Influence of State Laws Mandating Reporting of Healthcare-Associated Infections: The Case of Central Line–Associated Bloodstream Infections

2013 ◽  
Vol 34 (8) ◽  
pp. 780-784 ◽  
Author(s):  
Amy L. Pakyz ◽  
Michael B. Edmond
Keyword(s):  
Central Line ◽  
Healthcare Associated Infections ◽  
Probit Regression ◽  
Legal Requirements ◽  
State Legislation ◽  
State Laws ◽  
The Mean ◽  
Healthcare Associated ◽  
The Impact ◽  
Mean State

Objective.To evaluate the impact of state laws on reporting of healthcare-associated infections on central line-associated bloodstream infection (CLABSI) rates.Design.Retrospective, cross-sectional study.Methods.Hospital-level administrative and Hospital Compare data were collected on University HealthSystem Consortium hospitals. An ordered probit regression model assessed the association between state legislation and CLABSI standardized infection ratio (SIR). The main independent variable was a state legislation variable concerning 3 legal requirements (data submission, reporting of data to the public, inclusion of facility identifiers in public reports) and was coded for hospitals accordingly located in a state that did not have CLABSI reporting, located in a state that had CLABSI reporting legislation and met 3 legal requirements, or located in a state that had CLABSI reporting but did not meet the 3 legal requirements. A secondary analysis ascertained whether the mean state SIR values differed among the 3 legislation groups.Results.There were 159 hospitals included; 92 were located in states that had CLABSI reporting and met 3 requirements, 33 were located in states that had reporting but did not meet the 3 requirements, and 34 were in states that had no legislation. There was no effect of state legislation group on CLABSI SIR. There were no significant differences in the mean state CLABSI SIRs among the legislation groups.Conclusions.In this sample of academic medical centers, there was no evidence of an effect of state HAI laws on CLABSI occurrence. The impact of state legislation may be lessened by other CLABSI prevention initiatives.

scholarly journals Impact of Healthcare-Associated Infections Connected to Medical Devices—An Update

2021 ◽  
Vol 9 (11) ◽  
pp. 2332
Author(s):  
Nitin Chandra Teja Dadi ◽  
Barbora Radochová ◽  
Jarmila Vargová ◽  
Helena Bujdáková
Keyword(s):  
Medical Devices ◽  
Surgical Site Infections ◽  
Central Line ◽  
Ventilator Associated Pneumonia ◽  
Healthcare Associated Infections ◽  
Care Bundles ◽  
Planktonic Form ◽  
Novel Approaches ◽  
Healthcare Associated ◽  
The Impact

Healthcare-associated infections (HAIs) are caused by nosocomial pathogens. HAIs have an immense impact not only on developing countries but also on highly developed parts of world. They are predominantly device-associated infections that are caused by the planktonic form of microorganisms as well as those organized in biofilms. This review elucidates the impact of HAIs, focusing on device-associated infections such as central line-associated bloodstream infection including catheter infection, catheter-associated urinary tract infection, ventilator-associated pneumonia, and surgical site infections. The most relevant microorganisms are mentioned in terms of their frequency of infection on medical devices. Standard care bundles, conventional therapy, and novel approaches against device-associated infections are briefly mentioned as well. This review concisely summarizes relevant and up-to-date information on HAIs and HAI-associated microorganisms and also provides a description of several useful approaches for tackling HAIs.

scholarly journals 172. Impact of COVID-19 Pandemic on Healthcare-associated Infections (HAIs) in a Large Network of Hospitals

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S103-S104
Author(s):  
Sonali D Advani ◽  
Sonali D Advani ◽  
Emily Sickbert-Bennett ◽  
Elizabeth Dodds Ashley ◽  
Andrea Cromer ◽  
...  
Keyword(s):  
Regression Model ◽  
Baseline Period ◽  
Central Line ◽  
Healthcare Associated Infections ◽  
Large Network ◽  
Segmented Regression ◽  
Tract Infections ◽  
Healthcare Associated ◽  
The Impact ◽  
Segmented Regression Model

