Seasonal variations of nosocomial infections

Für viele Infektionskrankheiten sind saisonale Schwankungen in der Inzidenz bekannt, aber es ist bisher nicht in großem Umfang und systematisch untersucht worden, ob diese Schwankungen auch bei nosokomialen Infektionen bestehen. Dies ist von Bedeutung, da relevante saisonale Schwankungen bei der Planung von Studien zur Infektionsprävention berücksichtigt werden müssten und zudem eventuell zu saisonalen Anpassungen von Hygienemaßnahmen führen würden. Im Rahmen dieser Untersuchung sollten saisonale Schwankungen in der Inzidenzdichte der wichtigsten nosokomialen Infektionen und ihrer häufigsten Erreger ermittelt werden. Hierzu wurde die Referenzdatenbank der Surveillance- Module für Intensivpatienten (ITS-KISS) und operierte Patienten (OP-KISS) des Krankenhaus-Infektions-Surveillance-Systems (KISS) für den Zeitraum Januar 2000 bis Dezember 2009 analysiert. Die Definition der Jahreszeiten erfolgte anhand von frei verfügbaren Klimadaten des Deutschen Wetterdienstes. Für ITS- KISS wurden Inzidenzdichten (Infektionen/1000 Patiententage) und Inzidenzdichteverhältnisse, für OP-KISS wurden Inzidenzen (Infektionen/100 operierte Patienten) und Relative Risiken, jeweils mit den 95%-Konfidenzintervallen berechnet. In die Analyse gingen 8.680.283 Patiententage und 42.603 Infektionen aus 597 Intensivstationen sowie 767.970 Operationen und 13.586 postoperative Wundinfektionen aus 595 operativen Abteilungen ein. Es wurde gegenüber der Übergangszeit im Frühling/Herbst sowohl eine signifi-kante Zunahme der primären Sepsis im Sommer (Inzidenzdichteverhältnis 1,10 [1,05-1,16]) und eine signifikante Abnahme im Winter (Inzidenzdichteverhältnis 0,89 [0,84-0,94]) als auch eine signifikante Zunahme der Infektionen der unteren Atemwege im Sommer (Inzidenzdichte- verhältnis 1,08 [1,05-1,12]) und eine signifikante Abnahme im Winter (Inzidenzdichteverhältnis 0,96 [0,93-0,999]) festgestellt. Auch im Bereich der postoperativen Wundinfektionen wurde eine signifikante Zunahme im Sommer (Relatives Risiko 1,11 [1,06-1,15]) und eine signifikante Abnahme im Winter (Relatives Risiko 0,95 [0,91-0,99]) ermittelt. Bei den Erregern noso-komialer Infektionen konnten Nonfermenter wie Pseudomonas aeruginosa und Acinetobacter baumannii, Enterobakterien wie Enterobacter spp. und Klebsiella spp. und einige andere Erreger als saisonale Infektionserreger ermittelt werden.For many infectious diseases, seasonal variations in incidence are known, but it has not yet been investigated extensively and systematically whether these variations also exist in nosocomial infections. This is important because seasonal fluctuations should be considered relevant in the planning of studies on infection control and may result in seasonal adjustments of infection control measures. This study was performed in order to determine seasonal variations in the incidence density of nosocomial infections and their most important pathogens. For this purpose, the national reference database for the surveillance of nosocomial infections in intensive care patients (ICU-KISS) and operated patients (OP-KISS) of the German hospital infection surveillance system (KISS) was analyzed for the period from January 2000 to December 2009. The definition of the seasons was based on freely available climate data from the German weather service "Deutscher Wetterdienst". For ICU-KISS, incidence densities (infections/1000 patient-days) and incidence density ratios, for OP- KISS incidences (infections/100 operated patients) and relative risks, were calculated respectively with the 95% confidence intervals. The analysis was based on 8,680,283 patient-days and 42,603 infections from 597 intensive care units and 767,970 operated patients and 13,586 surgical site infections in 595 surgical departments. The results showed both a significant increase in primary sepsis in the summer period (incidence density ratio 1.10 [1.05 to 1.16]) and a significant decrease in winter period (incidence density ratio 0.89 [0.84 -0.94]) and also a significant increase in lower respiratory tract infections in the summer period (incidence density ratio 1.08 [1.05 to 1.12]) and a significant decrease in winter (incidence density ratio 0.96 [0.93 -0.999]) period. The surgical site infections also showed a significant increase in summer (relative risk 1.11 [1.06 to 1.15]) and a significant decrease in winter (relative risk 0.95 [0.91 to 0.99]). Among the most important pathogens of nosocomial infections nonfermenting bacteria such as pseudomonas aeruginosa and acinetobacter baumannii, enterobacteria such as enterobacter spp. and klebsiella spp. and some other pathogens were identified as seasonal infectious agents. The finding that seasonal effects exist in nosocomial infections makes it necessary to consider these effects in the planning, implementation and evaluation of studies. Since the extent of seasonal effects is relatively low, further studies will be necessary to evaluate the effect of the introduction of seasonally adjusted hygiene measures

Clinical evaluation of a web-based personalized recommendation system with electronic health record interface to optimize healthcare resources during SARS-CoV-2 surges

Abstract During the SARS-CoV-2 pandemic, the German healthcare system faced challenges of efficiently allocating testing resources. To address this, we developed an open-source personalized recommendation system (PRS) called “CovApp”. The PRS utilized a questionnaire to estimate the risk of infection, provided personalized recommendations such as testing, self-isolation, or quarantine, and featured QR code data transmission to electronic health records. The PRS served up to 2.5 million monthly users and received 67,000 backlinks from 1800 domains. We clinically evaluated the PRS at the SARS-CoV-2 testing facility at Charité and observed a 21.7% increase in patient throughput per hour and a 22.5% increase in patients per day. Patients using the PRS were twice as likely to belong to the High Risk group eligible for testing (18.6% vs. 8.9%, p < 0.0001), indicating successful compliance with CovApp’s recommendations. CovApp served as a digital bridge between the population and medical staff and significantly improved testing efficiency. As an open-source platform, CovApp can be readily customized to address emerging public health crises. Further, given the EHR interface, the app is of great utility for other applications in clinical settings