Last data update: Jun 24, 2024. (Total: 47078 publications since 2009)
Records 1-30 (of 38 Records) |
Query Trace: Allen-Bridson K [original query] |
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Health Care-Associated Infections Studies Project: An American Journal of Infection Control and National Healthcare Safety Network Data Quality Collaboration.
Watkins J , Gross C , Godfrey-Johnson D , Allen-Bridson K , Hebden JN , Wright MO . Am J Infect Control 2021 49 (8) 1075-1077 This case study is part of a series centered on the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) healthcare-associated infection (HAI) surveillance definitions. This specific case study focuses on the application of the Pneumonia (PNEU), Ventilator-associated event (VAE), and Bloodstream infections (BSI) surveillance definitions to a patient with COVID-19. The intent of the case study series is to foster standardized application of the NHSN HAI surveillance definitions among Infection Preventionists (IPs) and encourage accurate determination of HAI events. |
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
Konnor R , Russo V , Leaptrot D , Allen-Bridson K , Dudeck MA , Hebden JN , Wright MO . Am J Infect Control 2021 49 (11) 1423-1426 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. |
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.
Wu H , Soe MM , Konnor R , Dantes R , Haass K , Dudeck MA , Gross C , Leaptrot D , Sapiano MRP , Allen-Bridson K , Wattenmaker L , Peterson K , Lemoine K , Chernetsky Tejedor S , Edwards JR , Pollock D , Benin AL . Infect Control Hosp Epidemiol 2021 43 (10) 1-12 During March 27-July 14, 2020, the CDC'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. |
Laboratory-identified vancomycin-resistant enterococci bacteremia incidence: A standardized infection ratio prediction model
Tanwar SSS , Weiner-Lastinger LM , Bell JM , Allen-Bridson K , Bagchi S , Dudeck MA , Edwards JR . Infect Control Hosp Epidemiol 2021 43 (6) 1-5 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. |
Changes in the Number of Intensive Care Unit Beds in U.S. Hospitals During the Early Months of the COVID-19 Pandemic, as reported to the National Healthcare Safety Network's COVID-19 Module.
Weiner-Lastinger LM , Dudeck MA , Allen-Bridson K , Dantes R , Gross C , Nkwata A , Tejedor SC , Pollock D , Benin A . Infect Control Hosp Epidemiol 2021 43 (10) 1-12 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. |
Impact of coronavirus disease 2019 (COVID-19) on US Hospitals and Patients, April-July 2020.
Sapiano MRP , Dudeck MA , Soe M , Edwards JR , O'Leary EN , Wu H , Allen-Bridson K , Amor A , Arcement R , Chernetsky Tejedor S , Dantes R , Gross C , Haass K , Konnor R , Kroop SR , Leaptrot D , Lemoine K , Nkwata A , Peterson K , Wattenmaker L , Weiner-Lastinger LM , Pollock D , Benin AL . Infect Control Hosp Epidemiol 2021 43 (1) 1-28 OBJECTIVE: The rapid spread of SARS-CoV-2 throughout key regions of the United States (U.S.) 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 COVID-19 data. This paper presents time series estimates of the critical hospital capacity indicators during April 1-July 14, 2020. DESIGN: From March 27-July 14, 2020, NHSN collected daily data on hospital bed occupancy, number of hospitalized patients with COVID-19, and availability/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 during April to July, the proportion of occupied inpatient beds increased steadily. COVID-19 hospitalizations increased from mid-June in the South and Southwest 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 declining from a peak in April. Patient outcomes appeared to improve from early April to mid-July. |
Rates and causative pathogens of surgical site infections attributed to liver transplant procedures and other hepatic, biliary or pancreatic procedures, 2015-2018
Chea N , Sapiano MRP , Zhou L , Epstein L , Guh A , Edwards JR , Allen-Bridson K , Russo V , Watkins J , Pouch SM , Magill SS . Transpl Infect Dis 2021 23 (4) e13589 Liver transplant recipients are at high risk for surgical site infections (SSIs). Limited data are available on SSI epidemiology following liver transplant procedures (LTPs). We analyzed data on SSIs from 2015-2018 reported to CDC's National Healthcare Safety Network to determine rates, pathogen distribution, and antimicrobial resistance after LTPs and other hepatic, biliary, or pancreatic procedures (BILIs). LTP and BILI SSI rates were 5.7% and 5.9%, respectively. The odds of SSI after LTP were lower than after BILI (adjusted odds ratio = 0.70, 95% confidence interval 0.57-0.85). Among LTP SSIs, 43.1% were caused by Enterococcus spp., 17.2% by Candida spp., and 15.0% by coagulase-negative