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Prevention of Clostridioides difficile infection (CDI) is a national priority and may be facilitated by deployment of the Targeted Assessment for Prevention (TAP) Strategy, a quality improvement framework providing a focused approach to infection prevention. This article describes the process and outcomes of TAP Strategy implementation for CDI prevention in a healthcare system.
Hospital A was identified based on CDI surveillance data indicating an excess burden of infections above the national goal; hospitals B and C participated as part of systemwide deployment. TAP facility assessments were administered to staff to identify infection control gaps and inform CDI prevention interventions. Retrospective analysis was performed using negative-binomial, interrupted time series (ITS) regression to assess overall effect of targeted CDI prevention efforts. Analysis included hospital-onset, laboratory-identified C. difficile event data for 18 months before and after implementation of the TAP facility assessments.
The systemwide monthly CDI rate significantly decreased at the intervention (β2, −44%; P = .017), and the postintervention CDI rate trend showed a sustained decrease (β1 + β3; −12% per month; P = .008). At an individual hospital level, the CDI rate trend significantly decreased in the postintervention period at hospital A only (β1 + β3, −26% per month; P = .003).
This project demonstrates TAP Strategy implementation in a healthcare system, yielding significant decrease in the laboratory-identified C. difficile rate trend in the postintervention period at the system level and in hospital A. This project highlights the potential benefit of directing prevention efforts to facilities with the highest burden of excess infections to more efficiently reduce CDI rates.
Describe common pathogens and antimicrobial resistance patterns for healthcare-associated infections (HAIs) that occurred during 2015–2017 and were reported to the Centers for Disease Control and Prevention’s (CDC’s) National Healthcare Safety Network (NHSN).
Data from central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated events (VAEs), and surgical site infections (SSIs) were reported from acute-care hospitals, long-term acute-care hospitals, and inpatient rehabilitation facilities. This analysis included device-associated HAIs reported from adult location types, and SSIs among patients ≥18 years old. Percentages of pathogens with nonsusceptibility (%NS) to selected antimicrobials were calculated for each HAI type, location type, surgical category, and surgical wound closure technique.
Overall, 5,626 facilities performed adult HAI surveillance during this period, most of which were general acute-care hospitals with <200 beds. Escherichia coli (18%), Staphylococcus aureus (12%), and Klebsiella spp (9%) were the 3 most frequently reported pathogens. Pathogens varied by HAI and location type, with oncology units having a distinct pathogen distribution compared to other settings. The %NS for most pathogens was significantly higher among device-associated HAIs than SSIs. In addition, pathogens from long-term acute-care hospitals had a significantly higher %NS than those from general hospital wards.
This report provides an updated national summary of pathogen distributions and antimicrobial resistance among select HAIs and pathogens, stratified by several factors. These data underscore the importance of tracking antimicrobial resistance, particularly in vulnerable populations such as long-term acute-care hospitals and intensive care units.
To describe common pathogens and antimicrobial resistance patterns for healthcare-associated infections (HAIs) among pediatric patients that occurred in 2015–2017 and were reported to the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN).
Antimicrobial resistance data were analyzed for pathogens implicated in central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated pneumonias (VAPs), and surgical site infections (SSIs). This analysis was restricted to device-associated HAIs reported from pediatric patient care locations and SSIs among patients <18 years old. Percentages of pathogens with nonsusceptibility (%NS) to selected antimicrobials were calculated by HAI type, location type, and surgical category.
Overall, 2,545 facilities performed surveillance of pediatric HAIs in the NHSN during this period. Staphylococcus aureus (15%), Escherichia coli (12%), and coagulase-negative staphylococci (12%) were the 3 most commonly reported pathogens associated with pediatric HAIs. Pathogens and the %NS varied by HAI type, location type, and/or surgical category. Among CLABSIs, the %NS was generally lowest in neonatal intensive care units and highest in pediatric oncology units. Staphylococcus spp were particularly common among orthopedic, neurosurgical, and cardiac SSIs; however, E. coli was more common in abdominal SSIs. Overall, antimicrobial nonsusceptibility was less prevalent in pediatric HAIs than in adult HAIs.
This report provides an updated national summary of pathogen distributions and antimicrobial resistance patterns among pediatric HAIs. These data highlight the need for continued antimicrobial resistance tracking among pediatric patients and should encourage the pediatric healthcare community to use such data when establishing policies for infection prevention and antimicrobial stewardship.
To 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.
Acute care hospitals that report HAI data to the Centers for Disease Control and Prevention’s National Healthcare Safety Network.
The 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.
Of 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.
The 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
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the Agency for Toxic Substances and Diseases Registry.
Describe the impact of standardizing state-specific summary measures of antibiotic resistance that inform regional interventions to reduce transmission of resistant pathogens in healthcare settings.
Analysis of public health surveillance data.
Central line–associated bloodstream infection (CLABSI) data from intensive care units (ICUs) of facilities reporting to the National Healthcare Safety Network in 2011 were analyzed. For CLABSI due to methicillin-resistant Staphylococcus aureus (MRSA), extended-spectrum cephalosporin (ESC)-nonsusceptible Klebsiella species, and carbapenem-nonsusceptible Klebsiella species, we computed 3 state-level summary measures of nonsusceptibility: crude percent nonsusceptible, model-based adjusted percent nonsusceptible, and crude infection incidence rate.
Overall, 1,791 facilities reported CLABSIs from ICU patients. Of 1,618 S. aureus CLABSIs with methicillin-susceptibility test results, 791 (48.9%) were due to MRSA. Of 756 Klebsiella CLABSIs with ESC-susceptibility test results, 209 (27.7%) were due to ESC-nonsusceptible Klebsiella, and among 661 Klebsiella CLABSI with carbapenem susceptibility test results, 70 (10.6%) were due to carbapenem-nonsusceptible Klebsiella. All 3 state-specific measures demonstrated variability in magnitude by state. Adjusted measures, with few exceptions, were not appreciably different from crude values for any phenotypes. When linking values of crude and adjusted percent nonsusceptible by state, a state’s absolute rank shifted slightly for MRSA in 5 instances and only once each for ESC-nonsusceptible and carbapenem-nonsusceptible Klebsiella species. Infection incidence measures correlated strongly with both percent nonsusceptibility measures.
Crude state-level summary measures, based on existing NHSN CLABSI data, may suffice to assess geographic variability in antibiotic resistance. As additional variables related to antibiotic resistance become available, risk-adjusted summary measures are preferable.
Infect Control Hosp Epidemiol 2015;36(1): 54–64
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