Background Firearm fatalities are a major public health concern, claiming the lives of 40,000 Americans each year. While firearm fatalities have pervasive effects, it is unclear how social determinants of health (SDOH) such as residential racial segregation, income inequality, and community resilience impact firearm fatalities. This study investigates the relationships between these SDOH and the likelihood of firearm fatalities. Methods County-level SDOH data from the Agency for Health Care Research and Quality for 2019 were analyzed, covering 72 Wisconsin counties. The dependent variable was the number of firearm fatalities in each county, used as a continuous variable. The independent variable was residential racial segregation (Dissimilarity Index), defined as the degree to which non-White and White residents were distributed across counties, ranging from 0 (complete integration) to 100 (complete segregation), and higher values indicate greater residential segregation (categorized as low, moderate, and high). Covariates were income inequality ranging from zero (perfect equality) to one (perfect inequality) categorized as low, moderate, and high, community resilience risk factors (low, moderate, and high risks), and rural-urban classifications. Descriptive/summary statistics, unadjusted and adjusted negative binomial regression adjusting for population weight, were performed using STATA/MPv.17.0; P-values ≤ 0.05 were considered statistically significant. ArcMap was used for Geographic Information System analysis. Results In 2019, there were 802 firearm fatalities. The adjusted model demonstrates that the risk of firearm fatalities was higher in areas with high residential racial segregation compared to low-segregated areas (IRR.:1.26, 95% CI:1.04–1.52) and higher in areas with high-income inequality compared to areas with low-income inequality (IRR.:1.18, 95% CI:1.00–1.40). Compared to areas with low-risk community resilience, the risk of firearm fatalities was higher in areas with moderate (IRR.:0.61, 95% CI:0.48–0.78), and in areas with high risk (IRR.:0.53, 95% CI:0.41–0.68). GIS analysis demonstrated that areas with high racial segregation also have high rates of firearm fatalities. Conclusion Areas with high residential racial segregation have a high rate of firearm fatalities. With high income inequality and low community resilience, the likelihood of firearm fatalities increases.

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PURPOSE To examine cancer patients' perspectives on the impact of COVID-19 on teleoncology in Nigeria. METHODS Data from a multicenter survey conducted at 15 outpatient clinics to 1,097 patients with cancer from April and July 2020 were analyzed. The study outcome was telemedicine, defined as patients who reported their routine follow-up visits were converted to virtual visits because of COVID-19 (coded yes/no). Covariates included patient age, ethnicity, marital status, income, cancer treatment, service disruption, and cancer diagnosis/type. Stata/SE.v.17 (StataCorp, College Station, TX) was used to perform chi-square and logistic regression analyses. P values ≤ .05 were considered statistically significant. RESULTS The majority of the 1,097 patients with cancer were female (65.7%) and age 55 years and older (35.0%). Because of COVID-19, 12.6% of patients' routine follow-ups were converted to virtual visits. More patients who canceled/postponed surgery (17.7% v 7.5%; P ≤ .001), radiotherapy (16.9% v 5.3%; P ≤ .001), and chemotherapy (22.8% v 8.5%; P ≤ .001), injection chemotherapy (20.6% v 8.7%; P ≤ .001) and those who reported being seen less by their doctor/nurse (60.3% v 11.4%; P ≤ .001) reported more follow-up conversions to virtual visits. In multivariate analyses, patients seen less by their doctors/nurses were 14.3 times more likely to have their routine follow-ups converted to virtual visits than those who did not (odds ratio, 14.33; 95% CI, 8.36 to 24.58). CONCLUSION COVID-19 caused many patients with cancer in Nigeria to convert visits to a virtual format. These conversions were more common in patients whose surgery, radiotherapy, chemotherapy, and injection chemotherapy treatments were canceled or postponed. Our findings suggest how COVID-19 affects cancer treatment services and the importance of collecting teleoncological care data in Nigeria.

Background In 2013, Marshfield Clinic Health System (MCHS) implemented the Dragon Medical One (DMO) system provided by Nuance Management Center (NMC) for Real-Time Dictation (RTD), embracing the idea of streamlined clinic workflow, reduced dictation hours, and improved documentation legibility. Since then, MCHS has observed a trend of reduced time in documentation, however, the target goal of 100% adoption of voice recognition (VR)-based RTD has not been met. Objective To evaluate the uptake/adoption of VR technology for RTD in MCHS, between 2018–2020. Methods DMO data for 1,373 MCHS providers from 2018–2020 were analyzed. The study outcome was VR uptake, defined as the median number of hours each provider used VR technology to dictate patient information, and classified as no/yes. Covariates included sex, age, US-trained/international medical graduates, trend, specialty, and facility. Descriptive statistics and unadjusted and adjusted logistic regression analyses were performed. Stata/SE.version.17 was used for analyses. P-values less than/equal to 0.05 were considered statistically significant. Results Of the 1,373 MCHS providers, the mean (SD) age was 48.3 (12.4) years. VR uptake was higher than no uptake (72.0% vs. 28.0%). In both unadjusted and adjusted analyses, VR uptake was 4.3 times and 7.7 times higher in 2019–2020 compared to 2018, respectively (OR:4.30,95%CI:2.44–7.46 and AOR:7.74,95%CI:2.51–23.86). VR uptake was 0.5 and 0.6 times lower among US-trained physicians compared to internationally-trained physicians (OR:0.53,95%CI:0.37–0.76 and AOR:0.58,95%CI:0.35–0.97). Uptake was 0.2 times lower among physicians aged 60/above than physicians aged 29/less (OR:0.20,95%CI:0.10–0.59, and AOR:0.17,95%CI:0.27–1.06). Conclusion Since 2018, VR adoption has increased significantly across MCHS. However, it was lower among US-trained physicians than among internationally-trained physicians (although internationally physicians were in minority) and lower among more senior physicians than among younger physicians. These findings provide critical information about VR trends, physician factors, and which providers could benefit from additional training to increase VR adoption in healthcare systems.

Background: Firearm fatalities are a major public health concern, claiming the lives of 40,000 Americans each year. While firearm fatalities affect all, it is unclear how social determinants such as residential segregation affect firearm fatalities. To address this knowledge gap, this study investigates the relationship between residential segregation and the likelihood of firearm fatalities. Methods: Ecological county-level data for 72 Wisconsin counties from the American Community Survey (ACS) were merged with Vital Statistics System mortality records (2015-2019). The study outcome was firearm fatalities, defined as the number of deaths due to firearms per 100,000 population from 2015 to 2019 (used as a continuous variable). The independent variable was residential segregation, using the 2015-2019 ACS-Dissimilarity Index (DI), which measures the degree to which non-white and white residents are distributed across counties and ranges from 0 (complete integration) to 100 (complete segregation), with higher values indicating greater residential segregation. Confounders included income inequality (2015-2019) and community resilience (2019). Poisson regression analyses were conducted using STATA/MP-v.17.0. P-values of ≤0.05 were considered statistically significant. Results: From 2015 to 2019, there were 843 firearm fatalities. Mean (SD) residential segregation was 32.4 (13.1). Bivariate analysis indicates that an increase in residential segregation was significantly associated with increased firearm fatalities (Coef.:0.1,95%CI:0.05-0.06). Adjusted model results indicate that for every increase in residential segregation (by DI), the likelihood of firearm fatalities increased by 0.01% (Coef.:0.01,95%CI:0.007-0.02). Conclusion: Residential segregation, among other social determinants, increases the likelihood of firearm fatalities. This research helps healthcare systems-based practitioners understand how the larger social context influences gun violence disparities.