Staphylococcus spp. (CNS). Percentages of SSIs caused by Enterococcus faecium or CNS were higher after LTPs than BILIs, whereas percentages of SSIs caused by Enterobacteriaceae, Enterococcus faecalis, or viridans streptococci were higher after BILIs. Antimicrobial resistance was common in LTP SSI pathogens, including E. faecium (69.4% vancomycin-resistant); E. coli (68.8% fluoroquinolone-non-susceptible, 44.7% extended spectrum cephalosporin [ESC]-non-susceptible); and K. pneumoniae and K. oxytoca (39.4% fluoroquinolone-non-susceptible, 54.5% ESC-non-susceptible). National LTP SSI pathogen and resistance data can help prioritize studies to determine effective interventions to prevent SSIs and reduce antimicrobial resistance in liver transplant recipients. |
Health care-associated infections studies project: an American Journal of Infection Control and National Healthcare Safety Network data quality collaboration
Cali S , Gross C , Allen-Bridson K , Hebden JN , Wright MO . Am J Infect Control 2020 48 (4) 443-445 This case study is part of a series centered on the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN) health care-associated infection (HAI) surveillance definitions. The intent of the case study series is to foster standardized application of the NHSN HAI surveillance definitions among infection preventionists and to promote accurate determination of HAI events. These cases reflect some of the complex patient scenarios that infection preventionists have encountered in their daily surveillance of HAIs using NHSN definitions. Objectives have been previously published.(1). |
Healthcare-Associated Infections Studies Project: An American Journal of Infection Control and National Healthcare Safety Network Data Quality Collaboration Case Study
Norrick B , Lewis N , Allen-Bridson K , Hebden JN , Wright MO . Am J Infect Control 2020 49 (2) 224-225 This National Healthcare Safety Network (NHSN) surveillance case study is part of a case-study series in the American Journal of Infection Control (AJIC). These cases reflect some of the complex patient scenarios Infection Preventionists (IPs) have encountered in their daily surveillance of healthcare-associated infections (HAI) using NHSN definitions. Objectives have been previously published. |
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
Westercamp MD , Dudeck MA , Allen-Bridson K , Konnor R , Edwards JR , Park BJ , Smith RM . Infect Control Hosp Epidemiol 2020 41 (5) 1-3 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
Novosad SA , Fike L , Dudeck MA , Allen-Bridson K , Edwards JR , Edens C , Sinkowitz-Cochran R , Powell K , Kuhar D . Infect Control Hosp Epidemiol 2020 41 (3) 1-7 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. |
Accuracy of catheter-associated urinary tract infections reported to the National Healthcare Safety Network, January 2010 through July 2018
Bagchi S , Watkins J , Norrick B , Scalise E , Pollock DA , Allen-Bridson K . Am J Infect Control 2019 48 (2) 207-211 BACKGROUND: Surveillance of health care-associated, catheter-associated urinary tract infections (CAUTI) are the corner stone of infection prevention activity. The Centers for Disease Control and Prevention's National Healthcare Safety Network provides standard definitions for CAUTI surveillance, which have been updated periodically to increase objectivity, credibility, and reliability of urinary tract infection definitions. Several state health departments have validated CAUTI data that provided insights into accuracy of CAUTI reporting and adherence to CAUTI definition. METHODS: Data accuracy measures included pooled mean sensitivity, specificity, positive predictive value, and negative predictive value. Total CAUTI error rate was computed as proportion of mismatches among total records. The impact of 2015 CAUTI definition changes were tested by comparing pooled accuracy estimates of validations prior to 2015 with post-2015. RESULTS: At least 19 state health departments conducted CAUTI validations and indicated pooled mean sensitivity of 88.3%, specificity of 98.8%, positive predictive value of 93.6%, and negative predictive value of 97.6% of CAUTI reporting to the National Healthcare Safety Network. Among CAUTIs misclassified (121), 66% were underreported and 34% were overreported. CAUTI classification error rate declined significantly from 4.3% (pre-2015) to 2.4% (post-2015). Reasons for CAUTI misclassifications included: misapplication of CAUTI definition, misapplication of general health care-associated infection definitions, and clinical judgement over surveillance definition. CONCLUSIONS: CAUTI underreporting is a major concern; validations provide transparency, education, and relationship building to improve reporting accuracy. |
