Healthcare-Associated Infections In Acute Care Hospitals Research Articles

Validation of the prevalence to incidence conversion method for healthcare associated infections in long-term care facilities.

Residents of long-term care facilities (LTCFs) are a population at high risk of developing severe healthcare associated infections (HAIs). In the assessment of HAIs in acute-care hospitals, selection bias can occur due to cases being over-represented: patients developing HAIs usually have longer lengths of stays compared to controls, and therefore have an increased probability of being sampled in PPS, leading to an overestimation of HAI prevalence. Our hypothesis was that in LTCFs, the opposite may occur: residents developing HAIs either may have a greater chance of being transferred to acute-care facilities or of dying, and therefore could be under-represented in PPS, leading to an underestimation of HAI prevalence. Our aim was to test this hypothesis by comparing HAI rates obtained through longitudinal and cross-sectional studies. Results from two studies conducted simultaneously in four LTCFs in Italy were compared: a longitudinal study promoted by the European Centre for Disease Prevention and Control (ECDC, HALT4 longitudinal study, H4LS), and a PPS. Prevalence was estimated from the PPS and converted into incidence per year using an adapted version of the Rhame and Sudderth formula proposed by the ECDC. Differences between incidence rates calculated from the PPS results and obtained from H4LS were investigated using the Byar method for rate ratio (RR). On the day of the PPS, HAI prevalence was 1.47% (95% confidence interval, CI 0.38-3.97), whereas the H4LS incidence rate was 3.53 per 1000 patient-days (PDs, 95% CI 2.99-4.08). Conversion of prevalence rates obtained through the PPS into incidence using the ECDC formula resulted in a rate of 0.86 per 1000 PDs (95% CI 0-2.68). Comparing the two rates, a RR of 0.24 (95% CI 0.03-2.03, p 0.1649) was found. This study did not find significant differences between HAI incidence estimates obtained from a longitudinal study and through conversion from PPS data. Results of this study support the validity of the ECDC method.

Introduction to A Compendium of Strategies to Prevent Healthcare-Associated Infections In Acute-Care Hospitals: 2022 Updates.

Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients, leading to substantial morbidity, mortality, and excess healthcare expenditures, and persistent gaps remain between what is recommended and what is practiced.The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others.

Healthcare-associated infections and conditions in the era of digital measurement.

As the third edition of the Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute CareHospitals is released with the latest recommendations for the prevention and management of healthcare-associated infections (HAIs), a new approach to reporting HAIs is just beginning to unfold. This next generation of HAI reporting will be fully electronic and based largely on existing data in electronic health record (EHR) systems and other electronic data sources. It will be a significant change in how hospitals report HAIs and how the Centers for Disease Control and Prevention (CDC) and other agencies receive this information. This paper outlines what that future electronic reporting system will look like and how it will impact HAI reporting.

Executive Summary: A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute-Care Hospitals: 2022 Updates.

Executive Summary: A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute-Care Hospitals: 2022 Updates.

National Trends of Prevalence of Fluroquinolone Resistance Among Healthcare-Associated Escherichia coli Infections

Background:Escherichia coli is the third most common pathogen responsible for healthcare-associated infections (HAIs), but it is increasingly resistant to multiple antibiotics. Antimicrobial susceptibility test (AST) results for fluoroquinolones (FQs) among E. coli implicated in select HAIs are reported to the NHSN surveillance system. Trend analyses in the prevalence of FQ resistance among healthcare-associated E. coli infections reported to NHSN have not been previously assessed. Objective: We investigated the national trends of prevalence of FQ resistance among E. coli HAIs in acute-care hospitals from 2009 through 2018. Method: We analyzed E. coli AST data from central-line–associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), and surgical site infections (SSIs) reported to the NHSN between 2009 and 2018. Fluoroquinolone resistance is defined as the number of E. coli isolates that tested resistant or intermediate to at least 1 of 3 quinolones (ciprofloxacin, levofloxacin, and moxifloxacin), divided by number of pathogens tested for susceptibility, multiplied by 100. To evaluate the trends of fluoroquinolone resistance over time, we conducted an interrupted time-series analysis using a generalized linear mixed model with a logistic function. Substantial HAI definitional changes, most consequentially CAUTI in 2015 and a directional incidence change in 2018, were treated as interruptions to the outcome. Regression models adjusted for patient-level (ie, age, gender, HAI type) and facility-level characteristics (ie, facility type, teaching status, number of beds in intensive care units, and average length of stay) were obtained from the NHSN annual hospital surveys. Random-intercept and slope models were evaluated with covariance tests and were included to account for differential baseline fluoroquinolone resistance and trends among reporting facilities. Data were analyzed using SAS with statistical significance defined at alpha = 0.05. Results: During 2009–2018, the number of E. coli isolates with AST results for FQ reported to NHSN (Fig. 1) increased. After adjusting for covariates, fluoroquinolone resistance significantly increased from 2009 through 2015 at an average of 4.2% per year (Fig. 2, β1). There was no significant change in fluoroquinolone resistance from 2015 through 2017 (Fig. 2, β1+ β3). In 2018, there was 6.4% decline in fluoroquinolone resistance compared to 2017 (Fig. 2, β4) Conclusions: An increasing trend of fluoroquinolone resistance from 2009 through 2015 was observed, and fluoroquinolone resistance was stable during 2015–2017. Despite a relatively brief decline in fluoroquinolone resistance in 2018, the absolute change was small (~2%). Sustaining this decline warrants continued efforts in infection prevention and antimicrobial stewardship.Funding: NoneDisclosures: None

