ObjectiveTo describe the epidemiology of healthcare-associated infections (HAI) in hospitals participating in the German national nosocomial infections surveillance system (KISS). MethodThe epidemiology of HAI was described for the surveillance components for intensive care units (ITS-KISS), non-ICUs (STATIONS-KISS), very low birth weight infants (NEO-KISS) and surgical site infections (OP-KISS) in the period from 2006 to 2013. In addition, risk factor analyses were performed for the most important infections of ICU-KISS, NEO-KISS and OP-KISS. ResultsData from a total of 3,454,778 ICU patients from 913 ICUs, 618,816 non-ICU patients from 142 non-ICU wards, 53,676 VLBW from 241 neonatal intensive care units (NICU) and 1,005,064 surgical patients from operative departments from 550 hospitals were used for analysis. Compared with baseline data, a significant reduction of primary bloodstream infections (PBSI) and lower respiratory tract infections (LRTI) was observed in ICUs with the maximum effect in year 5 (or longer participation) (incidence rate ratio 0.60 (CI95 0.50–0.72) and 0.61 (CI95 0.52–0.71) respectively). A significant reduction of PBSI and LRTI was also observed in NEO-KISS when comparing the baseline situation with the 5th year of participation (hazard ratio 0.70 (CI95 0.64–0.76) and 0.43 (CI95 0.35–0.52)). The effect was smaller in operative departments after the introduction of OP-KISS (OR 0.80; CI95 0.64–1.02 in year 5 or later for all procedure types combined). Due to the large database, it has not only been possible to confirm well-known risk factors for HAI, but also to identify some new interesting risk factors like seasonal and volume effects. ConclusionsParticipating in a national surveillance system and using surveillance data for internal quality management leads to substantial reduction of HAI. In addition, a surveillance system can identify otherwise not recognized risk factors which should – if possible – be considered for infection control management and for risk adjustment in the benchmarking process.
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