Comparison of factors associated with seasonal influenza and COVID-19 booster vaccination coverage among healthcare personnel working at acute care hospitals during 2021-2022 influenza season, National Healthcare Safety Network, United States.

The simultaneous circulation of seasonal influenza virus and SARS-CoV-2 variants will likely pose unique challenges to public health during the future influenza seasons. Persons who are undergoing treatment in healthcare facilities may be particularly at risk. It is important for healthcare personnel to protect themselves and patients by receiving vaccines. The purpose of this study is to assess coverage of the seasonal influenza vaccine and COVID-19 monovalent booster among healthcare personnel working at acute care hospitals in the United States during the 2021-22 influenza season and to examine the demographic and facility characteristics associated with coverage. A total of 3260 acute care hospitals with over 7 million healthcare personnel reported vaccination data to National Healthcare Safety Network (NHSN) during the 2021-22 influenza season. Two separate negative binomial mixed models were developed to explore the factors associated with seasonal influenza coverage and COVID-19 monovalent booster coverage. At the end of the 2021-2022 influenza season, the overall pooled mean seasonal influenza coverage was 80.3%, and the pooled mean COVID-19 booster coverage was 39.5%. Several demographic and facility-level factors, such as employee type, facility ownership, and geographic region, were significantly associated with vaccination against influenza and COVID-19 among healthcare personnel working in acute care hospitals. Our findings highlight the need to increase the uptake of vaccination among healthcare personnel, particularly non-employees, those working in for-profit and non-medical school-affiliated facilities, and those residing in the South.

A Review of Pediatric Central Line-Associated Bloodstream Infections Reported to the National Healthcare Safety Network: United States, 2016-2022.

Central line-associated bloodstream infections (CLABSIs) are common healthcare-associated infections in pediatrics. Children's hospital CLABSI standardized infection ratios decreased when comparing 2016-2019 (-26%, 95% CI [-31%, -20%]), and increased from 2019 to 2022 (18%, 95% CI [9%, 26%]). Resilient pediatric CLABSI prevention initiatives are needed.

Sepsis Program Activities in Acute Care Hospitals - National Healthcare Safety Network, United States, 2022.

Sepsis, life-threatening organ dysfunction secondary to infection, contributes to at least 1.7 million adult hospitalizations and at least 350,000 deaths annually in the United States. Sepsis care is complex, requiring the coordination of multiple hospital departments and disciplines. Sepsis programs can coordinate these efforts to optimize patient outcomes. The 2022 National Healthcare Safety Network (NHSN) annual survey evaluated the prevalence and characteristics of sepsis programs in acute care hospitals. Among 5,221 hospitals, 3,787 (73%) reported having a committee that monitors and reviews sepsis care. Prevalence of these committees varied by hospital size, ranging from 53% among hospitals with 0-25 beds to 95% among hospitals with >500 beds. Fifty-five percent of all hospitals provided dedicated time (including assigned protected time or job description requirements) for leaders of these committees to manage a program and conduct daily activities, and 55% of committees reported involvement with antibiotic stewardship programs. These data highlight opportunities, particularly in smaller hospitals, to improve the care and outcomes of patients with sepsis in the United States by ensuring that all hospitals have sepsis programs with protected time for program leaders, engagement of medical specialists, and integration with antimicrobial stewardship programs. CDC's Hospital Sepsis Program Core Elements provides a guide to assist hospitals in developing and implementing effective sepsis programs that complement and facilitate the implementation of existing clinical guidelines and improve patient care. Future NHSN annual surveys will monitor uptake of these sepsis core elements.

Continued increases in the incidence of healthcare-associated infection (HAI) during the second year of the coronavirus disease 2019 (COVID-19) pandemic.

Data from the National Healthcare Safety Network were analyzed to assess the impact of COVID-19 on the incidence of healthcare-associated infections (HAI) during 2021. Standardized infection ratios were significantly higher than those during the prepandemic period, particularly during 2021-Q1 and 2021-Q3. The incidence of HAI was elevated during periods of high COVID-19 hospitalizations.