Abstract Background The COVID-19 pandemic had a considerable impact on US healthcare systems, straining hospital resources, staff, and operations. Our objective was to evaluate the impact of COVID-19 pandemic on incidence and trends of healthcare-associated infections (HAIs) in a network of hospitals. Methods This was a retrospective review of central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), C. difficile infections (CDI), and ventilator-associated events (VAE) in 51 hospitals from 2018 to 2021. Descriptive statistics were reported as mean hospital-level monthly incidence rates (IR) and compared using Poisson regression GEE models with period as the only covariate. Segmented regression (SR) analysis was performed to estimate changes in monthly IR of CAUTIs, CLABSIs and CDI in the baseline period (01/2018 – 02/2020) and the Pandemic period (03/2020 – 03/2021). SR model was not appropriate for VAE based on the plot. All models were constructed using SAS v.9.4 (SAS Institute, Cary NC). Results Compared to the baseline period, CLABSIs increased significantly by 50% from 0.6 to 0.9/ 1000 catheter days (P< 0. 001). In contrast, no significant changes were identified for CAUTI (P=0.87). Similar trends were seen in SR models for CLABSI and CAUTI (Figures 1, 2 and Table 1). While overall CDIs decreased significantly from 3.5 to 2.5/10,000 patient days in the pandemic period (P< 0.001), SR model showed increasing pandemic trend change (Figure 3). VAEs increased > 700% from 6.9 to 59.7/1000 ventilator days (P=0.15), but displayed considerable variation during the pandemic period (Figure 4). Compared to baseline period, there was a significant increase in central line days (647 vs 677, P=0.02), ventilator days (156 vs 215, P< 0.001), but no change in urinary catheter days (675 vs 686, P=0.32) during the pandemic period. Figure 1: Segmented Regression model showing baseline and pandemic period trends of CLABSI Figure 2: Segmented Regression model showing baseline and pandemic period trends of CAUTI Figure 3: Segmented Regression model showing baseline and pandemic period trends of C. difficile (HO-CDI) infections Conclusion The COVID-19 pandemic was associated with substantial increases in CLABSIs and VAEs, no change in CAUTIs, and an increasing trend in CDI incidence. These variations in trends of different HAIs are likely due, in part, to unique characteristics of the underlying infection, resource shortages, staffing concerns, increased device use, changes in testing practices, and the limitations of surveillance definitions. Figure 4: Trend of Ventilator-Associated Events (VAE) in the baseline and pandemic period (Segmented Regression model not appropriate) Disclosures Sonali D. Advani, MBBS, MPH, Nothing to disclose David J. Weber, MD, MPH, Merck (Individual(s) Involved: Self): Consultant; PDI (Individual(s) Involved: Self): Consultant; Pfizer (Individual(s) Involved: Self): Consultant; Sanofi (Individual(s) Involved: Self): Consultant; UVinnovators (Individual(s) Involved: Self): Consultant

scholarly journals 593. Burden of Healthcare-Associated Infections among Hospitalized Infants within Community Hospitals

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S279-S280
Author(s):  
Ibukunoluwa C Akinboyo ◽  
Rebecca R Young ◽  
Michael J Smith ◽  
Becky A Smith ◽  
Sarah S Lewis ◽  
...  
Keyword(s):  
Infection Control ◽  
Neonatal Intensive Care ◽  
Bloodstream Infections ◽  
Central Line ◽  
Control Network ◽  
Healthcare Associated Infections ◽  
Community Hospitals ◽  
Tract Infections ◽  
Healthcare Associated ◽  
The Impact

