Challenges and proposed improvements for reviewing symptoms and catheter use to identify National Healthcare Safety Network catheter-associated urinary tract infections

2014 ◽  
Vol 42 (10) ◽  
pp. S236-S241 ◽  
Author(s):  
Jennifer Meddings ◽  
Heidi Reichert ◽  
Laurence F. McMahon
2015 ◽  
Vol 36 (10) ◽  
pp. 1236-1238 ◽  
Author(s):  
Surbhi Leekha ◽  
Michael Anne Preas ◽  
Joan Hebden

Presented in part: 20th Annual Meeting of the Society for Healthcare Epidemiology of America; Dallas, Texas; April 1–4, 2011.Infect Control Hosp Epidemiol 2015;36(10):1236–1238


2015 ◽  
Vol 36 (12) ◽  
pp. 1379-1384 ◽  
Author(s):  
Minn M. Soe ◽  
Carolyn V. Gould ◽  
Daniel Pollock ◽  
Jonathan Edwards

OBJECTIVETo develop a method for calculating the number of healthcare-associated infections (HAIs) that must be prevented to reach a HAI reduction goal and identifying and prioritizing healthcare facilities where the largest reductions can be achieved.SETTINGAcute care hospitals that report HAI data to the Centers for Disease Control and Prevention’s National Healthcare Safety Network.METHODSThe cumulative attributable difference (CAD) is calculated by subtracting a numerical prevention target from an observed number of HAIs. The prevention target is the product of the predicted number of HAIs and a standardized infection ratio goal, which represents a HAI reduction goal. The CAD is a numeric value that if positive is the number of infections to prevent to reach the HAI reduction goal. We calculated the CAD for catheter-associated urinary tract infections for each of the 3,639 hospitals that reported such data to National Healthcare Safety Network in 2013 and ranked the hospitals by their CAD values in descending order.RESULTSOf 1,578 hospitals with positive CAD values, preventing 10,040 catheter-associated urinary tract infections at 293 hospitals (19%) with the highest CAD would enable achievement of the national 25% catheter-associated urinary tract infection reduction goal.CONCLUSIONThe CAD is a new metric that facilitates ranking of facilities, and locations within facilities, to prioritize HAI prevention efforts where the greatest impact can be achieved toward a HAI reduction goal.Infect. Control Hosp. Epidemiol. 2015;36(12):1379–1384


2020 ◽  
Vol 48 (2) ◽  
pp. 207-211
Author(s):  
Suparna Bagchi ◽  
Jennifer Watkins ◽  
Bonnie Norrick ◽  
Eileen Scalise ◽  
Daniel A. Pollock ◽  
...  

2020 ◽  
Vol 42 (1) ◽  
pp. 31-36
Author(s):  
Taniece R. Eure ◽  
Nimalie D. Stone ◽  
Elisabeth A. Mungai ◽  
Jeneita M. Bell ◽  
Nicola D. Thompson

AbstractObjective:Antibiotic resistance (AR) is a growing and highly prevalent problem in nursing homes. We describe selected AR phenotypes from pathogens causing urinary tract infections (UTIs) reported by nursing homes to the National Healthcare Safety Network (NHSN).Design:Pathogens and antibiotic susceptibility testing results for UTI events in nursing homes between January 2013 and December 2017 were analyzed. The pathogen distribution and pooled mean proportion of isolates that tested resistant to select antibiotic agents are reported.Setting and Participants:US nursing homes voluntarily participating in the Long-Term Care Facility component of the NHSN.Results:Overall, 243 nursing homes reported 1 or more UTIs: 121 (50%) were nonprofit facilities, median bed size was 91 (range: 9–801), and average occupancy was 87%. In total, 6,157 pathogens were reported for 5,485 UTI events. Moreover, 9 pathogens accounted for 90% of all reported UTIs; the 3 most frequently identified were Escherichia coli (41%), Proteus species (14%), and Klebsiella pneumoniae/oxytoca (13%). Among E. coli, fluoroquinolone, and extended-spectrum cephalosporin resistance were most prevalent (50% and 20%, respectively). Although Staphylococcus aureus and Enterococcus faecium represented <5% of pathogens reported, they had the highest rates of resistance (67% methicillin resistant and 60% vancomycin resistant, respectively). Multidrug resistance was most common in Pseudomonas aeruginosa (11%). For the resistant phenotypes we assessed, 36% of all UTIs reported were associated with a resistant pathogen.Conclusions:This is the first summary of AR among common pathogens causing UTIs reported to NHSN by nursing homes. Improved understanding of the resistance burden among common infections helps inform facility infection prevention and antibiotic stewardship efforts.


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