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

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. Observational retrospective study. Tertiary University Hospital "Spedali Civili" Hospital, Brescia, Italy. Workers (most of whom are healthcare workers) employed at the hospital. The information collected by the DDGS was transferred to the IBM SPSS statistical software package and then statistically analyzed. 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. 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.