Establishing semi-automated infection surveillance in obstetrics and gynaecology.

BACKGROUND: Surveillance is an acknowledged method to decrease nosocomial infections, such as surgical site infections (SSIs). Electronic healthcare records create the opportunity for automated surveillance. While approaches for different types of surgeries and indicators already exist, there are very few for obstetrics and gynaecology. AIM: To analyse the sensitivity and workload reduction of semi-automated surveillance in obstetrics and gynaecology. METHODS: In this retrospective, single-centre study at a 1438-bed tertiary care hospital in Germany, semi-automated SSI surveillance using the indicators 'antibiotic prescription', 'microbiological data' and 'administrative data' (diagnosis codes, readmission, post-hospitalization care) was compared with manual analysis and categorization of all patient files. Breast surgeries (BSs) conducted in 2018 and caesarean sections (CSs) that met the inclusion criteria between May 2013 and December 2019 were included. Indicators were analysed for sensitivity, number of analysed procedures needed to identify one case, and potential workload reduction in detecting SSIs in comparison with the control group. FINDINGS: The reference standard showed nine SSIs in 416 BSs (2.2%). Sensitivities for the indicators 'antibiotic prescription', 'diagnosis code', 'microbiological sample taken', and the combination 'diagnosis code or microbiological sample' were 100%, 88.9%, 66.7% and 100%, respectively. The reference standard showed 54 SSIs in 3438 CSs (1.6%). Sensitivities for the indicators 'collection of microbiological samples', 'diagnosis codes', 'readmission/post-hospitalization care', and the combination of all indicators were 38.9%, 27.8%, 85.2% and 94.4%, respectively. CONCLUSIONS: Semi-automated surveillance systems may reduce workload by maintaining high sensitivity depending on the type of surgery, local circumstances and thorough digitalization.

Inability to work following COVID-19 vaccination-a relevant aspect for future booster vaccinations.

OBJECTIVES: COVID-19 vaccination is a key prevention strategy to reduce the spread and severity of SARS-CoV-2 infections. However, vaccine-related inability to work among healthcare workers (HCWs) could overstrain healthcare systems. STUDY DESIGN: The study presented was conducted as part of the prospective CoVacSer cohort study. METHODS: This study examined sick leave and intake of pro re nata medication after the first, second, and third COVID-19 vaccination in HCWs. Data were collected by using an electronic questionnaire. RESULTS: Among 1704 HCWs enrolled, 595 (34.9%) HCWs were on sick leave following at least one COVID-19 vaccination, leading to a total number of 1550 sick days. Both the absolute sick days and the rate of HCWs on sick leave significantly increased with each subsequent vaccination. Comparing BNT162b2mRNA and mRNA-1273, the difference in sick leave was not significant after the second dose, but mRNA-1273 induced a significantly longer and more frequent sick leave after the third. CONCLUSION: In the light of further COVID-19 infection waves and booster vaccinations, there is a risk of additional staff shortages due to postvaccination inability to work, which could negatively impact the already strained healthcare system and jeopardise patient care. These findings will aid further vaccination campaigns to minimise the impact of staff absences on the healthcare system.