Health care-associated infections studies project: An American Journal of Infection Control and National Healthcare Safety Network data quality collaboration case study: Bloodstream infection-patient injection into vascular access 2018
Puckett K , Allen-Bridson K , Godfrey D , Gross C , Hebden JN , Powell L , Wright MO . Am J Infect Control 2018 47 (5) 574-576 This case study is part of a series centered on the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) health care-associated infection surveillance definitions. These cases reflect some of the complex patient scenarios infection preventionists have encountered in their daily surveillance of health care-associated infections using NHSN definitions and protocols. |
State health department validations of central line-associated bloodstream infection events reported via the National Healthcare Safety Network
Bagchi S , Watkins J , Pollock DA , Edwards JR , Allen-Bridson K . Am J Infect Control 2018 46 (11) 1290-1295 BACKGROUND: Numerous state health departments (SHDs) have validated central line-associated bloodstream infection (CLABSI) data, and results from these studies provide important insights into the accuracy of CLABSI reporting to the National Healthcare Safety Network (NHSN) and remediable shortcomings in adherence to the CLABSI definition and criteria. METHODS: State CLABSI validation results were obtained from peer-reviewed publications, reports on SHD Web sites, and via personal communications with the SHD health care-associated infections coordinator. Data accuracy measures included pooled mean sensitivity, specificity, positive predictive value, and negative predictive value. Total CLABSI error rate was computed as the proportion of mismatches among total records reviewed. When available, reasons for CLABSI misclassification reported by SHDs were reviewed. RESULTS: At least 23 SHDs that have completed CLABSI validations indicated sensitivity (pooled mean, 82.9%), specificity (pooled mean, 98.5%), positive predictive value (pooled mean, 94.1%), and negative predictive value (pooled mean, 95.9%) of CLABSI reporting. The pooled error rate of CLABSI reporting was 4.4%. Reasons for CLABSI misclassification included incorrect secondary bloodstream infection attribution, misapplication of CLABSI definition, missed case finding, applying clinical over surveillance definitions, misapplication of laboratory-confirmed bloodstream infection 2 definition, and misapplication of general NHSN definitions. CONCLUSIONS: CLABSI underreporting remains a major concern; validations conducted by SHDs provide an important impetus for improved reporting. SHDs are uniquely positioned to engage facilities in collaborative validation reviews that allow transparency, education, and relationship building. |
Healthcare-associated infections studies project: An American Journal of Infection Control and National Healthcare Safety Network data quality collaboration: Location mapping
Wright MO , Decker SG , Allen-Bridson K , Hebden JN , Leaptrot D . Am J Infect Control 2018 46 (5) 577-578 This case study is part of a series centered on the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) health care-associated infection (HAI) surveillance definitions. This specific case study focuses on appropriately mapping locations within an NHSN-enrolled facility. The intent of the case study series is to foster standardized application of the NHSN HAI surveillance definitions among IPs and encourage accurate determination of HAI events. 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 and explanations and rationales. 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 NHSN HAI surveillance definitions. |
Assessment of the accuracy and consistency in the application of standardized surveillance definitions: A summary of the American Journal of Infection Control and National Healthcare Safety Network case studies, 2010-2016
Wright MO , Allen-Bridson K , Hebden JN . Am J Infect Control 2017 45 (6) 607-611 BACKGROUND: The Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) surveillance definitions are the most widely used criteria for health care-associated infection (HAI) surveillance. NHSN participants agree to conduct surveillance in accordance with the NHSN protocol and criteria. To assess the application of these standardized surveillance specifications and offer infection preventionists (IPs) opportunities for ongoing education, a series of case studies, with questions related to NHSN definitions and criteria were published. METHODS: Beginning in 2010, case studies with multiple-choice questions based on standard surveillance criteria and protocols were