Quality improvement (QI) and patient safety are essential to the practice of medicine. Specific training in these fields has become a requirement in graduate medical education, although there is great variation in how residency programs choose to approach trainee education in QI and patient safety. Residents have a unique vantage point into the operations of a health care system and can guide the development of system improvement initiatives. In this report, we (1) describe the context that led to the creation of a pediatric resident safety council (PRSC) in its current structure, (2) identify the organizational features implemented to best meet the objectives of this council, and (3) describe the local and institutional impact of the PRSC. A PRSC is a useful model to build resident engagement in safe and high-quality patient care within a residency program and health care system. A PRSC encourages the professional development of future pediatric safety leaders and facilitates experiential training in patient safety and QI science.Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be diagnosed by PCR during acute infection or later in their clinical course by detection of virus-specific antibodies. While in theory complementary, both PCR and serologic tests have practical shortcomings. A retrospective study was performed in order to further define these limitations in a clinical context and to determine how to best utilize these tests in a coherent fashion. A total of 3,075 patients underwent both PCR and serology tests at University of California, Los Angeles (UCLA), in the study period. Among these, 2,731 (89%) had no positive tests at all, 73 (2%) had a positive PCR test and only negative serology tests, 144 (5%) had a positive serology test and only negative PCR tests, and 127 (4%) had positive PCR and serology tests. Approximately half of the patients with discordant results (i.e., PCR positive and serology negative or vice versa) had mistimed tests in reference to the course of their disease. PCR-positive patients who were asymptomatic or pregnant were less likely to generate a detectable humoral immune response to SARS-CoV-2. On a quantitative level, the log number of days between symptom onset and PCR test was positively correlated with cycle threshold (CT) values. However, there was no apparent relationship between PCR CT and serologic (arbitrary units per milliliter) results.Diagnostic assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are essential for patient management, infection prevention, and the public health response for coronavirus disease 2019 (COVID-19). The efficacy and reliability of these assays are of paramount importance in both tracking and controlling the spread of the virus. Real-time reverse transcription-PCR (RT-PCR) assays rely on a fixed genetic sequence for primer and probe binding. Mutations can potentially alter the accuracy of these assays and lead to unpredictable analytical performance characteristics and false-negative results. Here, we identify a G-to-U transversion (nucleotide 26372) in the SARS-CoV-2 E gene in three specimens with reduced viral detection efficiency using a widely available commercial assay. Further analysis of the public GISAID repository led to the identification of 18 additional genomes with this mutation, which reflect five independent mutational events. This work supports the use of dual-target assays to reduce the number of false-negative PCR results.We assessed the performance of the CoronaCHEK lateral flow assay on samples from Uganda and Baltimore to determine the impact of geographic origin on assay performance. Plasma samples from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-positive individuals (Uganda, 78 samples from 78 individuals, and Baltimore, 266 samples from 38 individuals) and from prepandemic individuals (Uganda, 1,077, and Baltimore, 532) were evaluated. Prevalence ratios (PR) were calculated to identify factors associated with a false-positive test. After the first positive PCR in Ugandan samples, the sensitivity was 45% (95% confidence interval [CI], 24,68) at 0 to 7 days, 79% (95% CI, 64 to 91) at 8 to 14 days, and 76% (95% CI, 50 to 93) at >15 days. selleck products In samples from Baltimore, sensitivity was 39% (95% CI, 30 to 49) at 0 to 7 days, 86% (95% CI, 79 to 92) at 8 to 14 days, and 100% (95% CI, 89 to 100) at 15 days after positive PCR. The specificity of 96.5% (95% CI, 97.5 to 95.2) in Ugandan samples was significantly lower than that in samples from Baltimore, 99.3% (95% CI, 98.1 to 99.8; P  less then  0.01). In Ugandan samples, individuals with a false-positive result were more likely to be male (PR, 2.04; 95% CI, 1.03,3.69) or individuals who had had a fever more than a month prior to sample acquisition (PR, 2.87; 95% CI, 1.12 to 7.35). Sensitivity of the CoronaCHEK was similar in samples from Uganda and Baltimore. The specificity was significantly lower in Ugandan samples than in Baltimore samples. False-positive results in Ugandan samples appear to correlate with a recent history of a febrile illness, potentially indicative of a cross-reactive immune response in individuals from East Africa. Bilirubin screening before discharge is performed to identify neonates at risk for future hyperbilirubinemia. The American Academy of Pediatrics recommends using a graph of bilirubin levels by age (the Bhutani Nomogram) to guide follow-up and a different graph to determine phototherapy recommendations. Our objective was to evaluate predictive models that incorporate the difference between the last total serum bilirubin (TSB) before discharge and the American Academy of Pediatrics phototherapy threshold (Δ-TSB) to predict a postdischarge TSB above the phototherapy threshold by using a single graph. We studied 148 162 infants born at ≥35 weeks' gestation at 11 Kaiser Permanente Northern California facilities from 2012 to 2017 whose TSB did not exceed phototherapy levels and who did not receive phototherapy during the birth hospitalization. We compared 3 logistic models (Δ-TSB; Δ-TSB-Plus, which included additional variables; and the Bhutani Nomogram) by using the area under the receiver operating characteristic curve (AUC) in a 20% validation subset.