizing univariate binary logistic regression. 64% (n = 23) of participants responded to SD. Identifying as white OR = 5.14, p = .030, 95% CI [1.19, 22.48], being employed OR = 4.53, p = .042, 95% CI [1.06, 19.41], and greater scores on the baseline PANAS positive affect scale OR = 1.30, p = .010, 95% CI [ 1.07, 1.59], were significantly associated with the odds of experiencing an antidepressant response to SD. To our knowledge, the PANAS positive affect scale has not been previously identified as a predictor of response to SD. The results of this research may be utilized to inform and ease screening for this treatment modality in the clinical and research settings

Time to Relapse after Epilepsy Surgery as a Predictor of Future Seizures

Epilepsy affects more than 50 million people worldwide. Refractory epilepsy, defined as failure to respond to two anti-epileptic medications, is often considered for surgery. 30-50% of those who undergo surgery experience seizures after their procedure. Those who experience a seizure following surgery may benefit from prognostic information to determine when subsequent seizures will occur. This knowledge may inform best practices with respect to further surgeries or pharmacologic intervention, thus improving tertiary prevention and public health. Current literature uses the length of time between surgery and the first post-surgery seizure (seizure latency) to predict the long-term outcome of the patient. This study uses seizure latency to examine short-term outcomes and identify the timing of the second and third seizure after surgery. Data was used from a retrospective database at Thomas Jefferson University Hospital’s Comprehensive Epilepsy Center that has been maintained since 1986. Records were initially stratified into temporal (N = 943) and extratemporal (N = 125) surgeries. Statistical analyses were done using SAS software and utilized a Cox proportional hazards model while controlling for demographics and clinical factors. Generally, as seizure latency increased, the time between the first seizure recurrence and subsequent seizures increased. These results were statistical meaningful in the temporal group (First-to-Second Analysis: Wald Chi Square: 39.85, df = 5,