Healthcare-Associated Bloodstream Infections Secondary to a Urinary Focus The Québec Provincial Surveillance Results

Objective.Urinary tract infections (UTIs) are an important source of secondary healthcare-associated bloodstream infections (BSIs), where a potential for prevention exists. This study describes the epidemiology of BSIs secondary to a urinary source (U-BSIs) in the province of Québec and predictors of mortality.Design.Dynamic cohort of 9,377,830 patient-days followed through a provincial voluntary surveillance program targeting all episodes of healthcare-associated BSIs occurring in acute care hospitals.Setting.Sixty-one hospitals in Québec, followed between April 1, 2007, and March 31, 2010.Participants.Patients admitted to participating hospitals for 48 hours or longer.Methods.Descriptive statistics were used to summarize characteristics of U-BSIs and microorganisms involved. Wilcoxon and X2 tests were used to compare U-BSI episodes with other BSIs. Negative binomial regression was used to identify hospital characteristics associated with higher rates. We explored determinants of mortality using logistic regression.Results.Of the 7,217 reported BSIs, 1,510 were U-BSIs (21%), with an annual rate of 1.4 U-BSIs per 10,000 patient-days. A urinary device was used in 71% of U-BSI episodes. Identified institutional risk factors were average length of stay, teaching status, and hospital size. Increasing hospital size was influential only in nonteaching hospitals. Age, nonhematogenous neoplasia, Staphylococcus aureus, and Foley catheters were associated with mortality at 30 days.Conclusion.U-BSI characteristics suggest that urinary catheters may remain in patients for ease of care or because practitioners forget to remove them. Ongoing surveillance will enable hospitals to monitor trends in U-BSIs and impacts of process surveillance that will be implemented shortly.

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Hospital Microbiologic Culture Results to Predict the Use of Anti–methicillin-Resistant Staphylococcus aureus (MRSA)

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.521 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s40-s40

Author(s):

Hsiu Wu ◽

Tyler Kratzer ◽

Liang Zhou ◽

Minn Soe ◽

Jonathan Edwards ◽

...

Keyword(s):

Staphylococcus Aureus ◽

Risk Adjustment ◽

Negative Binomial ◽

Average Length ◽

Negative Binomial Regression ◽

Drug Resistant ◽

Gram Positive ◽

Average Length Of Stay ◽

Control And Prevention ◽

Hospital Characteristics

Background: To provide a standardized, risk-adjusted method for summarizing antimicrobial use (AU), the Centers for Disease Control and Prevention developed the standardized antimicrobial administration ratio, an observed-to-predicted use ratio in which predicted use is estimated from a statistical model accounting for patient locations and hospital characteristics. The infection burden, which could drive AU, was not available for assessment. To inform AU risk adjustment, we evaluated the relationship between the burden of drug-resistant gram-positive infections and the use of anti-MRSA agents. Methods: We analyzed data from acute-care hospitals that reported ≥10 months of hospital-wide AU and microbiologic data to the National Healthcare Safety Network (NHSN) from January 2018 through June 2019. Hospital infection burden was estimated using the prevalence of deduplicated positive cultures per 1,000 admissions. Eligible cultures included blood and lower respiratory specimens that yielded oxacillin/cefoxitin–resistant Staphylococcus aureus (SA) and ampicillin-nonsusceptible enterococci, and cerebrospinal fluid that yielded SA. The anti-MRSA use rate is the total antimicrobial days of ceftaroline, dalbavancin, daptomycin, linezolid, oritavancin, quinupristin/dalfopristin, tedizolid, telavancin, and intravenous vancomycin per 1,000 days patients were present. AU rates were modeled using negative binomial regression assessing its association with infection burden and hospital characteristics. Results: Among 182 hospitals, the median (interquartile range, IQR) of anti-MRSA use rate was 86.3 (59.9–105.0), and the median (IQR) prevalence of drug-resistant gram-positive infections was 3.4 (2.1–4.8). Higher prevalence of drug-resistant gram-positive infections was associated with higher use of anti-MRSA agents after adjusting for facility type and percentage of beds in intensive care units (Table 1). Number of hospital beds, average length of stay, and medical school affiliation were nonsignificant. Conclusions: Prevalence of drug-resistant gram-positive infections was independently associated with the use of anti-MRSA agents. Infection burden should be used for risk adjustment in predicting the use of anti-MRSA agents. To make this possible, we recommend that hospitals reporting to NHSN’s AU Option also report microbiologic culture results.Funding: NoneDisclosures: None