Pathogens attributed to central-line-associated bloodstream infections in US acute-care hospitals during the first year of the coronavirus disease 2019 (COVID-19) pandemic.

To assess potential changes in the pathogens attributed to central-line-associated bloodstream infections between 2019 and 2020, hospital data from the National Healthcare Safety Network were analyzed. Compared to 2019, increases in the proportions of pathogens identified as Enterococcus faecalis and coagulase-negative staphylococci were observed during 2020.

Impact of COVID-19 pandemic on central-line-associated bloodstream infections during the early months of 2020, National Healthcare Safety Network.

Data reported to the Centers for Disease Control and Prevention's National Healthcare Safety Network (CDC NHSN) were analyzed to understand the potential impact of the COVID-19 pandemic on central-line-associated bloodstream infections (CLABSIs) in acute-care hospitals. Descriptive analysis of the standardized infection ratio (SIR) was conducted by location, location type, geographic area, and bed size.

Impact of coronavirus disease 2019 (COVID-19) on US Hospitals and Patients, April-July 2020.

OBJECTIVE: The rapid spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) throughout key regions of the United States in early 2020 placed a premium on timely, national surveillance of hospital patient censuses. To meet that need, the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN), the nation's largest hospital surveillance system, launched a module for collecting hospital coronavirus disease 2019 (COVID-19) data. We present time-series estimates of the critical hospital capacity indicators from April 1 to July 14, 2020. DESIGN: From March 27 to July 14, 2020, the NHSN collected daily data on hospital bed occupancy, number of hospitalized patients with COVID-19, and the availability and/or use of mechanical ventilators. Time series were constructed using multiple imputation and survey weighting to allow near-real-time daily national and state estimates to be computed. RESULTS: During the pandemic's April peak in the United States, among an estimated 431,000 total inpatients, 84,000 (19%) had COVID-19. Although the number of inpatients with COVID-19 decreased from April to July, the proportion of occupied inpatient beds increased steadily. COVID-19 hospitalizations increased from mid-June in the South and Southwest regions after stay-at-home restrictions were eased. The proportion of inpatients with COVID-19 on ventilators decreased from April to July. CONCLUSIONS: The NHSN hospital capacity estimates served as important, near-real-time indicators of the pandemic's magnitude, spread, and impact, providing quantitative guidance for the public health response. Use of the estimates detected the rise of hospitalizations in specific geographic regions in June after they declined from a peak in April. Patient outcomes appeared to improve from early April to mid-July.

Hospital capacities and shortages of healthcare resources among US hospitals during the coronavirus disease 2019 (COVID-19) pandemic, National Healthcare Safety Network (NHSN), March 27-July 14, 2020.

During March 27-July 14, 2020, the Centers for Disease Control and Prevention's National Healthcare Safety Network extended its surveillance to hospital capacities responding to COVID-19 pandemic. The data showed wide variations across hospitals in case burden, bed occupancies, ventilator usage, and healthcare personnel and supply status. These data were used to inform emergency responses.

The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: A summary of data reported to the National Healthcare Safety Network.

OBJECTIVES: To determine the impact of the coronavirus disease 2019 (COVID-19) pandemic on healthcare-associated infection (HAI) incidence in US hospitals, national- and state-level standardized infection ratios (SIRs) were calculated for each quarter in 2020 and compared to those from 2019. METHODS: Central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated events (VAEs), select surgical site infections, and Clostridioides difficile and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia laboratory-identified events reported to the National Healthcare Safety Network for 2019 and 2020 by acute-care hospitals were analyzed. SIRs were calculated for each HAI and quarter by dividing the number of reported infections by the number of predicted infections, calculated using 2015 national baseline data. Percentage changes between 2019 and 2020 SIRs were calculated. Supporting analyses, such as an assessment of device utilization in 2020 compared to 2019, were also performed. RESULTS: Significant increases in the national SIRs for CLABSI, CAUTI, VAE, and MRSA bacteremia were observed in 2020. Changes in the SIR varied by quarter and state. The largest increase was observed for CLABSI, and significant increases in VAE incidence and ventilator utilization were seen across all 4 quarters of 2020. CONCLUSIONS: This report provides a national view of the increases in HAI incidence in 2020. These data highlight the need to return to conventional infection prevention and control practices and build resiliency in these programs to withstand future pandemics.