written and published in the American Journal of Infection Control with a link to an online survey. Participants anonymously submitted their responses before receiving the correct answers. RESULTS: The 22 case studies had 7,950 respondents who provided 27,790 responses to 75 questions during the first 6 years. Correct responses were selected 62.5% of the time (17,376 out of 27,290), but ranged widely (16%-87%). In a subset analysis, 93% of participants self-identified as IPs (3,387 out of 3,640), 4.5% were public health professionals (163 out of 3,640), and 2.5% were physicians (90 out of 3,640). IPs responded correctly (62%) more often than physicians (55%) (P = .006). CONCLUSIONS: Among a cohort of voluntary participants, accurate application of surveillance criteria to case studies was suboptimal, highlighting the need for continuing education, competency development, and auditing. |
Health care-associated infections studies project: An American Journal of Infection Control and National Healthcare Safety Network data quality collaboration
Smith H , Brooks JE , Leaptrot D , Allen-Bridson K , Anttila A , Gross C , Hebden JN , Ryan G , Scalise E , Wright MO . Am J Infect Control 2017 45 (6) 612-614 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. The intent of the case study series is to foster standardized application of the NHSN's HAI surveillance definitions among infection preventionists and accurate determination of HAI events. This specific case study focuses on the definitions found within the surgical site infection (SSI) protocol. It aims to reflect the real life and complex patient scenario surrounding a bloodstream infection that is secondary to an SSI and the application of the Present at the Time of Surgery event detail. 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 and explanations and rationales. 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 surveillance definitions. |
Response to "Potential Misclassification of Urinary Tract Related Bacteremia Upon Applying the 2015 Catheter-Associated Urinary Tract Infection Surveillance Definition From the National Healthcare Safety Network"
Allen-Bridson K , Pollock D . Infect Control Hosp Epidemiol 2016 37 (9) 1121 In their concise communication, “Potential Misclassification of Urinary Tract Related Bacteremia Upon Applying the 2015 Catheter-Associated Urinary Tract Infection Surveillance Definition From the National Healthcare Safety Network,”1 Greene et al present findings from their retrospective review of cases they define as urinary tract–related bloodstream infection at 3 VA hospitals. The authors report that among 145 cases with documented indwelling urinary catheters, 93 cases (64.1%) would be deemed catheter-associated urinary tract infections (CAUTIs) according to the updated 2015 National Healthcare Safety Network (NHSN) criteria. The authors conclude that applying those criteria, specifically the criterion introduced in 2015 that requires a urine culture bacterial count of at least 1 × 105 colony-forming units (CFU/mL), would lead to under-ascertainment of clinically meaningful CAUTIs. | | The authors’ concern that “the new CDC surveillance definition has the potential to underestimate the burden of CAUTI-related illness” and that “this has the potential to undermine the faith that clinicians have in the reliability of the national surveillance system for CAUTI,” must be balanced by what was previously an even larger “disconnect” and widely shared concerns about a lack of clinical credibility. A study comparing clinical CAUTI determinations to earlier NHSN definitions indicated that the NHSN definitions had a positive predictive value of only 35% compared to Infectious Diseases consultant evaluation.2 While the CAUTI surveillance criteria that the CDC introduced in 2015 may omit some infections that are deemed clinically significant, the magnitude of missed cases associated with bloodstream infections likely is small, and this possible shortcoming should be placed in the larger context of criteria changes that improve the specificity of case findings. An analysis of NHSN data, completed as part of the review of predecessor CAUTI criteria, showed that the CFU/mL threshold change would result in 10% fewer reported CAUTIs; only 0.5% of all CAUTIs with a reported secondary bloodstream infection would not be reported as a result of the change, much lower than that identified by Green et al.3 Furthermore, many of the “secondary bloodstream infections” previously attributed to the urinary tract may still (and perhaps more appropriately) be captured in NHSN surveillance as central-line–associated bloodstream infections. |
