Prevalence of Coronavirus Disease 2019 Infection and Outcomes Among Symptomatic Healthcare Workers in Seattle, Washington.

BACKGROUND: Healthcare workers (HCWs) who serve on the front lines of the coronavirus disease 2019 (COVID-19) pandemic have been at increased risk for infection due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in some settings. Healthcare-acquired infection has been reported in similar epidemics, but there are limited data on the prevalence of COVID-19 among HCWs and their associated clinical outcomes in the United States. METHODS: We established 2 high-throughput employee testing centers in Seattle, Washington, with drive-through and walk-through options for symptomatic employees in the University of Washington Medicine system and its affiliated organizations. Using data from these testing centers, we report the prevalence of SARS-CoV-2 infection among symptomatic employees and describe the clinical characteristics and outcomes among employees with COVID-19. RESULTS: Between 12 March 2020 and 23 April 2020, 3477 symptomatic employees were tested for COVID-19 at 2 employee testing centers; 185 (5.3%) employees tested positive for COVID-19. The prevalence of SARS-CoV-2 was similar when comparing frontline HCWs (5.2%) with nonfrontline staff (5.5%). Among 174 positive employees reached for follow-up at least 14 days after diagnosis, 6 reported COVID-related hospitalization; all recovered. CONCLUSIONS: During the study period, we observed that the prevalence of positive SARS-CoV-2 tests among symptomatic HCWs was comparable to that of symptomatic nonfrontline staff. Reliable and rapid access to testing for employees is essential to preserve the health, safety, and availability of the healthcare workforce during this pandemic and to facilitate the rapid return of SARS-CoV-2-negative employees to work.

Christmas and New Year as risk factors for death.

This paper poses three questions: (1) Does mortality from natural causes spike around Christmas and New Year? (2) If so, does this spike exist for all major disease groups or only specialized groups? (3) If twin holiday spikes exist, need this imply that Christmas and New Year are risk factors for death? To answer these questions, we used all official U.S. death certificates, 1979-2004 (n = 57,451,944) in various hospital settings to examine daily mortality levels around Christmas and New Year. We measured the Christmas increase by comparing observed deaths with expected deaths in the week starting on Christmas. The New Year increase was measured similarly. The expected number of deaths was determined by locally weighted regression, given the null hypothesis that mortality is affected by seasons and trend but not by holidays. On Christmas and New Year, mortality from natural causes spikes in dead-on-arrival (DOA) and emergency department (ED) settings. There are more DOA/ED deaths on 12/25, 12/26, and 1/1 than on any other day. In contrast, deaths in non-DOA/ED settings display no holiday spikes. For DOA/ED settings, there are holiday spikes for each of the top five disease groups (circulatory diseases; neoplasms; respiratory diseases; endocrine/nutritional/metabolic diseases; digestive diseases). For all settings combined, there are holiday spikes for most major disease groups and for all demographic groups, except children. In the two weeks starting with Christmas, there is an excess of 42,325 deaths from natural causes above and beyond the normal winter increase. Christmas and New Year appear to be risk factors for deaths from many diseases. We tested nine possible explanations for these risk factors, but further research is needed.

A July spike in fatal medication errors: a possible effect of new medical residents.

BACKGROUND: Each July thousands begin medical residencies and acquire increased responsibility for patient care. Many have suggested that these new medical residents may produce errors and worsen patient outcomes-the so-called "July Effect;" however, we have found no U.S. evidence documenting this effect. OBJECTIVE: Determine whether fatal medication errors spike in July. DESIGN: We examined all U.S. death certificates, 1979-2006 (n = 62,338,584), focusing on medication errors (n = 244,388). We compared the observed number of deaths in July with the number expected, determined by least-squares regression techniques. We compared the July Effect inside versus outside medical institutions. We also compared the July Effect in counties with versus without teaching hospitals. OUTCOME MEASURE: JR = Observed number of July deaths / Expected number of July deaths. RESULTS: Inside medical institutions, in counties containing teaching hospitals, fatal medication errors spiked by 10% in July and in no other month [JR = 1.10 (1.06-1.14)]. In contrast, there was no July spike in counties without teaching hospitals. The greater the concentration of teaching hospitals in a region, the greater the July spike (r = .80; P = .005). These findings held only for medication errors, not for other causes of death. CONCLUSIONS: We found a significant July spike in fatal medication errors inside medical institutions. After assessing competing explanations, we concluded that the July mortality spike results at least partly from changes associated with the arrival of new medical residents.

A steep increase in domestic fatal medication errors with use of alcohol and/or street drugs.

BACKGROUND: Increasingly, medications are consumed outside of clinical settings, with relatively little professional oversight. Despite this trend, previous studies of medication errors have focused on clinical settings. METHODS: We examined all US death certificates from January 1, 1983, to December 31, 2004 (N = 49,586,156), particularly those with fatal medication errors (FMEs) (n = 224,355). We examined trends in 4 types of FMEs that vary according to the relative importance of alcohol/street drugs and the relative likelihood of professional oversight in the consumption of medications. RESULTS: The overall FME death rate increased by 360.5% (1983-2004). This increase far exceeds the increase in death rates from adverse effects of medications (33.2%) or from alcohol and/or street drugs (40.9%). The increase in FMEs varies markedly by type. Type 1 (domestic FMEs combined with alcohol and/or street drugs) shows the largest increase (3196%). In contrast, type 4 (nondomestic FMEs not involving alcohol and/or street drugs) shows the smallest increase (5%). Types 2 and 3 show intermediate increases. Type 2 (domestic FMEs not involving alcohol and/or street drugs) increased by 564%. Type 3 (nondomestic FMEs combined with alcohol and/or street drugs) increased by 555%. Thus, domestic FMEs combined with alcohol and/or street drugs have become an increasingly important health problem compared with other FMEs. CONCLUSIONS: These findings suggest that a shift in the location of medication consumption from clinical to domestic settings is linked to a steep increase in FMEs. It may now be possible to reduce FMEs by focusing not only on clinical settings but also on domestic settings.