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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.

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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.

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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.

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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.

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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.

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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.'

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BACKGROUND: Healthcare-associated antibiotic-resistant (AR) infections increase patient morbidity and mortality and might be impossible to successfully treat with any antibiotic. CDC assessed healthcare-associated infections (HAI), including Clostridium difficile infections (CDI), and the role of six AR bacteria of highest concern nationwide in several types of healthcare facilities. METHODS: During 2014, approximately 4000 short-term acute care hospitals, 501 long-term acute care hospitals, and 1135 inpatient rehabilitation facilities in all 50 states reported data on specific infections to the National Healthcare Safety Network. National standardized infection ratios and their percentage reduction from a baseline year for each HAI type, by facility type, were calculated. The proportions of AR pathogens and HAIs caused by any of six resistant bacteria highlighted by CDC in 2013 as urgent or serious threats were determined. RESULTS: In 2014, the reductions in incidence in short-term acute care hospitals and long-term acute care hospitals were 50% and 9%, respectively, for central line-associated bloodstream infection; 0% (short-term acute care hospitals), 11% (long-term acute care hospitals), and 14% (inpatient rehabilitation facilities) for catheter-associated urinary tract infection; 17% (short-term acute care hospitals) for surgical site infection, and 8% (short-term acute care hospitals) for CDI. Combining HAIs other than CDI across all settings, 47.9% of Staphylococcus aureus isolates were methicillin resistant, 29.5% of enterococci were vancomycin resistant, 17.8% of Enterobacteriaceae were extended-spectrum beta-lactamase phenotype, 3.6% of Enterobacteriaceae were carbapenem resistant, 15.9% of Pseudomonas aeruginosa isolates were multidrug resistant, and 52.6% of Acinetobacter species were multidrug resistant. The likelihood of HAIs caused by any of the six resistant bacteria ranged from 12% in inpatient rehabilitation facilities to 29% in long-term acute care hospitals. CONCLUSIONS: Although there has been considerable progress in preventing some HAIs, many remaining infections could be prevented with implementation of existing recommended practices. Depending upon the setting, more than one in four of HAIs excluding CDI are caused by AR bacteria. IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: Physicians, nurses, and healthcare leaders need to consistently and comprehensively follow all recommendations to prevent catheter- and procedure-related infections and reduce the impact of AR bacteria through antimicrobial stewardship and measures to prevent spread.

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BACKGROUND: Health care-associated antibiotic-resistant (AR) infections increase patient morbidity and mortality and might be impossible to successfully treat with any antibiotic. CDC assessed health care-associated infections (HAI), including Clostridium difficile infections (CDI), and the role of six AR bacteria of highest concern nationwide in several types of health care facilities. METHODS: During 2014, approximately 4,000 short-term acute care hospitals, 501 long-term acute care hospitals, and 1,135 inpatient rehabilitation facilities in all 50 states reported data on specific infections to the National Healthcare Safety Network. National standardized infection ratios and their percentage reduction from a baseline year for each HAI type, by facility type, were calculated. The proportions of AR pathogens and HAIs caused by any of six resistant bacteria highlighted by CDC in 2013 as urgent or serious threats were determined. RESULTS: In 2014, the reductions in incidence in short-term acute care hospitals and long-term acute care hospitals were 50% and 9%, respectively, for central line-associated bloodstream infection; 0% (short-term acute care hospitals), 11% (long-term acute care hospitals), and 14% (inpatient rehabilitation facilities) for catheter-associated urinary tract infection; 17% (short-term acute care hospitals) for surgical site infection, and 8% (short-term acute care hospitals) for CDI. Combining HAIs other than CDI across all settings, 47.9% of Staphylococcus aureus isolates were methicillin resistant, 29.5% of enterococci were vancomycin-resistant, 17.8% of Enterobacteriaceae were extended-spectrum beta-lactamase phenotype, 3.6% of Enterobacteriaceae were carbapenem resistant, 15.9% of Pseudomonas aeruginosa isolates were multidrug resistant, and 52.6% of Acinetobacter species were multidrug resistant. The likelihood of HAIs caused by any of the six resistant bacteria ranged from 12% in inpatient rehabilitation facilities to 29% in long-term acute care hospitals. CONCLUSIONS: Although there has been considerable progress in preventing some HAIs, many remaining infections could be prevented with implementation of existing recommended practices. Depending upon the setting, more than one in four of HAIs excluding CDI are caused by AR bacteria. IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: Physicians, nurses, and health care leaders need to consistently and comprehensively follow all recommendations to prevent catheter- and procedure-related infections and reduce the impact of AR bacteria through antimicrobial stewardship and measures to prevent spread.

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