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Background: We evaluated the trend of four years (2015 - 2018) of "alert organisms" surveillance carried out at the 450 bed teaching hospital S. Andrea in Rome., Methods: All patients with an "Alert organism" isolation were screened. In accordance with definitions used by the Centers for Disease Control patients with an "alert organism" isolation were evaluated for infection or colonization, by an infection control team (ICT)., Results: Between April 2015 and December 2018 a total 4,762 specimens with "Alert organism" isolation were screened and 1,601 patients were surveyed and included in the study. Overall 780 (48.8%) patients developed an healthcare acquired infection (HAI) at our institution, whereas 311 (19.4%) entered with a community acquired infection, 254 (15.8%) with an infection acquired in another healthcare setting and 256 (16.0%) resulted simply colonized. The 780 patients who developed an HAI at our institution presented 878 infectious episodes and the isolation of 931 microorganisms. C. difficile infections were the most common (27.2%), followed by 21.3% respiratory tract infections, 16.9% urinary tract infections, 15.5% surgical site infections, 12.5% bloodstream infections, 3.6% ulcers and 3.0% others. Among HAI group Gram negatives (54.1%) were more frequent than Gram positives (45.9%), whereas in patients entering in the hospital already with a community infection Gram positives overpassed Gram negatives (58.7% vs. 41.3%; p<0.001). Most common pathogens responsible for HAI were C. difficile (25.6%), Klebsiella spp. (25.5%), MRSA (19.6%) and Acinetobacter spp. (15.3%). Notably 30.0% HAI at other institutions were represented by C. difficile. Impressively, >40% of community acquired infections were related to MRSA., Conclusions: The present study provided some useful insight into the major multi-resistant pathogens epidemiology at our institution. The Authors succeeded in organizing a multidisciplinary ICT that created a partnership feeling with the hospital personnel.

Background: Healthcare acquired infections (HAI) cause an increase of burden and in particular excess length of hospital stay (LOS) accounts for approximately up to 90% of total costs. Therefore accurate estimation of extra hospital stay due to healthcare acquired infections is very important., Methods: The authors carried out a review comparing the principal methods internationally used for estimating the excess LOS attributable to healthcare acquired infections., Results: The methods described and analysed are: 1) Implicit physician assessment; 2) appropriateness evaluation protocol; 3) unmatched case-control; 4) matched case-control; 5) regression analysis; 6) multistate model. The various methodologies are described underlining advantages and limits which researchers need to know before starting any economic analysis., Conclusions: Overall, studies taking into account the time-dependent nature of HAI show to give more precise and reliable results.