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Healthcare-associated bloodstream infection trends under a provincial surveillance program

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2018.357 ◽

2019 ◽

Vol 40 (3) ◽

pp. 307-313

Author(s):

Iman Fakih ◽

Élise Fortin ◽

Marc-André Smith ◽

Alex Carignan ◽

Claude Tremblay ◽

...

Keyword(s):

Bloodstream Infection ◽

Bloodstream Infections ◽

Surveillance Program ◽

First Year ◽

Period Effect ◽

Surveillance Period ◽

Year Effect ◽

Rate Ratios ◽

Tract Infections ◽

Healthcare Associated

AbstractObjective:BACTOT, Quebec’s healthcare-associated bloodstream infection (HABSI) surveillance program has been operating since 2007. In this study, we evaluated the changes in HABSI rates across 10 years of BACTOT surveillance under a Bayesian framework.Design:A retrospective, cohort study of eligible hospitals having participated in BACTOT for at least 3 years, regardless of their entry date. Multilevel Poisson regressions were fitted independently for cases of HABSI, catheter-associated bloodstream infections (CA-BSIs), non–catheter-associated primary BSIs (NCA-BSIs), and BSIs secondary to urinary tract infections (BSI-UTIs) as the outcome and log of patient days as the offset. The log of the mean Poisson rate was decomposed as the sum of a surveillance year effect, period effect, and hospital effect. The main estimate of interest was the cohort-level rate in years 2–10 of surveillance relative to year 1.Results:Overall, 17,479 cases and 33,029,870 patient days were recorded for the cohort of 77 hospitals. The pooled 10-year HABSI rate was 5.20 per 10,000 patient days (95% CI, 5.12–5.28). For HABSI, CA-BSI, and BSI-UTI, there was no difference between the estimated posterior rates of years 2–10 compared to year 1. The posterior means of the NCA-BSI rate ratios increased from the seventh year until the tenth year, when the rate was 29% (95% confidence interval, 1%–89%) higher than the first year rate.Conclusions:HABSI rates and those of the most frequent subtypes remained stable over the surveillance period. To achieve reductions in incidence, we recommend that more effort be expended in active interventions against HABSI alongside surveillance.

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171. The Impact of COVID-19 on Healthcare-Associated Infections

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab466.171 ◽

2021 ◽

Vol 8 (Supplement_1) ◽

pp. S102-S103

Author(s):

Meghan A Baker ◽

Kenneth Sands ◽

Susan S Huang ◽

Ken Kleinman ◽

Edward Septimus ◽

...

Keyword(s):

Nursing Homes ◽

Negative Binomial ◽

Bloodstream Infections ◽

Local Variation ◽

Healthcare Associated Infections ◽

Material Support ◽

Cleaning Products ◽

Tract Infections ◽

Healthcare Associated ◽

The Impact

Abstract Background The profound changes wrought by COVID-19 on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). Objective Evaluate the association between COVID-19 surges and HAI or cluster rates Methods Design: Prospective cohort study Setting 148 HCA Healthcare-affiliated hospitals, 3/1/2020-9/30/2020, and a subset of hospitals with microbiology and cluster data through 12/31/2020 Patients All inpatients Measurements We evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month at each hospital. Results Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased (P ≤ 0.001 for all), with 60% (95% CI, 23 to 108%) more CLABSI, 43% (95% CI, 8 to 90%) more CAUTI, and 44% (95% CI, 10 to 88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection (CDI) was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus and Gram-negative organisms were each significantly associated with COVID-19 surges (P < 0.05 for all). Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased (P = 0.02). Limitations Variations in surveillance and reporting may affect HAI data. Table 1. Effect of an increase in number of COVID-19 discharges on HAIs and hospital-onset pathogens Figure 1. Predicted mean HAI rates as COVID-19 discharges increase Predicted mean HAI rate by increasing monthly COVID-19 discharges. Panel a. CLABSI, Panel b, CAUTI Panel c. MRSA Bacteremia, Panel d. CDI. Data are stratified by small, medium and large hospitals. Figure 2. Monthly comparison of COVID discharges to clusters COVID-19 discharges and the number of clusters of hospital-onset pathogens are correlated throughout the pandemic. Conclusion COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention. Disclosures Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Eunice J. Blanchard, MSN RN, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Deborah S. Yokoe, MD, MPH, Nothing to disclose Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)

