Purpose: Develop and validate simple risk scores based on initial clinical data and no or minimal laboratory testing to predict mortality in hospitalized adults with COVID-19.Methods: We gathered clinical and initial laboratory variables on consecutive inpatients with COVID-19 who had either died or been discharged alive at 6 US health centers. Logistic regression was used to develop a predictive model using no laboratory values (COVID-NoLab) and one adding tests available in many outpatient settings (COVID-SimpleLab). The models were converted to point scores and their accuracy evaluated in an internal validation group.Results: We identified 1340 adult inpatients with complete data for nonlaboratory parameters and 741 with complete data for white blood cell (WBC) count, differential, c-reactive protein (CRP), and serum creatinine. The COVID-NoLab risk score includes age, respiratory rate, and oxygen saturation and identified risk groups with 0.8%, 11.4%, and 40.4% mortality in the validation group (AUROCC = 0.803). The COVID-SimpleLab score includes age, respiratory rate, oxygen saturation, WBC, CRP, serum creatinine, and comorbid asthma and identified risk groups with 1.0%, 9.1%, and 29.3% mortality in the validation group (AUROCC = 0.833).Conclusions: Because they use simple, readily available predictors, developed risk scores have potential applicability in the outpatient setting but require prospective validation before use. ( J Am Board Fam Med 2021;34:S127-S135.

IntroductionSeveral prior studies have examined the impact of learners (medical students or residents) on overall emergency department (ED) flow as well as the impact of resident training level on the number of patients seen by residents per hour. No study to date has specifically examined the impact of learners on emergency medicine (EM) attending physician productivity, with regards to patients per hour (PPH). We sought to evaluate whether learners increase, decrease, or have no effect on the productivity of EM attending physicians in a teaching program with one student or resident per attending.MethodsThis was a retrospective database review of an urban, academic tertiary care center with 3 separate teams on the acute care side of the ED. Each team was staffed with one attending physician paired with either one resident, one medical student or with no learners. All shifts from July 1, 2008 to June 30, 2010 were reviewed using an electronic database. We predefined a shift as “Resident” if > 5 patients were seen by a resident, “Medical Student” if any patients were seen by a medical student, and “No Learners” if no patients were seen by a medical student or resident. Shifts were removed from analysis if more than one learner saw patients during the shift. We further stratified resident shifts by EM training level or off-service rotator. For each type of shift, the total number of patients seen by the attending physician was then divided by 8 hours (shift duration) to arrive at number of patients per hour.ResultsWe analyzed a total of 7,360 shifts with 2,778 removed due to multiple learners on a team. For the 2,199 shifts with attending physicians with no learners, the average number of PPH was 1.87(95% confidence interval [CI] 1.86,1.89). For the 514 medical student shifts, the average PPH was 1.87(95% CI 1.84,1.90), p = 0.99 compared with attending with no learner. For the 1,935 resident shifts, the average PPH was 1.99(95% CI 1.97,2.00). Compared with attending physician with no learner, attending physicians with a resident saw more PPH (1.99 vs 1.87, p<0.005). There was no statistically significant difference found between EM1: 1.98PPH, EM2: 1.99PPH, EM3: 1.99PPH, and off-service rotators: 1.99PPH.ConclusionEM attending physicians paired with a resident in a one-on-one teaching model saw statistically significantly more patients per hour (0.12 more patients per hour) than EM attending physicians alone. EM attending physicians paired with a medical student saw the same number of patients per hour compared with working alone.

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IntroductionVariability in the use of computed tomography (CT) between providers in the emergency department (ED) suggests that CT is ordered on a provider rather than a patient level. We aimed to evaluate the variability of CT ordering practices for non-traumatic abdominal pain (NTAP) across physicians in the ED using patient-visit and physician-level factors.MethodsWe conducted a retrospective study among 6,409 ED visits for NTAP from January 1 to December 31, 2012, at a large, urban, academic, tertiary-care hospital. We used a two-level hierarchical logistic regression model to estimate inter-physician variation. Intraclass correlation coefficient (ICC) was calculated.ResultsThe hierarchical logistic regression analyses showed that patient-visit factors including younger age, arrival mode by ambulance, prior CT, >79 ED arrivals in the previous four hours, and ultrasound had statistically significant negative associations with physician CT ordering, while surgical team admission and white blood count (WBC) >12.5 K/millimeter cubed (mm3) had statistically significant positive associations with physician CT ordering. With physician-level factors, only physicians with >21 years experience after medical school graduation showed statistical significance negatively associated with physician CT ordering. Our data demonstrated increased CT ordering from the mean in only one out of 43 providers (2.3%), which indicated limited variation across physicians to order CT. After adjusting for patient-visit and physician-level factors, the calculated ICC was 1.46%.ConclusionWe found minimal physician variability in CT ordering practices for NTAP. Patient-visit factors such as age, arrival mode, admission team, prior CT, ED arrivals in previous four hours, ultrasound, and WBC count were found to largely influence CT ordering practices.

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Objectives As students on an emergency medicine (EM) rotation work with different faculty on a daily basis, EM clerkships often incorporate an end‐of‐shift evaluation to capture sufficient student performance data. Electronic shift evaluations have been shown to increase faculty completion compliance. This study aimed to examine learner perceptions of their individualized feedback during an EM clerkship following the adoption of an electronic evaluation tool. Methods This retrospective study examined end‐of‐rotation surveys that students complete at the conclusion of their EM rotation. Survey respondents used a standard Likert scale (1–5). This study examined responses to the question: “The feedback I received on this rotation was adequate.” The study period included the 3 academic years prior to and subsequent to the adoption of an electronic evaluation system (replacing paper end‐of‐shift evaluations). The primary outcome was the mean Likert score and the secondary outcome was the percentage of students who rated their feedback a “5” or “strongly agree.” Results A total of 491 students responded (83.9% response rate) to the survey during the paper evaluation period, while 427 responded (80.7% response rate) in the electronic period. The mean response improved from 4.02 (paper evaluations) to 4.22 (electronic evaluations; mean difference = 0.20, p < 0.05). The percentage of students who responded with a 5 improved (31% with paper evaluations vs. 41% with electronic evaluations, p < 0.05). Conclusions The adoption of an electronic end‐of‐shift evaluation system was associated with improved learner perception of their feedback as compared to paper evaluations. Electronic evaluations are a useful tool to gather just‐in‐time data on learner performance.

District of Columbia * † physician coverage. Those that do not alter EM attending physician coverage based on presence or absence of learners (medical students or resident physicians) may have varying Introduction: Several prior studies have examined the impact of learners (medical students or residents) on overall emergency department (ED) flow as well as the impact of resident training level on the number of patients seen by residents per hour. No study to date has specifically examined the impact of learners on emergency medicine (EM) attending physician productivity, with regards to patients per hour (PPH). We sought to evaluate whether learners increase, decrease, or have no effect on the productivity of EM attending physicians in a teaching program with one student or resident per attending.