Changes in the number of intensive care unit beds in US hospitals during the early months of the coronavirus disease 2019 (COVID-19) pandemic.

Using data from the National Healthcare Safety Network (NHSN), we assessed changes to intensive care unit (ICU) bed capacity during the early months of the COVID-19 pandemic. Changes in capacity varied by hospital type and size. ICU beds increased by 36%, highlighting the pressure placed on hospitals during the pandemic.

Laboratory-identified vancomycin-resistant enterococci bacteremia incidence: A standardized infection ratio prediction model.

BACKGROUND: We analyzed 2017 healthcare facility-onset (HO) vancomycin-resistant Enterococcus (VRE) bacteremia data to identify hospital-level factors that were significant predictors of HO-VRE using the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) multidrug-resistant organism and Clostridioides difficile reporting module. A risk-adjusted model that can be used to calculate the number of predicted HO-VRE bacteremia events in a facility was developed, thus enabling the calculation of VRE standardized infection ratios (SIRs). METHODS: Acute-care hospitals reporting at least 1 month of 2017 VRE bacteremia data were included in the analysis. Various hospital-level characteristics were assessed to develop a best-fit model and subsequently derive the 2018 national and state SIRs. RESULTS: In 2017, 470 facilities in 35 states participated in VRE bacteremia surveillance. Inpatient VRE community-onset prevalence rate, average length of patient stay, outpatient VRE community-onset prevalence rate, and presence of an oncology unit were all significantly associated (all 95% likelihood ratio confidence limits excluded the nominal value of zero) with HO-VRE bacteremia. The 2018 national SIR was 1.01 (95% CI, 0.93-1.09) with 577 HO bacteremia events reported. CONCLUSION: The creation of an SIR enables national-, state-, and facility-level monitoring of VRE bacteremia while controlling for individual hospital-level factors. Hospitals can compare their VRE burden to a national benchmark to help them determine the effectiveness of infection prevention efforts over time.

How infection present at time of surgery (PATOS) data impacts your surgical site infection (SSI) standardized infection ratios (SIR), with focus on the complex 30-day SSI SIR model.

This case study is part of a series centered on the Centers for Disease Control and Prevention's National Healthcare Safety Network's (NHSN) health care-associated infection (HAI) surveillance definitions. This is the first analytic case study published in AJIC since the CDC/ NHSN updated its HAI risk adjustment models and rebaselined the standardized infection ratios (SIRs) in 2015. This case describes a scenario that Infection Preventionists (IPs) have encountered during their analysis of surgical site infection (SSI) surveillance data. The case study is intended to illustrate how specific models can impact the SIR results by highlighting differences in the criteria for NHSN's older and newer risk models: the original versions and the updated models introduced in 2015. Understanding these differences provides insight into how SSI SIR calculations differ between the older and newer NHSN baseline models. NHSN plans to produce another set of HAI risk adjustment models in the future, using newer HAI incidence and risk factor data. While the timetable for these changes remains to be determined, the statistical methods used to produce future models and SIR calculations will continue the precedents that NHSN has established. An online survey link is provided where participants may confidentially answer questions related to the case study and receive immediate feedback in the form of correct answers, explanations, rationales, and summary of teaching points. Details of the case study, answers, and explanations have been reviewed and approved by NHSN staff. We hope that participants take advantage of this educational offering and thereby gain a greater understanding of the NHSN's HAI data analysis. There are 2 baselines available for SSI standardized infection ration (SIRs) in the National Healthcare Safety Network (NHSN); one based on the 2006-2008 national aggregate data and another based on the 2015 data. Each of the 2 baselines has a different set of inclusion criteria for the SSI data, which impact the calculation of the SIR. In this case study, we focused on the impact of the inclusion of PATOS in the calculation of the 2006-2008 baseline SSI SIR and the exclusion of PATOS from the calculation of the 2015 baseline SSI SIR. In the 2006-2008 baseline SSI SIRs, PATOS events and the procedures to which they are linked are included in the calculation of the SSI SIR whereas in the 2015 baseline SSI SIRs, PATOS events and the procedures to which they are linked are excluded from the calculation of the SSI SIR. Meaning, if we control for all other inclusion criteria other than PATOS data for both baselines, we will notice differences in the number of observed events as well as the number of predicted infections for the 2 baselines. For details of the 2015 baseline and risk adjustment calculation, please review the NHSN Guide to the SIR referenced below. For details of the 2006-2008 baseline4 and risk adjustment, please see the SHEA paper "Improving Risk-Adjusted Measures of Surgical Site Infection for the National Healthcare Safety Network" by author Yi Mu.