Incidence and characteristics of ventilator-associated events reported to the National Healthcare Safety Network in 2014
Magill SS , Li Q , Gross C , Dudeck M , Allen-Bridson K , Edwards JR . Crit Care Med 2016 44 (12) 2154-2162 OBJECTIVE: Ventilator-associated event surveillance was introduced in the National Healthcare Safety Network in 2013, replacing surveillance for ventilator-associated pneumonia in adult inpatient locations. We determined incidence rates and characteristics of ventilator-associated events reported to the National Healthcare Safety Network. DESIGN, SETTING, AND PATIENTS: We analyzed data reported from U.S. healthcare facilities for ventilator-associated events that occurred in 2014, the first year during which ventilator-associated event surveillance definitions were stable. We used negative binomial regression modeling to identify healthcare facility and inpatient location characteristics associated with ventilator-associated events. We calculated ventilator-associated event incidence rates, rate distributions, and ventilator utilization ratios in critical care and noncritical care locations and described event characteristics. MEASUREMENTS AND MAIN RESULTS: A total of 1,824 healthcare facilities reported 32,772 location months of ventilator-associated event surveillance data to the National Healthcare Safety Network in 2014. Critical care unit pooled mean ventilator-associated event incidence rates ranged from 2.00 to 11.79 per 1,000 ventilator days, whereas noncritical care unit rates ranged from 0 to 14.86 per 1,000 ventilator days. The pooled mean proportion of ventilator-associated events defined as infection-related varied from 15.38% to 47.62% in critical care units. Pooled mean ventilator utilization ratios in critical care units ranged from 0.24 to 0.47. CONCLUSIONS: We found substantial variability in ventilator-associated event incidence, proportions of ventilator-associated events characterized as infection-related, and ventilator utilization within and among location types. More work is needed to understand the preventable fraction of ventilator-associated events and identify patient care strategies that reduce ventilator-associated events.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. |
Letter in response to "questionable validity of the catheter-associated urinary tract infection metric used for value-based purchasing"
Halpin AL , Sinkowitz-Cochran R , Allen-Bridson K , Edwards JR , Pollock D , McDonald LC , Gould CV . Am J Infect Control 2016 44 (3) 369-70 Calderon et al. compares the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) catheter-associated urinary tract infection (CAUTI) metric and the Agency for Healthcare Research and Quality (AHRQ) CAUTI metric. CAUTIs are a major source of morbidity among US hospital patients, leading to unnecessary antibiotic use, secondary bacteremia, and increased length of stay. Many private and public sector organizations have led and continue to lead efforts aimed at preventing CAUTIs, including initiatives spearheaded by Federal agencies: AHRQ, CDC, and the Centers for Medicare & Medicaid Services. To monitor progress in CAUTI prevention, several metrics have been developed. While the CDC metric relies on self-reports of CAUTI events and urinary catheter use by facilities, the NHSN protocol specifies criteria and reporting rules for the purposes of objectivity and standardization. Further, the changes to the definition made in 2015 (Allen-Bridson, Pollock, et al.) likely will improve objectivity and comparability across facilities and enhance the clinical credibility of the CAUTIs reported (e.g., by excluding yeast). In addition, the potential for underreporting will be minimized over time through ongoing and expanding validation efforts and eventual transition to electronic reporting. |
Health care-associated infections studies project: An American Journal of Infection Control and National Healthcare Safety Network data quality collaboration 2016 Case #1
Hebden JN , Leaptrot D , Anttila A , Allen-Bridson K , Brooks JE , Gross C , Scalise E , Wright MO . Am J Infect Control 2016 44 (7) 761-3 This is the first case study published in a series in the American Journal of Infection Control (AJIC) since the Centers for Disease Control and Prevention/ National Healthcare Safety Network (NHSN) surveillance definition update of 2016. These cases represent some of the complex patient scenarios IPs have encountered in their daily surveillance of healthcare-associated infections (HAI) using NHSN procedural approach and definitions. Case study objectives have been previously published. (1) | With each case, a link to an online survey is provided, where you may enter answers to questions and receive immediate feedback in the form of correct answers and explanations. All individual participant answers will remain confidential, although it is the authors' intention to share a summary of the survey responses at a later date. Cases, answers, and explanations have been reviewed and approved by NHSN staff. We hope that you will take advantage of this offering, and we look forward to your active participation. |