Abstract Background Healthcare-associated infections (HAI) remain the leading cause of morbidity and mortality among hospitalized children. Within community hospitals with targeted infection prevention efforts, participation in an infection control network has led to significant decreases in device or procedure-related infections among adult patients. The impact of these interventions has not been assessed in pediatric patients admitted to community hospitals. Methods We conducted a retrospective cohort study to describe the burden of HAI among hospitalized infants (< 1 year old) within 53 community hospitals participating in the Duke Infection Control Outreach Network (DICON) from 2013–2018. We determined the frequency of device-related HAI, central line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI) and hospital-associated pneumonia or ventilator-associated events (HAP/VAE) using National Healthcare Safety Network (NHSN) definitions; and the burden of HAIs among neonatal intensive care units (NICU) and non-NICU centers. The trend of HAI was analyzed with Spearman’s correlation. Results Thirty hospitals reported 150 HAI among 141 infants over the 6-year period. Median (IQR) time to infection was 10 (4, 20) days after admission. Hospitals with a NICU (15) reported more HAI (median 5, (IQR: 3, 12)) than hospitals without a NICU (median 2 (IQR: 1, 2)) (P = 0.031). CLABSI represented 35% of HAI, HAP/VAE were 23% and CAUTI were 12%. The most frequently isolated primary organism for all HAI was Escherichia coli (22 HAI, 15%) which was also isolated in 39% of CAUTI. Methicillin-resistant and methicillin-susceptible Staphylococcus aureus (S. aureus) were the most commonly isolated organisms among CLABSI (17%) and HAP/VAE (33%). Nine centers with ≥4 years of NICU and Central line (CL) use data reported a median (IQR) rate of 1.2 (0, 2.4) CLABSIs/1,000 central line days. There was no change in median CLABSI rate over time (P = 0.47), Figure 1. Conclusion CLABSI, most commonly caused by S. aureus, represented the majority of HAI reported from hospitalized infants within community hospitals participating in an infection control network. Further research into device utilization practices may inform future interventions to reduce HAI. Disclosures All authors: No reported disclosures.

scholarly journals Pathogens Associated With Repeat Versus Single Central-Line–Associated Bloodstream Infections, Acute-Care Hospitals, NHSN

2020 ◽  
Vol 41 (S1) ◽  
pp. s343-s344
Author(s):  
Margaret A. Dudeck ◽  
Katherine Allen-Bridson ◽  
Jonathan R. Edwards
Keyword(s):  
Acute Care ◽  
National Level ◽  
Bloodstream Infections ◽  
Acute Care Hospitals ◽  
Central Line ◽  
Patient Specific ◽  
Healthcare Associated Infections ◽  
Healthcare Associated ◽  
Repeat Infection ◽  
Single Versus

Background: The NHSN is the nation’s largest surveillance system for healthcare-associated infections. Since 2011, acute-care hospitals (ACHs) have been required to report intensive care unit (ICU) central-line–associated bloodstream infections (CLABSIs) to the NHSN pursuant to CMS requirements. In 2015, this requirement included general medical, surgical, and medical-surgical wards. Also in 2015, the NHSN implemented a repeat infection timeframe (RIT) that required repeat CLABSIs, in the same patient and admission, to be excluded if onset was within 14 days. This analysis is the first at the national level to describe repeat CLABSIs. Methods: Index CLABSIs reported in ACH ICUs and select wards during 2015–2108 were included, in addition to repeat CLABSIs occurring at any location during the same period. CLABSIs were stratified into 2 groups: single and repeat CLABSIs. The repeat CLABSI group included the index CLABSI and subsequent CLABSI(s) reported for the same patient. Up to 5 CLABSIs were included for a single patient. Pathogen analyses were limited to the first pathogen reported for each CLABSI, which is considered to be the most important cause of the event. Likelihood ratio χ2 tests were used to determine differences in proportions. Results: Of the 70,214 CLABSIs reported, 5,983 (8.5%) were repeat CLABSIs. Of 3,264 nonindex CLABSIs, 425 (13%) were identified in non-ICU or non-select ward locations. Staphylococcus aureus was the most common pathogen in both the single and repeat CLABSI groups (14.2% and 12%, respectively) (Fig. 1). Compared to all other pathogens, CLABSIs reported with Candida spp were less likely in a repeat CLABSI event than in a single CLABSI event (P < .0001). Insertion-related organisms were more likely to be associated with single CLABSIs than repeat CLABSIs (P < .0001) (Fig. 2). Alternatively, Enterococcus spp or Klebsiella pneumoniae and K. oxytoca were more likely to be associated with repeat CLABSIs than single CLABSIs (P < .0001). Conclusions: This analysis highlights differences in the aggregate pathogen distributions comparing single versus repeat CLABSIs. Assessing the pathogens associated with repeat CLABSIs may offer another way to assess the success of CLABSI prevention efforts (eg, clean insertion practices). Pathogens such as Enterococcus spp and Klebsiella spp demonstrate a greater association with repeat CLABSIs. Thus, instituting prevention efforts focused on these organisms may warrant greater attention and could impact the likelihood of repeat CLABSIs. Additional analysis of patient-specific pathogens identified in the repeat CLABSI group may yield further clarification.Funding: NoneDisclosures: None

scholarly journals Perioperative Microbial Contamination From Patients on Contact Precaution in Operating Room Environment

