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This study describes a novel transfer model implemented between an academic, level 1 trauma center (Hospital A) and a nearby affiliate community hospital (Hospital B). Primary outcome is change in boarding hours and percentage of boarders in the Hospital A emergency department. Secondary objectives of this study include how improved flow in the emergency department to reduce boarding improves length of stay, prevents patients from escalating to more acute acuity levels of care, reduces patient morbidity and mortality and therefore improves health care costs as well. A retrospective chart review was conducted over a consecutive 14-months period of all patients that presented to main hospital emergency department who were transferred to the Hospital B for inpatient admission. This included analysis of patient cohort characteristics, hospital LOS, return rate to the Hospital A (boomerang), rates of against medical advice (AMA) dispositions, post-discharge recidivism, in addition to enterprise data on total number of boarders, percent of boarders, and total boarding hours. There was a total of 718 transfer encounters during the study period. Percent boarding decreased from 70.6% in the pre-period to 63.8% in the post-period (p < 0.001). Total boarding hours decreased at both the main hospital and the sister hospital with this transfer process. The median length of stay at the sister hospital was 74 h, with 9 upgrades to ICU admissions. Five patients were dispositioned back to the hospital A after admission to hospital B. A distributive model was useful in transferring admissions within a healthcare system, reducing number of boarders, percent of boarders, and boarding hours in Hospital A emergency department. Furthermore, the Hospital B was an appropriate location for transfers, based on the low number of ICU transfers and dispositions back to the main hospital. [ABSTRACT FROM AUTHOR]

In his refutation of Marcion, Tertullian argued that Marcion failed to appreciate that Christ, as figured, is present in the Old Testament. Marcion may have similarly denied the presence of Christ, as figured, in the Eucharist. This outcome is expressed in the eucharistic theology of the great eighteenth-century Anglican theologian, Samuel Clarke. Clarke is a harbinger of modern Marcionism because his Old Testament denigration is the product of his specifically Marcionite impulse to excise Christ from the Old Testament. And as he consistently applies this impulse to his eucharistic theology, his memorialism becomes another venue for him to transmit Marcionism to modernity. [ABSTRACT FROM AUTHOR]

International Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD‐10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods. Objective: Compare COVID‐19 cohort manual‐chart‐review and ICD‐10‐based comorbidity data; characterize the accuracy of different methods of extracting ICD‐10‐code‐based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission. Design: Retrospective cross‐sectional study. Measurements: ICD‐10‐based‐data performance characteristics relative to manual‐chart‐review. Results: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79–0.85; comorbidity range: 0.35–0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69–0.76; range: 0.44–0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63–0.71; range: 0.47–0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54–0.63; range: 0.30–0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43–0.53; range: 0.30–0.56). Conclusions and Relevance: ICD‐10‐based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual‐chart‐review. [ABSTRACT FROM AUTHOR]

COVID‐19 has disproportionately affected low‐income communities and people of color. Previous studies demonstrated that race/ethnicity and socioeconomic status (SES) are not independently correlated with COVID‐19 mortality. The purpose of our study is to determine the effect of race/ethnicity and SES on COVID‐19 30‐day mortality in a diverse, Philadelphian population. This is a retrospective cohort study in a single‐center tertiary care hospital in Philadelphia, PA. The study includes adult patients hospitalized with polymerase‐chain‐reaction‐confirmed COVID‐19 between March 1, 2020 and June 6, 2020. The primary outcome was a composite of COVID‐19 death or hospice discharge within 30 days of discharge. The secondary outcome was intensive care unit (ICU) admission. The study included 426 patients: 16.7% died, 3.3% were discharged to hospice, and 20.0% were admitted to the ICU. Using multivariable analysis, race/ethnicity was not associated with the primary nor secondary outcome. In Model 4, age greater than 75 (odds ratio [OR]: 11.01; 95% confidence interval [CI]: 1.96–61.97) and renal disease (OR: 2.78; 95% CI: 1.31–5.90) were associated with higher odds of the composite primary outcome. Living in a "very‐low‐income area" (OR: 0.29; 95% CI: 0.12–0.71) and body mass index (BMI) 30–35 (OR: 0.24; 95% CI: 0.08–0.69) were associated with lower odds of the primary outcome. When controlling for demographics, SES, and comorbidities, race/ethnicity was not independently associated with the composite primary outcome. Very‐low SES, as extrapolated from census‐tract‐level income data, was associated with lower odds of the composite primary outcome. [ABSTRACT FROM AUTHOR]

Research is presented concerning the detection and generation of single flux quantum pulse trains through the use of parameters which are suitable for NbN Josephson junctions. The pulse shape and repetition rate are discussed.