Health care-associated infections studies project case #1: A 2015 American Journal of Infection Control and National Healthcare Safety Network data quality collaboration
Gross C , Allen-Bridson K , Anttila A , Brooks JE , Hebden JN , Leaptrot D , Morabit S , Wright MO . Am J Infect Control 2015 43 (9) 987-8 This is the first case study published in a series in the American Journal of Infection Control since the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) surveillance definition update of 2015. These cases reflect some of the complex patient scenarios infection control professionals (ICPs) have encountered in their daily surveillance of health care-associated infections (HAI) using NHSN definitions. |
Health care-associated infections studies project case #2: a 2015 American Journal of Infection Control and National Healthcare Safety Network data quality collaboration
Allen-Bridson K , Anttila A , Brooks JE , Gross C , Hebden JN , Leaptrot D , Morabit S , Wright MO . Am J Infect Control 2015 43 (10) 1099-101 This is the second case study published in a series in the American Journal of Infection Control since the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) surveillance definition update of 2015. These cases reflect some of the complex patient scenarios infection control professionals (ICPs) have encountered in their daily surveillance of health care-associated infections (HAIs) using NHSN definitions |
Promoting prevention through meaningful measures: improving the Centers for Disease Control and Prevention's National Healthcare Safety Network urinary tract infection surveillance definitions
Allen-Bridson K , Pollock D , Gould CV . Am J Infect Control 2015 43 (10) 1096-8 The new year of 2015 brought with it the release of the update to the Centers for Disease Control and Prevention (CDC)'s National Healthcare Safety Network (NHSN) urinary tract infection (UTI) definitions. Although the NHSN UTI definitions were last updated in 2009, the inclusion of catheter-associated UTIs (CAUTIs) in the Centers for Medicare & Medicaid Services' Inpatient Quality Reporting Program in 2012 heightened the challenges to the definitions by many professionals involved in infection prevention. Feedback to CDC beginning in 2012 highlighted the gap between clinical and surveillance determinations of CAUTI1, raised questions about the clinical relevance of some CAUTIs reported to NHSN and drew attention to variability in the application of, and adherence to, the UTI surveillance criteria and differences in clinical laboratory practices relevant to the criteria. Many commenters questioned the validity and fairness of using CAUTI data for public reporting and payment purposes and called for definitions which would more accurately measure the success of CAUTI prevention activities. | For these reasons, in early 2013, CDC began a systematic process of reviewing the NHSN UTI definitions. The main objectives of this work were to: 1) improve the objectivity, credibility, and reliability of the UTI definitions, 2) promote best practices for patient safety with a metric that is reflective of the success or failure of quality improvement and prevention activities, 3) develop a metric that is amenable to full electronic capture to allow for increased objectivity and reduced burden of data collection, and 4) help target CAUTI prevention. |
National Healthcare Safety Network report, data summary for 2013, device-associated Module
Dudeck MA , Edwards JR , Allen-Bridson K , Gross C , Malpiedi PJ , Peterson KD , Pollock DA , Weiner LM , Sievert DM . Am J Infect Control 2015 43 (3) 206-21 This report is a summary of Device-associated (DA) Module data collected by hospitals participating in the National Healthcare Safety Network (NHSN) for events occurring from January through December 2013 and reported to the Centers for Disease Control and Prevention (CDC) by June 1, 2014. This report updates previously published DA Module data from NHSN and provides contemporary comparative rates.1 Figure 1 provides a brief summary of highlights from this report. This report complements other NHSN reports, including national and state-specific progress reports for select healthcare-associated infections (HAIs).2 |
National Healthcare Safety Network (NHSN) report, data summary for 2012, Device-associated module