2020 ◽  
Vol 41 (S1) ◽  
pp. s348-s349
Author(s):  
Hajime Kanamori ◽  
William Rutala ◽  
Maria Gergen ◽  
David Jay Weber
Keyword(s):  
Small Computer ◽  
Contact Precaution ◽  
Time Points ◽  
Contact Precautions ◽  
Surgery Patient ◽  
Patient Arrival ◽  
The Mean ◽  
Healthcare Associated ◽  
Cleaning And Disinfection ◽  
The Impact

Background: The contaminated healthcare environment, including operating rooms (ORs), can serve as an important role in transmission of healthcare-associated pathogens. Studies are very limited regarding the level of contamination of ORs during the surgery of a patient on contact precautions and the risk to the next surgery patient after standard room cleaning and disinfection. Objective: Here, we investigated the microbial burden on the OR environment when patients on contact precautions receive surgery, and we assessed the impact of cleaning and disinfection on the contamination of OR environmental sites. Methods: This investigation was conducted in the ORs of an academic facility during an 8-month period. It involved 10 patients on contact precautions for multidrug-resistant pathogens, including methicillin-resistant Staphylococcus aureus (MRSA; n = 7); carbapenem-resistant Enterobacteriaceae (CRE) plus MRSA (n = 2); and vancomycin-resistant Enterococcus (VRE) plus MRSA (n = 1), who underwent surgery. Environmental sampling was performed at the following time points: (1) immediately before the surgical patient’s arrival in the OR, (2) after surgery but before the OR cleaning and disinfection, and (3) after the OR cleaning and disinfection. In total, 1,520 environmental samples collected from 15 OR sites for 10 surgical patients at 3 time points were analyzed. Relatedness among environmental MRSA isolates was determined by pulsed-field gel electrophoresis. Results: Overall, the mean CFUs of aerobes per Rodac plate (CFU/25 cm2) were 10.1 before patient arrival, 14.7 before cleaning and disinfection, and 6.3 after cleaning and disinfection (P < .0001, after cleaning and disinfection vs before cleaning and disinfection). Moreover, 7 environmental sites (46.7%) after cleaning and disinfection, including bed, arm rest, pyxis counter, floor (near, door side), floor (far, by door), steel counter (small, near bed), and small computer desk, had significantly lower mean counts of aerobes than before patient arrival or before cleaning and disinfection (Fig. 1). The mean CFUs of MRSA per Rodac plate (CFU/25 cm2) were 0.04 before patient arrival, 0.66 before cleaning and disinfection, and 0.08 after cleaning and disinfection (P = .0006, after cleaning and disinfection vs before cleaning and disinfection). Of environmental sites where MRSA was identified, 87.2% were on floors (41 of 47) and 19.1% were after cleaning and disinfection (9 of 47, 8 from floors and 1 from pyxis touchscreen). The A2/B2 MRSA strain was identified on different environmental sites (eg, floor, computer desk, counter) in various rooms (eg, OR2, OR10, and OR16), even after cleaning and disinfection (Fig. 2). Conclusions: Our study has demonstrated that the OR environment was contaminated with aerobic bacteria and MRSA after surgery and that MRSA persisted in the environment even after cleaning and disinfection. Enhanced environmental cleaning in the perioperative environment used for patients on isolation is necessary to prevent transmission of healthcare-associated pathogens in ORs.Funding: NoneDisclosures: Drs. Rutala and Weber are consultants to PDI (Professional Disposable International)

Burden of healthcare-associated infections among hospitalized children within community hospitals participating in an infection control network

2021 ◽  
pp. 1-3
Author(s):  
Ibukunoluwa C. Akinboyo ◽  
Rebecca R. Young ◽  
Michael J. Smith ◽  
Sarah S. Lewis ◽  
Becky A. Smith ◽  
...  
Keyword(s):  
Infection Control ◽  
Bloodstream Infections ◽  
Central Line ◽  
Control Network ◽  
Hospitalized Children ◽  
Healthcare Associated Infections ◽  
Community Hospitals ◽  
Prospective Surveillance ◽  
Healthcare Associated ◽  
Pediatric Healthcare