Building an Interactive Geospatial Visualization Application for National Health Care-Associated Infection Surveillance: Development Study.

BACKGROUND: The Centers for Disease Control and Prevention's (CDC's) National Healthcare Safety Network (NHSN) is the most widely used health care-associated infection (HAI) and antimicrobial use and resistance surveillance program in the United States. Over 37,000 health care facilities participate in the program and submit a large volume of surveillance data. These data are used by the facilities themselves, the CDC, and other agencies and organizations for a variety of purposes, including infection prevention, antimicrobial stewardship, and clinical quality measurement. Among the summary metrics made available by the NHSN are standardized infection ratios, which are used to identify HAI prevention needs and measure progress at the national, regional, state, and local levels. OBJECTIVE: To extend the use of geospatial methods and tools to NHSN data, and in turn to promote and inspire new uses of the rendered data for analysis and prevention purposes, we developed a web-enabled system that enables integrated visualization of HAI metrics and supporting data. METHODS: We leveraged geocoding and visualization technologies that are readily available and in current use to develop a web-enabled system designed to support visualization and interpretation of data submitted to the NHSN from geographically dispersed sites. The server-client model-based system enables users to access the application via a web browser. RESULTS: We integrated multiple data sets into a single-page dashboard designed to enable users to navigate across different HAI event types, choose specific health care facility or geographic locations for data displays, and scale across time units within identified periods. We launched the system for internal CDC use in January 2019. CONCLUSIONS: CDC NHSN statisticians, data analysts, and subject matter experts identified opportunities to extend the use of geospatial methods and tools to NHSN data and provided the impetus to develop NHSNViz. The development effort proceeded iteratively, with the developer adding or enhancing functionality and including additional data sets in a series of prototype versions, each of which incorporated user feedback. The initial production version of NHSNViz provides a new geospatial analytic resource built in accordance with CDC user requirements and extensible to additional users and uses in subsequent versions.

Antibiotic Multidrug Resistance of Escherichia coli Causing Device- and Procedure-related Infections in the United States Reported to the National Healthcare Safety Network, 2013-2017.

BACKGROUND: Escherichia coli is one of the most common causes of healthcare-associated infections (HAIs); multidrug resistance reduces available options for antibiotic treatment. We examined factors associated with the spread of multidrug-resistant E. coli phenotypes responsible for device- and procedure-related HAIs from acute care hospitals, long-term acute care hospitals, and inpatient rehabilitation facilities, using isolate and antimicrobial susceptibility data reported to the National Healthcare Safety Network during 2013-2017. METHODS: We used multivariable logistic regression to examine associations between co-resistant phenotypes, patient and healthcare facility characteristics, and time. We also examined the geographic distribution of co-resistant phenotypes each year by state and by hospital referral region to identify hot spots. RESULTS: A total of 96 672 E. coli isolates were included. Patient median age was 62 years, and 60% were female; more than half (54%) were reported from catheter-associated urinary tract infections. From 2013 to 2017, 35% of the isolates were nonsusceptible to fluoroquinolones (FQs), 17% to extended-spectrum cephalosporins (ESCs), and 13% to both ESCs and FQs. The proportion of isolates co-resistant to ESCs and FQs was higher in 2017 (14%) than in 2013 (11%) (P < .0001); overall prevalence and increases were heterogeneously distributed across healthcare referral regions. Co-resistance to FQs and ESCs was independently associated with male sex, central line-associated bloodstream infections, long-term acute care hospitals, and the 2016-2017 (vs 2013-2014) reporting period. CONCLUSIONS: Multidrug resistance among E. coli causing device- and procedure-related HAIs has increased in the United States. FQ and ESC co-resistant strains appear to be spreading heterogeneously across hospital referral regions.