Dudeck MA , Weiner LM , Allen-Bridson K , Malpiedi PJ , Peterson KD , Pollock DA , Sievert DM , Edwards JR . Am J Infect Control 2013 41 (12) 1148-66 This report is a summary of Device-associated (DA) Module data collected by hospitals participating in the National Healthcare Safety Network (NHSN) for events occurring from January through December 2012 and reported to the Centers for Disease Control and Prevention (CDC) by July 1, 2013. This report updates previously published DA Module data from NHSN and provides contemporary comparative rates.1 Figure 1 provides a brief summary of key findings from this report. This report complements other NHSN reports, including national and state-specific reports of standardized infection ratios (SIRs) for select healthcare-associated infections (HAIs).2, 3 |
Healthcare-associated infections studies project: an American Journal of Infection Control and National Healthcare Safety Network data quality collaboration-ventilator-associated event 1, 2013
Allen-Bridson K , Gross C , Hebden JN , Morrell GC , Wright MO , Horan T . Am J Infect Control 2013 41 (11) 1085-6 This is the second case study published in a series in AJIC since the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) surveillance definition update of 2013. These cases reflect some of the complex patient scenarios Infection Preventionists (IP) have encountered in their daily surveillance of health care-associated infections (HAI) using NHSN definitions. This is the first case utilizing the new NHSN Ventilator-associated Events (VAE) module and criteria. |
Healthcare-associated infections studies project: an American Journal of Infection Control and National Healthcare Safety Network data quality collaboration-LabID Clostridium Difficile event 2013
Hebden JN , Anttila A , Allen-Bridson K , Morrell GC , Wright MO , Horan T . Am J Infect Control 2013 41 (10) 916-7 This is the first in a series of case studies that will be published in American Journal of Infection Control following the Centers for Disease Control and Prevention/National Healthcare Safety Network (NHSN) surveillance definition update of 2013. These cases reflect some of the complex patient scenarios infection professionals encounter during daily surveillance of health care-associated infections using NHSN definitions. Answers to the questions posed and immediate feedback in the form of answers and explanations are available at: http://www.surveymonkey.com/s/AJIC-NHSN-LbId2013. All individual participant answers will remain confidential, although it is the authors' hope to share a summary of the findings at a later date. Cases, answers, and explanations have been reviewed and approved by NHSN staff. Active participation is encouraged and recommended. Review/reference Chapter 12-Multidrug-resistant organism &C difficile infection module protocol, of the NHSN Patient Safety Component Manual (http://www.cdc.gov/nhsn/PDFs/pscManual/12pscMDRO_CDADcurrent.pdf), for information you may need to answer the case study questions. |
Mucosal barrier injury laboratory-confirmed bloodstream infection: results from a field test of a new National Healthcare Safety Network definition
See I , Iwamoto M , Allen-Bridson K , Horan T , Magill SS , Thompson ND . Infect Control Hosp Epidemiol 2013 34 (8) 769-76 OBJECTIVE: To assess challenges to implementation of a new National Healthcare Safety Network (NHSN) surveillance definition, mucosal barrier injury laboratory-confirmed bloodstream infection (MBI-LCBI). DESIGN: Multicenter field test. SETTING: Selected locations of acute care hospitals participating in NHSN central line-associated bloodstream infection (CLABSI) surveillance. METHODS: Hospital staff augmented their CLABSI surveillance for 2 months to incorporate MBI-LCBI: a primary bloodstream infection due to a selected group of organisms in patients with either neutropenia or an allogeneic hematopoietic stem cell transplant with gastrointestinal graft-versus-host disease or diarrhea. Centers for Disease Control and Prevention (CDC) staff reviewed submitted data to verify whether CLABSIs met MBI-LCBI criteria and summarized the descriptive epidemiology of cases reported. RESULTS: Eight cancer, 2 pediatric, and 28 general acute care hospitals including 193 inpatient units (49% oncology/bone marrow transplant [BMT], 21% adult ward, 20% adult critical care, 6% pediatric, 4% step-down) conducted field testing. Among 906 positive blood cultures reviewed, 282 CLABSIs were identified. Of the 103 CLABSIs that also met MBI-LCBI criteria, 100 (97%) were reported from oncology/BMT locations. Agreement between hospital staff and CDC classification of reported CLABSIs as meeting the MBI-LCBI definition was high (90%; [Formula: see text]). Most MBI-LCBIs (91%) occurred in patients meeting neutropenia criteria. Some hospitals indicated that their laboratories' methods of reporting cell counts prevented application of neutropenia criteria; revised neutropenia criteria were created using data from field testing. CONCLUSIONS: Hospital staff applied the MBI-LCBI definition accurately. Field testing informed modifications for the January 2013 implementation of MBI-LCBI in the NHSN. |