Abstract We describe the frequency of pediatric healthcare-associated infections (HAIs) identified through prospective surveillance in community hospitals participating in an infection control network. Over a 6-year period, 84 HAIs were identified. Of these 51 (61%) were pediatric central-line–associated bloodstream infections, and they often occurred in children <1 year of age.

scholarly journals Impact of Resolution on the Tropical Pacific Circulation in a Matrix of Coupled Models

2009 ◽  
Vol 22 (10) ◽  
pp. 2541-2556 ◽  
Author(s):  
Malcolm J. Roberts ◽  
A. Clayton ◽  
M.-E. Demory ◽  
J. Donners ◽  
P. L. Vidale ◽  
...  
Keyword(s):  
Coupled Model ◽  
Walker Circulation ◽  
Ocean Model ◽  
Tropical Pacific ◽  
Coupled Models ◽  
Model Stability ◽  
The Mean ◽  
The Impact ◽  
Mean State ◽  
The Tropical Pacific

Abstract Results are presented from a matrix of coupled model integrations, using atmosphere resolutions of 135 and 90 km, and ocean resolutions of 1° and 1/3°, to study the impact of resolution on simulated climate. The mean state of the tropical Pacific is found to be improved in the models with a higher ocean resolution. Such an improved mean state arises from the development of tropical instability waves, which are poorly resolved at low resolution; these waves reduce the equatorial cold tongue bias. The improved ocean state also allows for a better simulation of the atmospheric Walker circulation. Several sensitivity studies have been performed to further understand the processes involved in the different component models. Significantly decreasing the horizontal momentum dissipation in the coupled model with the lower-resolution ocean has benefits for the mean tropical Pacific climate, but decreases model stability. Increasing the momentum dissipation in the coupled model with the higher-resolution ocean degrades the simulation toward that of the lower-resolution ocean. These results suggest that enhanced ocean model resolution can have important benefits for the climatology of both the atmosphere and ocean components of the coupled model, and that some of these benefits may be achievable at lower ocean resolution, if the model formulation allows.

scholarly journals Current Pattern and Clinico-Bacteriological Profile of Healthcare Associated Infections (HAI) in an ICU Setting: An Observational Study

2021 ◽  
Author(s):  
Mradul Kumar Daga ◽  
Govind Mawari ◽  
Saman Wasi ◽  
Naresh Kumar ◽  
Udbhav Sharma ◽  
...  
Keyword(s):  
Age Groups ◽  
Healthcare Facility ◽  
Central Line ◽  
Multidrug Resistant ◽  
Gram Negative Bacteria ◽  
Healthcare Associated Infections ◽  
Acinetobacter Species ◽  
Gram Negative ◽  
Causative Agents ◽  
Healthcare Associated

Abstract Objective To understand the pattern and types of healthcare associated infections (HAI) at our healthcare facility, and to determine the common causative agents and their antibiotic susceptibility profile. Methods One hundred consecutive patients diagnosed with HAI were enrolled and monitored; the causative organisms isolated on culture were recorded and their sensitivity profile was generated. Results Of the 100 patients diagnosed with HAI (mean age ± SD being 42 ± 17 years), there were a total of 110 hospital acquired infections with 10 patients having two infections each. Out of 100 patients with HAI, 69 patients had ventilator associated pneumonia (VAP), 21 patients had catheter associated urinary tract infection (CAUTI) patients, and 20 patients had central line associated bloodstream infection (CLABSI). There were 10 patients with both VAP and CAUTI. All of the HAIs were device associated. A total of 76 pathogens were isolated on culture. No organism was isolated in 40 HAI. Majority (94.7%) of the organisms isolated from HAIs were gram-negative bacteria and all were multidrug resistant. Seventy-seven of the enrolled patients expired while 23 were discharged from the hospital Conclusions Our study demonstrated that HAIs occur in patients of all age groups; younger patients are not spared. Majority of the HAIs were caused by multidrug resistant gram-negative bacteria and were associated with high patient mortality. Acinetobacter species was the most common organism associated with HAI.