Performance of simplified surgical site infection (SSI) surveillance case definitions for resource limited settings: Comparison to SSI cases reported to the National Healthcare Safety Network, 2013-2017.

Surgical site infections (SSIs) are among the most common healthcare-associated infections in low- and middle-income countries. To encourage establishment of actionable and standardized SSI surveillance in these countries, we propose simplified surveillance case definitions. Here, we use NHSN reports to explore concordance of these simplified definitions to NHSN as 'reference standard.'

Pathogens causing central-line-associated bloodstream infections in acute-care hospitals-United States, 2011-2017.

OBJECTIVE: To describe pathogen distribution and rates for central-line-associated bloodstream infections (CLABSIs) from different acute-care locations during 2011-2017 to inform prevention efforts. METHODS: CLABSI data from the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) were analyzed. Percentages and pooled mean incidence density rates were calculated for a variety of pathogens and stratified by acute-care location groups (adult intensive care units [ICUs], pediatric ICUs [PICUs], adult wards, pediatric wards, and oncology wards). RESULTS: From 2011 to 2017, 136,264 CLABSIs were reported to the NHSN by adult and pediatric acute-care locations; adult ICUs and wards reported the most CLABSIs: 59,461 (44%) and 40,763 (30%), respectively. In 2017, the most common pathogens were Candida spp/yeast in adult ICUs (27%) and Enterobacteriaceae in adult wards, pediatric wards, oncology wards, and PICUs (23%-31%). Most pathogen-specific CLABSI rates decreased over time, excepting Candida spp/yeast in adult ICUs and Enterobacteriaceae in oncology wards, which increased, and Staphylococcus aureus rates in pediatric locations, which did not change. CONCLUSIONS: The pathogens associated with CLABSIs differ across acute-care location groups. Learning how pathogen-targeted prevention efforts could augment current prevention strategies, such as strategies aimed at preventing Candida spp/yeast and Enterobacteriaceae CLABSIs, might further reduce national rates.

Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015-2017.

OBJECTIVE: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Antimicrobial-resistant pathogens associated with pediatric healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015-2017.

OBJECTIVE: 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). METHODS: 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. RESULTS: 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. CONCLUSION: 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.

The National Healthcare Safety Network Long-term Care Facility Component early reporting experience: January 2013-December 2015.

BACKGROUND: In 2012, the Centers for Disease Control and Prevention launched the Long-term Care Facility (LTCF) Component of the National Healthcare Safety Network (NHSN) designed for LTCFs to monitor Clostridium difficile infections (CDIs), urinary tract infections (UTIs), infections due to multidrug-resistant organisms, including methicillin-resistant Staphylococcus aureus (MRSA), and infection prevention process measures. METHODS: We describe characteristics and reporting patterns of facilities enrolled in the first 3 years of the surveillance system and rate estimates for CDI, UTI, and MRSA data submitted between 2013 and 2015. RESULTS: From 2013-2015, 279 LTCFs were enrolled and eligible to report to the NHSN with variability in reporting from year to year. Crude rate estimates pooled over these 3 years from reporting facilities were 0.98 incident LTCF-onset CDI cases per 10,000 resident days, 0.59 UTI cases per 1,000 resident days, and 0.10 LTCF-onset MRSA cases per 1,000 resident days. CONCLUSIONS: These initial data demonstrate the capability of the NHSN LTCF Component as a national surveillance system for monitoring infections in LTCFs. Further investigation is needed to understand factors associated with successful enrollment and reporting. As participation increases, data from a larger group of LTCFs will be used to establish national baselines and track prevention goals.