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Many clinical trials leverage real-world data. Typically, these data are manually abstracted from electronic health records (EHRs) and entered into electronic case report forms (CRFs), a time and labor-intensive process that is also error-prone and may miss information. Automated transfer of data from EHRs to eCRFs has the potential to reduce data abstraction and entry burden as well as improve data quality and safety.
We conducted a test of automated EHR-to-CRF data transfer for 40 participants in a clinical trial of hospitalized COVID-19 patients. We determined which coordinator-entered data could be automated from the EHR (coverage), and the frequency with which the values from the automated EHR feed and values entered by study personnel for the actual study matched exactly (concordance).
The automated EHR feed populated 10,081/11,952 (84%) coordinator-completed values. For fields where both the automation and study personnel provided data, the values matched exactly 89% of the time. Highest concordance was for daily lab results (94%), which also required the most personnel resources (30 minutes per participant). In a detailed analysis of 196 instances where personnel and automation entered values differed, both a study coordinator and a data analyst agreed that 152 (78%) instances were a result of data entry error.
An automated EHR feed has the potential to significantly decrease study personnel effort while improving the accuracy of CRF data.
To determine the incidence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare personnel (HCP) and to assess occupational risks for SARS-CoV-2 infection.
Prospective cohort of healthcare personnel (HCP) followed for 6 months from May through December 2020.
Large academic healthcare system including 4 hospitals and affiliated clinics in Atlanta, Georgia.
HCP, including those with and without direct patient-care activities, working during the coronavirus disease 2019 (COVID-19) pandemic.
Incident SARS-CoV-2 infections were determined through serologic testing for SARS-CoV-2 IgG at enrollment, at 3 months, and at 6 months. HCP completed monthly surveys regarding occupational activities. Multivariable logistic regression was used to identify occupational factors that increased the risk of SARS-CoV-2 infection.
Of the 304 evaluable HCP that were seronegative at enrollment, 26 (9%) seroconverted for SARS-CoV-2 IgG by 6 months. Overall, 219 participants (73%) self-identified as White race, 119 (40%) were nurses, and 121 (40%) worked on inpatient medical-surgical floors. In a multivariable analysis, HCP who identified as Black race were more likely to seroconvert than HCP who identified as White (odds ratio, 4.5; 95% confidence interval, 1.3–14.2). Increased risk for SARS-CoV-2 infection was not identified for any occupational activity, including spending >50% of a typical shift at a patient’s bedside, working in a COVID-19 unit, or performing or being present for aerosol-generating procedures (AGPs).
In our study cohort of HCP working in an academic healthcare system, <10% had evidence of SARS-CoV-2 infection over 6 months. No specific occupational activities were identified as increasing risk for SARS-CoV-2 infection.
To estimate prior severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among skilled nursing facility (SNF) staff in the state of Georgia and to identify risk factors for seropositivity as of fall 2020.
Baseline survey and seroprevalence of the ongoing longitudinal Coronavirus 2019 (COVID-19) Prevention in Nursing Homes study.
The study included 14 SNFs in the state of Georgia.
In total, 792 SNF staff employed or contracted with participating SNFs were included in this study. The analysis included 749 participants with SARS-CoV-2 serostatus results who provided age, sex, and complete survey information.
We estimated unadjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for potential risk factors and SARS-CoV-2 serostatus. We estimated adjusted ORs using a logistic regression model including age, sex, community case rate, SNF resident infection rate, working at other facilities, and job role.
Staff working in high-infection SNFs were twice as likely (unadjusted OR, 2.08; 95% CI, 1.45–3.00) to be seropositive as those in low-infection SNFs. Certified nursing assistants and nurses were 3 times more likely to be seropositive than administrative, pharmacy, or nonresident care staff: unadjusted OR, 2.93 (95% CI, 1.58–5.78) and unadjusted OR, 3.08 (95% CI, 1.66–6.07). Logistic regression yielded similar adjusted ORs.
Working at high-infection SNFs was a risk factor for SARS-CoV-2 seropositivity. Even after accounting for resident infections, certified nursing assistants and nurses had a 3-fold higher risk of SARS-CoV-2 seropositivity than nonclinical staff. This knowledge can guide prioritized implementation of safer ways for caregivers to provide necessary care to SNF residents.
Among 353 healthcare personnel in a longitudinal cohort in 4 hospitals in Atlanta, Georgia (May–June 2020), 23 (6.5%) had severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies. Spending >50% of a typical shift at the bedside (OR, 3.4; 95% CI, 1.2–10.5) and black race (OR, 8.4; 95% CI, 2.7–27.4) were associated with SARS-CoV-2 seropositivity.
The recording and analysis of a burnt mound and adjacent palaeochannel deposits on the floodplain of the River Soar in Leicestershire revealed that the burnt mound was in use, possibly for a number of different purposes, at the transition from the Neolithic to the Bronze Age. An extensive radiocarbon dating programme indicated that the site was revisited. Human remains from the palaeochannel comprised the remains of three individuals, two of whom pre-dated the burnt mound by several centuries while the partial remains of a third, dating from the Late Bronze Age, provided evidence that this individual had met a violent death. These finds, along with animal bones dating to the Iron Age, and the remains of a bridge from the early medieval period, suggest that people were drawn to this location over a long period of time.
Although the origins of domestic animals have been well-documented, it is unclear when livestock were first exploited for secondary products, such as milk. The analysis of remnant fats preserved in ceramic vessels from two agricultural sites in central and eastern Europe dating to the Early Neolithic (5900-5500 cal BC) are best explained by the presence of milk residues. On this basis, the authors suggest that dairying featured in early European farming economies. The evidence is evaluated in the light of analysis of faunal remains from this region to determine the scale of dairying. It is suggested that dairying—perhaps of sheep or goats—was initially practised on a small scale and was part of a broad mixed economy.
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