National Healthcare Safety Network report, data summary for 2011, device-associated module
Dudeck MA , Horan TC , Peterson KD , Allen-Bridson K , Morrell G , Anttila A , Pollock DA , Edwards JR . Am J Infect Control 2013 41 (4) 286-300 This report is a summary of Device-associated (DA) Module data collected by hospitals participating in the National Healthcare Safety Network (NHSN) for events occurring from January through December 2011 and reported to the Centers for Disease Control and Prevention (CDC) by August 1, 2012. This report updates previously published DA Module data from NHSN and provides contemporary comparative rates.1 This report complements other NHSN reports, including national and state-specific reports of standardized infection ratios (SIRs) for select healthcare-associated infections (HAIs).2,3,4 | NHSN data collection, reporting, and analysis are organized into three components: Patient Safety, Healthcare Personnel Safety, and Biovigilance, and use standardized methods and definitions in accordance with specific module protocols.5,6,7 Institutions may use modules singly or simultaneously, but once selected, they must be used for a minimum of one calendar month for the data to be included in CDC analyses. All infections are categorized using standard CDC definitions that include laboratory and clinical criteria.7 The DA Module may be used by facilities other than hospitals, including outpatient dialysis centers. A report of data from this module for outpatient dialysis centers was published separately.8 NHSN facilities contributing HAI surveillance data to this report did so voluntarily, in response to state mandatory reporting requirements or in compliance with the Centers for Medicare and Medicaid Services’ (CMS) Hospital Inpatient Quality Reporting (IQR) Program. CDC aggregated these data into a single national database for 2011, consistent with the stated purposes of NHSN, which were to: | Collect data from a sample of healthcare facilities in the United States to permit valid estimation of the magnitude of adverse events among patients and healthcare personnel. | Collect data from a sample of healthcare facilities in the United States to permit valid estimation of the adherence to practices known to be associated with prevention of these adverse events. | Analyze and report collected data to permit recognition of trends. | Provide facilities with risk-adjusted metrics that can be used for inter-facility comparisons and local quality improvement activities. | Assist facilities in developing surveillance and analysis methods that permit timely recognition of patient and healthcare worker safety problems and prompt intervention with appropriate measures. | Conduct collaborative research studies with NHSN member facilities (e.g., describe the epidemiology of emerging healthcare-associated infection [HAI] and pathogens, assess the importance of potential risk factors, further characterize HAI pathogens and their mechanisms of resistance, and evaluate alternative surveillance and prevention strategies). | Comply with legal requirements – including but not limited to state or federal laws, regulations, or other requirements – for mandatory reporting of healthcare facility-specific adverse event, prevention practice adherence, and other public health data. | Enable healthcare facilities to report HAI and prevention practice adherence data via NHSN to the U.S. Centers for Medicare and Medicaid Services (CMS) in fulfillment of CMS’s quality measurement reporting requirements for those data. | Provide state departments of health with information that identifies the healthcare facilities in their state that participate in NHSN. | Provide to state agencies, at their request, facility-specific, NHSN patient safety component and healthcare personnel safety component adverse event and prevention practice adherence data for surveillance, prevention, or mandatory public reporting. | Patient- and facility-specific data reported to CDC are kept confidential in accordance with sections 304, 306, and 308(d) of the Public Health Service Act (42 USC 242b, 242k, and 242m(d)). |
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