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Colonization and Infection With MRSA and CRKP and Its Result in an Increased Mortality Rate Within the Intensive Care and High-Dependency Units in Barbados

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.703 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s173-s174

Author(s):

Keisha Gustave

Keyword(s):

Intensive Care ◽

Length Of Stay ◽

High Mortality ◽

Average Length ◽

Cohort Analysis ◽

Health Concern ◽

Queen Elizabeth Hospital ◽

Surveillance Program ◽

Average Length Of Stay ◽

High Dependency

Background: Methicillin-resistant Staphylococcus aureus(MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) are a growing public health concern in Barbados. Intensive care and critically ill patients are at a higher risk for MRSA and CRKP colonization and infection. MRSA and CRKP colonization and infection are associated with a high mortality and morbidly rate in the intensive care units (ICUs) and high-dependency units (HDUs). There is no concrete evidence in the literature regarding MRSA and CRKP colonization and infection in Barbados or the Caribbean. Objectives: We investigated the prevalence of MRSA and CRKP colonization and infection in the patients of the ICU and HDU units at the Queen Elizabeth Hospital from 2013 to 2017. Methods: We conducted a retrospective cohort analysis of patients admitted to the MICU, SICU, and HDU from January 2013 through December 2017. Data were collected as part of the surveillance program instituted by the IPC department. Admissions and weekly swabs for rectal, nasal, groin, and axilla were performed to screen for colonization with MRSA and CRKP. Follow-up was performed for positive cultures from sterile isolates, indicating infection. Positive MRSA and CRKP colonization or infection were identified, and patient notes were collected. Our exclusion criteria included patients with a of stay of <48 hours and patients with MRSA or CRKP before admission. Results: Of 3,641 of persons admitted 2,801 cases fit the study criteria. Overall, 161 (5.3%) were colonized or infected with MRSA alone, 215 (7.67%) were colonized or infected with CRKP alone, and 15 (0.53%) were colonized or infected with both MRSA and CRKP. In addition, 10 (66.6%) of patients colonized or infected with MRSA and CRKP died. Average length of stay of patients who died was 50 days. Conclusions: The results of this study demonstrate that MRSA and CRKP cocolonization and coinfection is associated with high mortality in patients within the ICU and HDU units. Patients admitted to the ICU and HDU with an average length of stay of 50 days are at a higher risk for cocolonization and coinfection with MRSA and CRKP. Stronger IPC measures must be implemented to reduce the spread and occurrence of MRSA and CRKP.Funding: NoneDisclosures: None

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Temporal Changes in Central-Line–Associated Bloodstream Infection Time Between Events, 2017–2018 Versus 2015–2016

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1051 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s403-s404

Author(s):

Jonathan Edwards ◽

Katherine Allen-Bridson ◽

Daniel Pollock

Keyword(s):

