Effectiveness of a digital data gathering system to manage the first pandemic wave among healthcare workers in a main European coronavirus disease 2019 (COVID-19) tertiary-care hospital

Abstract

Abstract Objective: To evaluate the information collected from workers infected with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) or close contacts using a digital data gathering system (DDGS) developed at the onset of the coronavirus disease 2019 (COVID-19) pandemic to better manage the spread of infection at our hospital. Design: Observational retrospective study. Setting: Tertiary University Hospital Spedali Civili Hospital, Brescia, Italy. Participants: Workers (most of whom are healthcare workers) employed at the hospital. Methods: The information collected by the DDGS was transferred to the IBM SPSS statistical software package and then statistically analyzed. Results: Overall, ∼16% of the hospital workforce was infected by SARS-CoV-2 in the first pandemic wave. Nurses were the professional category with the highest infection rate (∼15%). The asymptomatic rate of infection was between 31% and 62%. Positive molecular swabs were significantly more frequent in workers undergoing the test after sending a signaling form to our DDGS. Among workers sending the signaling forms, the information about symptoms was more predictive in terms of risk, compared to the close-contact information. The concordance between molecular swabs and subsequent serological testing was significantly higher in workers signaling their at-risk condition through the DDGS. Conclusions: Overall, our data demonstrate the advantages of a digital system to gather information from workers, which is useful for managing emergencies such as the COVID-19 pandemic. This holds particularly true for large organizations such as hospitals.