This study reviewed 395 young adults, 18–35 year-old, admitted for COVID-19 to one of the eleven hospitals in New York City public health system. Demographics, comorbidities, clinical course, outcomes and characteristics linked to hospitalization were analyzed including temporal survival analysis. Fifty-seven percent of patients had a least one major comorbidity. Mortality without comorbidity was in 3.8% patients. Further investigation of admission features and medical history was conducted. Comorbidities associated with mortality were diabetes (n = 54 deceased/73 diagnosed,74% tested POS;98.2% with diabetic history deceased; Wilcoxon p (Wp) = .044), hypertension (14/44,32% POS, 25.5%; Wp = 0.030), renal (6/16, 37.5% POS,11%; Wp = 0.000), and cardiac (6/21, 28.6% POS,11%; Wp = 0.015). Kaplan survival plots were statistically significant for these four indicators. Data suggested glucose >215 or hemoglobin A1c >9.5 for young adults on admission was associated with increased mortality. Clinically documented respiratory distress on admission was statistically significant outcome related to mortality (X2 = 236.6842, df = 1, p < .0001). Overall, 28.9% required supportive oxygen beyond nasal cannula. Nasal cannula oxygen alone was required for 71.1%, who all lived. Non-invasive ventilation was required for 7.8%, and invasive mechanical ventilation 21.0% (in which 7.3% lived, 13.7% died). Temporal survival analysis demonstrated statistically significant response for Time to Death <10 days (X2 = 18.508, df = 1, p = .000); risk lessened considerably for 21 day cut off (X2 = 3.464, df = 1, p = .063), followed by 31 or more days of hospitalization (X2 = 2.212, df = 1, p = .137).

Background:The siloed delivery of oral and medical health care in the United States has contributed to a lack of awareness of the consequences of poor oral health and has hampered effective interprofessional education and collaboration. The aim of this study was to assess the knowledge and practice behaviors of primary care medical providers in an urban safety-net hospital regarding collaboration with dentists and integration of oral health into overall health-care delivery. Methods: A 36-item survey was designed in a web-based platform (Survey Monkey ® ) and electronically distributed in September 2020 to 181 primary care medical providers (physicians, nurses, physician assistants) within a municipal hospital in the Bronx, New York. The questionnaire included sections on demographics, current practices, oral health knowledge, and opinions regarding interprofessional collaboration. Descriptive statistics and bivariate analyses using the chi-square and Fisher's exact test were performed with a significance level of 0.05. Results: The response rate was 66% (119 respondents). The vast majority (80%) reported little or no training in oral health and 85% reported no team experience with oral health professionals. Medical providers' confidence in examining the oral cavity was positively associated with previous additional training (p = 0.001) and with team experience (p = 0.005). The two most commonly reported barriers to willingness to collaborate were lack of formal relationships with dental providers (74%) and competing priorities (69%). Conclusion: Overall, there is very limited awareness and integration of oral health into the clinical practice of medical providers at this safety-net hospital. However, those providers with previous training and team experience had greater oral health confidence. Given the critical importance of oral health to overall health, increased efforts should be directed to further educate and train medical providers and address barriers to interprofessional care.

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Background The Promoting Excellence and Reflective Learning in Simulation (PEARLS) Healthcare Debriefing Tool is a cognitive aid designed to deploy debriefing in a structured way. The tool has the potential to increase the facilitator’s ability to acquire debriefing skills, by breaking down the complexity of debriefing and thereby improving the quality of a novice facilitator’s debrief. In this pilot study, we aimed to evaluate the impact of the tool on facilitators’ cognitive load, workload, and debriefing quality. Methods Fourteen fellows from the New York City Health + Hospitals Simulation Fellowship, novice to the PEARLS Healthcare Debriefing Tool, were randomized to two groups of 7. The intervention group was equipped with the cognitive aid while the control group did not use the tool. Both groups had undergone an 8-h debriefing course. The two groups performed debriefings of 3 videoed simulated events and rated the cognitive load and workload of their experience using the Paas-Merriënboer scale and the raw National Aeronautics and Space Administration task load index (NASA-TLX), respectively. The debriefing performances were then rated using the Debriefing Assessment for Simulation in Healthcare (DASH) for debriefing quality. Measures of cognitive load were measured as Paas-Merriënboer scale and compared using Wilcoxon rank-sum tests. Measures of workload and debriefing quality were analyzed using mixed-effect linear regression models. Results Those who used the tool had significantly lower median scores in cognitive load in 2 out of the 3 debriefings (median score with tool vs no tool: scenario A 6 vs 6, p=0.1331; scenario B: 5 vs 6, p=0.043; and scenario C: 5 vs 7, p=0.031). No difference was detected in the tool effectiveness in decreasing composite score of workload demands (mean difference in average NASA-TLX −4.5, 95%CI −16.5 to 7.0, p=0.456) or improving composite scores of debriefing qualities (mean difference in DASH 2.4, 95%CI −3.4 to 8.1, p=0.436). Conclusions The PEARLS Healthcare Debriefing Tool may serve as an educational adjunct for debriefing skill acquisition. The use of a debriefing cognitive aid may decrease the cognitive load of debriefing but did not suggest an impact on the workload or quality of debriefing in novice debriefers. Further research is recommended to study the efficacy of the cognitive aid beyond this pilot; however, the design of this research may serve as a model for future exploration of the quality of debriefing.

Introduction: In the initial pandemic regional differences may have existed in COVID-19 hospitalizations and patient outcomes in New York City. Whether these patterns were present in public hospitals is unknown. The aim of this brief study was to investigate COVID-19 hospitalizations and outcomes in the public health system during the initial pandemic response.Methods: A retrospective review was conducted on COVID-19 admissions in New York City public hospitals during the exponential phase of the pandemic. All data were collected from an integrated electronic medical records system (Epic Health Systems, Verona, WI). Overall, 5,422 patients with at least one admission each for COVID-19 were reviewed, with a study of demographic characteristics (including age, gender, race, BMI), pregnancy status, comorbidities, facility activity, and outcomes. Data related to hospitalization and mortality trends were also collected from City of New York website. These data often involved more than one facility and/or service line resulting in more location or treatment facility counts than patients due to utilization of services at more than one location and transfers between locations and facilities.Results: Higher mortality was associated with increasing age with the highest death rate (51.9%) noted in the age group &gt;75 years (OR 7.88, 95%CI 6.32–10.08). Comorbidities with higher mortality included diabetes (OR 1.5, 95% CI 1.33–1.70), hypertension (OR 1.62, 95% CI 1.44–1.83), cardiovascular conditions (OR 1.66, 95% CI 1.47–1.87), COPD (OR 1.86, 95% CI 1.39–2.50). It was deduced that 20% of all New York City COVID-19 positive admissions were in public health system during this timeframe. A high proportion of admissions (21.26%) and deaths (19.93%) were at Elmhurst Hospital in Queens. Bellevue and Metropolitan Hospitals had the lowest number of deaths, both in borough of Manhattan. Mortality in public hospitals in Brooklyn was 29.9%, Queens 28.1%, Manhattan 20.4%.Conclusion: Significant variations existed in COVID-19 hospitalizations and outcomes in the public health system in New York City during the initial pandemic. Although outcomes are worse with older age and those with comorbidities, variations in hospitals and boroughs outside of Manhattan are targets to investigate and strategize efforts.