Length Of Stay ◽

Patient Care ◽

Average Length ◽

Bloodstream Infections ◽

Central Line ◽

Significant Shift ◽

Care Hospital ◽

Average Length Of Stay ◽

Period 2 ◽

Hospital Bed

Background: The CDC NHSN surveillance coverage includes central-line–associated bloodstream infections (CLABSIs) in acute-care hospital intensive care units (ICUs) and select patient-care wards across all 50 states. This surveillance enables the use of CLABSI data to measure time between events (TBE) as a potential metric to complement traditional incidence measures such as the standardized infection ratio and prevention progress. Methods: The TBEs were calculated using 37,705 CLABSI events reported to the NHSN during 2015–2018 from medical, medical-surgical, and surgical ICUs as well as patient-care wards. The CLABSI TBE data were combined into 2 separate pairs of consecutive years of data for comparison, namely, 2015–2016 (period 1) and 2017–2018 (period 2). To reduce the length bias, CLABSI TBEs were truncated for period 2 at the maximum for period 1; thereby, 1,292 CLABSI events were excluded. The medians of the CLABSI TBE distributions were compared over the 2 periods for each patient care location. Quantile regression models stratified by location were used to account for factors independently associated with CLABSI TBE, such as hospital bed size and average length of stay, and were used to measure the adjusted shift in median CLABSI TBE. Results: The unadjusted median CLABSI TBE shifted significantly from period 1 to period 2 for the patient care locations studied. The shift ranged from 20 to 75.5 days, all with 95% CIs ranging from 10.2 to 32.8, respectively, and P < .0001 (Fig. 1). Accounting for independent associations of CLABSI TBE with hospital bed size and average length of stay, the adjusted shift in median CLABSI TBE remained significant for each patient care location that was reduced by ∼15% (Table 1). Conclusions: Differences in the unadjusted median CLABSI TBE between period 1 and period 2 for all patient care locations demonstrate the feasibility of using TBE for setting benchmarks and tracking prevention progress. Furthermore, after adjusting for hospital bed size and average length of stay, a significant shift in the median CLABSI TBE persisted among all patient care locations, indicating that differences in patient populations alone likely do not account for differences in TBE. These findings regarding CLABSI TBEs warrant further exploration of potential shifts at additional quantiles, which would provide additional evidence that TBE is a metric that can be used for setting benchmarks and can serve as a signal of CLABSI prevention progress.Funding: NoneDisclosures: None

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Systemic Determinants in Surgery: Nonclinical Factors Affecting Time to Operation for Incarcerated Ventral Hernias

The American Surgeon ◽

10.1177/00031348211011118 ◽

2021 ◽

pp. 000313482110111

Author(s):

David E. Wang ◽

Paul J. Chung ◽

Rafael Barrera ◽

Gene F. Coppa ◽

Antonio E. Alfonso ◽

...

Keyword(s):

Operating Room ◽

Negative Binomial ◽

Private Insurance ◽

Negative Binomial Regression ◽

Outcome Variable ◽

Hospital Size ◽

Factors Affecting ◽

Binomial Regression ◽

Comorbidity Status ◽

Ventral Hernias

Introduction We explore nonclinical factors affecting the amount of time from admission to the operating room for patients requiring nonelective repair of ventral hernias. Methods Using the 2005-2012 Nationwide Inpatient Sample, we identified adult patients with a primary diagnosis of ventral hernia without obstruction/gangrene, who underwent nonelective repair. The outcome variable of interest was time from admission to surgery. We performed univariate and multivariable analyses using negative binomial regression, adjusting for age, sex, race, income, insurance, admission day, comorbidity status (van Walraven score), diagnosis, procedure, hospital size, location/teaching status, and region. Results 7,253 patients met criteria, of which majority were women (n = 4,615) and white (n = 5,394). The majority of patients had private insurance (n = 3,015) followed by Medicare (n = 2,737). Median time to operation was 0 days. Univariate analysis comparing operation <1 day to ≥1 day identified significant differences in race, day of admission, insurance, length of stay, comorbidity status, hospital location, type, and size. Negative binomial regression showed that weekday admission (IRR 4.42, P < .0001), private insurance (IRR 1.53-2.66, P < .0001), rural location (IRR 1.39-1.76, P < .01), small hospital size (IRR 1.26-1.36, P < .05), white race (IRR 1.30-1.34, P < .01), healthier patients (van Walraven score IRR 1.05, P < .0001), and use of mesh (IRR 0.39-0.56, P < .02) were associated with shorter time until procedure. Conclusion Shorter time from admission to the operating room was associated with several nonclinical factors, which suggest disparities may exist. Further prospective studies are warranted to elucidate these disparities affecting patient care.

