Using live stream technology to conduct workplace observation assessment of trainee dental nurses: an evaluation of effectiveness and user experience.

AIM/OBJECTIVE: This study evaluates the effectiveness and users' experience of using live stream technology to conduct workplace observation assessments of trainee dental nurses. Information on the usability, accessibility, and general satisfaction of this technological technique were collected. MATERIALS AND METHODS: This nationwide cross-sectional survey was conducted in Scotland and included one focus group and three online questionnaires with qualitative and quantitative questions. The quantitative responses were described using standard descriptive analysis, while the quantitative data were investigated using thematic analysis. RESULTS: Eighty-one trainee dental nurses, 35 clinicians and 19 assessors participated in this study. Live stream observation was generally well received by the trainee dental nurses and clinicians, who thought that it had helped increase their confidence to perform practical skills. The assessors also stated that overall satisfaction was high, and that live stream observation met their expectations for efficacy. However, several technical challenges, such as network issues were brought up by responders. CONCLUSION: This study provides evidence that workplace observation assessments can be performed in the future by using live stream technology. However, additional investigation and comparison will aid in determining the most effective way of using this approach and providing feedback to promote learning among dental trainees.

Universal admission laboratory screening for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) asymptomatic infection across a large health system.

BACKGROUND: Admission laboratory screening for asymptomatic coronavirus disease 2019 (COVID-19) has been utilized to mitigate healthcare-associated severe acute respiratory coronavirus virus 2 (SARS-CoV-2) transmission. An understanding of the impact of such testing across a variety of patient populations is needed. METHODS: SARS-CoV-2 nucleic acid amplification admission testing results for all asymptomatic patients across 4 distinct inpatient facilities between April 20, 2020, and June 14, 2021, were analyzed. Positivity rates and the number needed to test (NNT) to identify 1 asymptomatic infected patient were calculated. Admission results were compared to COVID-19 community incidence rates for the system's surrounding metropolitan service area. Using a national survey of hospital epidemiologists, a clinically meaningful NNT of 1:100 was identified. RESULTS: In total, 51,187 tests were collected (positivity rate, 1.8%). During periods of high transmission, the NNT met the clinically relevant threshold in all populations. The NNT approached or met the threshold for most locations during periods of lower transmission. For all transmission levels, the NNT for fully vaccinated patients did not meet the threshold. CONCLUSIONS: Implementing an asymptomatic patient admission testing program can provide clinically relevant data based on the NNT, even during periods of lower transmission and among different patient populations. Limiting admission testing to non-fully vaccinated patients during periods of lower transmission may be a strategy to address resource concerns around this practice. Although the impact of such testing on healthcare-associated COVID-19 among patients and healthcare workers could not be clearly determined, these data provide important information as facilities weigh the costs and benefits of such testing.

Development and implementation of the National Heart, Lung, and Blood Institute COVID-19 common data elements.

Background: Coronavirus Disease 2019 (COVID-19) instigated a flurry of clinical research activity. The unprecedented pace with which trials were launched left an early void in data standardization, limiting the potential for subsequent data pooling. To facilitate data standardization across emerging studies, the National Heart, Lung, and Blood Institute (NHLBI) charged two groups with harmonizing data collection, and these groups collaborated to create a concise set of COVID-19 Common Data Elements (CDEs) for clinical research. Methods: Our iterative approach followed three guiding principles: 1) draw from existing multi-center COVID-19 clinical trials as precedents, 2) incorporate existing data elements and data standards whenever possible, and 3) alignment to data standards that facilitate data sharing and regulatory submission. We also supported rapid implementation of the CDEs in NHLBI-funded studies and iteratively refined the CDEs based on feedback from those study teams. Results: The NHLBI COVID-19 CDEs are publicly available and being used for current COVID-19 clinical trials. CDEs are organized into domains, and each data element is classified within a three-tiered prioritization system. The CDE manual is hosted publicly at https://nhlbi-connects.org/common_data_elements with an accompanying data dictionary and implementation guidance. Conclusions: The NHLBI COVID-19 CDEs are designed to aid data harmonization across studies to achieve the benefits of pooled analyses. We found that organizing CDE development around our three guiding principles focused our efforts and allowed us to adapt as COVID-19 knowledge advanced. As these CDEs continue to evolve, they could be generalized for use in other acute respiratory illnesses.