scholarly journals The financial impact of improved hand hygiene on healthcare-associated infections in the UK

2020 ◽  
pp. 117-122
Author(s):  
Katie-Rose Cawthorne Cawthorne ◽  
Jason Dean ◽  
Richard PD Cooke
Keyword(s):  
Hand Hygiene ◽  
Financial Analysis ◽  
Cost Savings ◽  
Direct Costs ◽  
Healthcare Associated Infections ◽  
Financial Assessment ◽  
Paediatric Hospital ◽  
The Uk ◽  
Healthcare Associated ◽  
The Impact

Background: Though high hand hygiene (HH) levels significantly reduce the risk of healthcare-associated infections (HCAIs), the current cost of HCAIs and the impact of optimal HH practices on HCAIs are poorly defined. The last NHS England financial assessment was in 2009. Methods: The number of HCAIs per bed per year for NHS England were calculated and average costs were attributed using data from three sources; National Audit Office report, a commercially available calculator, and a financial analysis by a specialist paediatric hospital in England. Improved HH compliance for NHS England was based on a sustained rise in compliance rates from 50 to 80% combined with an HCAI reduction of at least 20%. The cost savings based on such improvements were then calculated. Results: In 2020, it is estimated that the number of HCAIs per bed per year ranges from 3.0 to 9.3, with a midpoint of 5.1. The direct costs of HCAI to NHS England were found to lie between £1.6 and £5 billion. Based on a 20% reduction in HCAI rates, this could lead to cost savings of between £322 million and £1 billion per year. Conclusion: Current direct costs of HCAIs consume approximately 1.3% to 4.1% of NHS England’s annual budget. Improving HH compliance among healthcare workers can lead to significant cost savings. There appears to be a strong financial argument for investment into innovative HH compliance technologies that have been historically perceived as too expensive.

Infection preventionist staffing levels and rates of 10 types of healthcare-associated infections: A 9-year ambidirectional observation

2022 ◽  
pp. 1-6
Author(s):  
Robert J. Clifford ◽  
Donna Newhart ◽  
Maryrose R. Laguio-Vila ◽  
Jennifer L. Gutowski ◽  
Melissa Z. Bronstein ◽  
...  
Keyword(s):  
Control Charts ◽  
Bloodstream Infections ◽  
Central Line ◽  
Healthcare Associated Infections ◽  
Full Time ◽  
Staffing Levels ◽  
Clostridioides Difficile ◽  
Carbapenem Resistant ◽  
Healthcare Associated ◽  
Carbapenem Resistant Enterobacteriaceae

Abstract Objective: To quantitatively evaluate relationships between infection preventionists (IPs) staffing levels, nursing hours, and rates of 10 types of healthcare-associated infections (HAIs). Design and setting: An ambidirectional observation in a 528-bed teaching hospital. Patients: All inpatients from July 1, 2012, to February 1, 2021. Methods: Standardized US National Health Safety Network (NHSN) definitions were used for HAIs. Staffing levels were measured in full-time equivalents (FTE) for IPs and total monthly hours worked for nurses. A time-trend analysis using control charts, t tests, Poisson tests, and regression analysis was performed using Minitab and R computing programs on rates and standardized infection ratios (SIRs) of 10 types of HAIs. An additional analysis was performed on 3 stratifications: critically low (2–3 FTE), below recommended IP levels (4–6 FTE), and at recommended IP levels (7–8 FTE). Results: The observation covered 1.6 million patient days of surveillance. IP staffing levels fluctuated from ≤2 IP FTE (critically low) to 7–8 IP FTE (recommended levels). Periods of highest catheter-associated urinary tract infection SIRs, hospital-onset Clostridioides difficile and carbapenem-resistant Enterobacteriaceae infection rates, along with 4 of 5 types of surgical site SIRs coincided with the periods of lowest IP staffing levels and the absence of certified IPs and a healthcare epidemiologist. Central-line–associated bloodstream infections increased amid lower nursing levels despite the increased presence of an IP and a hospital epidemiologist. Conclusions: Of 10 HAIs, 8 had highest incidences during periods of lowest IP staffing and experience. Some HAI rates varied inversely with levels of IP staffing and experience and others appeared to be more influenced by nursing levels or other confounders.

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