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Times of change in complex environments - Evaluating hospital co-payments in Palestine refugee camps

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.1252 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

S V Valente de Almeida ◽

H Ghattas ◽

G Paolucci ◽

A Seita

Keyword(s):

Length Of Stay ◽

Policy Change ◽

Negative Binomial ◽

Negative Impact ◽

Average Length ◽

Lessons Learned ◽

Policy Impact ◽

Average Length Of Stay ◽

Ex Post ◽

The Impact

Abstract We measure the impact introducing a of 10% co-payment component on hospitalisation costs for Palestine refugees from Lebanon in public and private hospitals. This ex-post analysis provides a detailed insight on the direction and magnitude of the policy impact in terms of demand and supply for healthcare. The data was collected by the United Nations Relief and Works Agency for Palestine Refugees in the Near East and include episode level information from all public, private and Red Crescent Hospitals in Lebanon, between April 2016 and October 2017. This is a complete population episode level dataset with information from before and after the policy change. We use multinomial logit, negative binomial and linear models to estimate the policy impact on demand by type of hospital, average length of stay and treatment costs for the patient and the provider. After the new policy was implemented patients were 18% more likely to choose a (free-of-charge) PRCS hospital for secondary care, instead of a Private or Public hospital, where the co-payment was introduced. This impact was stronger for episodes with longer stays, which are also the more severe and more expensive cases. Average length of stay decreased in general for all hospitals and we could not find a statistically significant impact on costs for the provider nor the patient. We find evidence that the introduction of co-payments is hospital costs led to a shift in demand, but it is not clear to what extent the hospitals receiving this demand shift were prepared for having more patients than before, also because these are typically of less quality then the others. Regarding costs, there is no evidence that the provider managed to contain costs with the new policy, as the demand adapted to the changes. Our findings provide important information on hospitalisation expenses and the consequences of a policy change from a lessons learned perspective that should be taken into account for future policy decision making. Key messages We show that in a context of poverty, the introduction of payment for specific hospital types can be efficient for shifting demand, but has doubtable impact on costs containment for the provider. The co-payment policy can have a negative impact on patients' health since after its implementation demand increased at free-of-charge hospitals, which typically have less resources to treat patients.

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Healthcare-Associated Infection in Italy Annual Point-Prevalence Surveys, 2002–2004

Infection Control and Hospital Epidemiology ◽

10.1086/597596 ◽

2009 ◽

Vol 30 (7) ◽

pp. 659-665 ◽

Cited By ~ 21

Author(s):

Simone Lanini ◽

William R. Jarvis ◽

Emanuele Nicastri ◽

Gaetano Privitera ◽

Giovanni Gesu ◽

...

Keyword(s):

Intensive Care ◽

Intensive Care Units ◽

Univariate Analysis ◽

National Health System ◽

Bloodstream Infections ◽

Surgical Site Infections ◽

Point Prevalence ◽

Healthcare Associated Infection ◽

Tract Infections ◽

Healthcare Associated

Objective.Healthcare-associated infections (HAIs) are an important cause of morbidity and mortality worldwide. During the period from 2002 through 2004, a group of Italian hospitals was recruited to conduct HAI point-prevalence surveys.Design.Three point-prevalence surveys.Methods.A total of 9,609 patients were surveyed.Results.The overall frequency of HAI was 6.7% (645 infections among the 9,609 surveyed patients). The most frequent HAIs were lower respiratory tract infections, which accounted for 35.8% (231 of 645 HAIs) of all HAIs, followed by urinary tract infections (152 [23.6%] of 645 HAIs), bloodstream infections (90 [14.0%] of 645 HAIs), and surgical site infections (79 [12.2%] of 645 HAIs). In both multivariate and univariate analysis, invasive procedures, duration of stay, chemotherapy, trauma, coma, and the location of the hospital were all factors statistically significantly associated with the occurrence of an HAL Enterobacteriaceae were the most common isolates recovered in medical and surgical wards, whereas gram-negative aerobic bacilli were the most common isolates recovered in intensive care units. Approximately one-half of all of the patients surveyed were receiving antibiotics at the time of our study; the most used antibiotic classes were fluoroquinolones in medical wards, cephalosporins in surgical wards, and penicillins and glycopeptides in intensive care units.Conclusion.Our study emphasizes the need for implementing further HAI surveillance to provide the National Health System with proper tools to prevent and manage infection in hospitalized patients.

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Healthcare-associated Infections in Pediatric Cardiovascular Surgery Intensive Care Unit between 2016-2020

Kosuyolu Heart Journal ◽

10.51645/khj.2021.m125 ◽

2021 ◽

Author(s):

Mehmet Emirhan Işık ◽

Ergin Arslanoğlu ◽

Ömer Faruk Şavluk ◽

Hakan Ceyran

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Cardiovascular Surgery ◽

Heart Diseases ◽

Bloodstream Infections ◽

Healthcare Associated Infections ◽

Developmental Problems ◽

Pediatric Cardiovascular Surgery ◽

Tract Infections ◽

Healthcare Associated

Objectives: Healthcare-associated infections are the most common problem in intensive care unit worldwide. Children with congenital heart diseases have many complications such as developmental problems, respiratory tract infections, endocarditis,pneumonia and after long-term hospital and intensive care stays and surgeries patients become vulnerable to healthcare-associated infections. Patients and Methods: The study presents the frequency of infection, microorganisms in patients hospitalized at SBÜ Koşuyolu High Spesialization Research and Training Hospital pediatric cardiovascular surgery intensive care unit between 2016-2020. Results: One hundred-eight HAI episodes were seen in 83 of 1920 patients hospitalized in pediatric cardiovascular surgery intensive care unit between 2016-2020.HAI rates varied between 4.8% and 7.77%. In the 5-year period,a total of 118 different microorganisms were detected.Among all microorganisms, Candida species (n: 43, 36.4%) ranked first. central line-associated bloodstream infections (CLABSI) 53 (49%), ventilator-associated pneumonia (VAP)40 (37%), surgical site infection (SSI) 8 (6.5%), catheter -associated urinary tract infection (CAUTI) 7 (6%) Conclusion: Healthcare-associated infections are require special attention in pediatric cardiovascular intensive care units. In order to prevent, innovations such as bundle applications should be implemented as well as personnel training.

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Costs of ambulatory pediatric healthcare-associated infections: Central-line–associated bloodstream infection (CLABSIs), catheter-associated urinary tract infection (CAUTIs), and surgical site infections (SSIs)

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.305 ◽

2020 ◽

Vol 41 (11) ◽

pp. 1292-1297

Author(s):

Michael L. Rinke ◽

Suzette O. Oyeku ◽

William J. H. Ford ◽

Moonseong Heo ◽

Lisa Saiman ◽

...

Keyword(s):

Urinary Tract ◽

Ambulatory Surgery ◽

Bloodstream Infections ◽

Surgical Site Infections ◽

Central Line ◽

Healthcare Associated Infections ◽

Retrospective Case ◽

Additional Costs ◽

Tract Infections ◽

Healthcare Associated

AbstractObjective:Ambulatory healthcare-associated infections (HAIs) occur frequently in children and are associated with morbidity. Less is known about ambulatory HAI costs. This study estimated additional costs associated with pediatric ambulatory central-line–associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTI), and surgical site infections (SSIs) following ambulatory surgery.Design:Retrospective case-control study.Setting:Four academic medical centers.Patients:Children aged 0–22 years seen between 2010 and 2015 and at risk for HAI as identified by electronic queries.Methods:Chart review adjudicated HAIs. Charges were obtained for patients with HAIs and matched controls 30 days before HAI, on the day of, and 30 days after HAI. Charges were converted to costs and 2015 USD. Mixed-effects linear regression was used to estimate the difference-in-differences of HAI case versus control costs in 2 models: unrecorded charge values considered missing and a sensitivity analysis with unrecorded charge considered $0.Results:Our search identified 177 patients with ambulatory CLABSIs, 53 with ambulatory CAUTIs, and 26 with SSIs following ambulatory surgery who were matched with 382, 110, and 75 controls, respectively. Additional cost associated with an ambulatory CLABSI was $5,684 (95% confidence interval [CI], $1,005–$10,362) and $6,502 (95% CI, $2,261–$10,744) in the 2 models; cost associated with a CAUTI was $6,660 (95% CI, $1,055, $12,145) and $2,661 (95% CI, −$431 to $5,753); cost associated with an SSI following ambulatory surgery at 1 institution only was $6,370 (95% CI, $4,022–$8,719).Conclusions:Ambulatory HAI in pediatric patients are associated with significant additional costs. Further work is needed to reduce ambulatory HAIs.

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