Pilot Survey for National Point Prevalence Study of Healthcare-Associated Infections in Acute-Care Hospitals in South Korea

Background: The Korean National Healthcare-Associated Infections Surveillance System (KONIS) was established to conduct nationwide surveillance of device-associated healthcare-associated infections (HAIs) and surgical site infections annually in 2006. However, no surveillance on overall HAIs has been conducted. Objective: We conducted a point-prevalence survey of total HAIs to estimate the incidence rate of HAIs in acute-care hospitals in South Korea. Methods: We defined HAIs according to KONIS and NHSN criteria. In total, 29 acute-care hospitals including 9 tertiary-care hospitals (TCHs) and 20 secondary-care hospitals (SCHs) were recruited as representing the population of every metropolitan city and province in South Korea. Patients who stayed at the hospitals on August 1, 2018, were randomly selected: 100 for SCHs and 200 for TCHs. Their medical records were retrospectively reviewed for HAIs according to the NHSN criteria by the infection control nurses (ICNs) from each hospital. A web-based data collection and analysis program was developed, and participating ICNs were educated in a 1-day training course with pre- and postevaluations. They received continuous feedback of input data and questions through the web-based system during the study. To generate estimates of the incidence rate of HAIs, we converted prevalence to incidence using the formula of Rhame and Sudderth. Results: Of 4,296 patients, 133 had ≥1 HAI (3.1%). In total, 141 HAIs were identified: gastrointestinal infections (n = 30, 21.3%), bloodstream infections (n = 30, 21.3%), pneumonia (n = 29, 20.6%), urinary tract infection (n =26, 18.4%). Among the gastrointestinal infections, C. difficile infections were the most common (17.7%). Device-associated infections accounted for 34.8% of all HAIs. The overall incidence of HAIs in TCHs was 4.39%, which was a higher incidence than SCHs (3.76%). Intensive care units had 12.6% of HAIs, whereas general wards had 3.4%. HAI incidences were 5.7%, 2.8%, and 2.3%, respectively, for each of the medical wards, surgical wards, and pediatric wards. The 3 most common pathogens were Escherichia coli, Acinetobacter baumannii, and Enterococcus faecium. Conclusions: The prevalence of HAI in Korea is lower than in most Western countries. The HAI burden of Clostridium difficile infection is surprisingly high, which calls for prompt control at the national level. To obtain national-level data on HAI burdens, ongoing surveillance is needed.Funding: NoneDisclosures: None

2182. Perceived Impact of Mandatory Reporting of Healthcare-Associated Infections on Infection Prevention and Control Departments in Acute Care Hospitals

BackgroundThe Centers for Medicare and Medicaid Services (CMS) requires hospitals to report healthcare-associated infections (HAIs) through the Hospital Inpatient Quality Reporting Program. Facilitated by the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN), mandatory reporting aims to improve quality by benchmarking and improving transparency. In addition, the majority of U.S. states have policies in place for mandatory reporting of HAIs in acute care hospitals. The aim of this study was to examine Infection Preventionists’ perceptions of the impact of mandatory reporting on infection prevention and control (IPC) departments.MethodsIn Winter of 2018, we electronically surveyed IPs working in acute care hospitals. The survey was distributed by the Association of Professionals in Infection Prevention and Epidemiology (APIC) to its members via an initial email and weekly e-blasts over a 6-week period. Descriptive statistics were conducted and themes from open-ended questions were analyzed to describe IP perceptions of mandatory reporting.ResultsThere were 255 IPs who completed the survey; 187 IPs provided responses in the mandatory reporting section. Half (53%) reported that mandatory reporting resulted in more influence of the IPC department on hospital decision making and 38% reported increased visibility. The most important benefit of mandatory reporting was increased awareness of IPC for hospital administrators (42%), followed by transparency of outcomes for patients and providers (28%). However, a third of IPs reported less time for staff education and routine IPC activities. IPs also reported an increased workload and lack of action based on the results of the reports as drawbacks of reporting mandates.ConclusionAccording to IPs, mandatory reporting has resulted in increased visibility and awareness of IPC in acute care hospitals, however, some drawbacks were also identified. Given CMS and state mandates for HAI reporting, policy makers need to be attuned to additional demands placed on hospitals to comply with mandatory reporting processes. Future research should aim to examine whether IPC departments have sufficient resources to comply with these regulatory policies and ways in which to improve the reporting process.Disclosures All authors: No reported disclosures.

Risk factors for death in a cohort of patients with and without healthcare-associated infections in Finnish acute care hospitals

We evaluated risk factors for death among hospitalised patients with healthcare-associated infections (HCAIs) using the McCabe classification and Charlson index to predict mortality. The study consisted of a cohort of 703 patients with HCAIs and 7531 patients without HCAI in acute care hospitals participating in the Finnish national prevalence survey in 2005. We used Centers for Disease Control and Prevention definitions for HCAIs and recorded the McCabe classification for comorbidity. We used the date from the prevalence survey and the patient's national identity code in order to retrieve data from the National Hospital Discharge Registry on discharge diagnoses (International Classification of Diseases-10 codes) for the Charlson index and the dates of death from the National Population Information System. Of all inpatients, 425 (5.2%) died within 28 days from the prevalence survey date; the death rate was higher in HCAI patients than in those without HCAI (9.8% vs 4.7%, P<0.001). In the multivariate regression analysis age >65 years, intensive care, McCabe classification and Charlson index, gastrointestinal system infection and pneumonia/other lower respiratory tract infections were independent predictors for death. The survival analysis, when adjusted by McCabe class or Charlson index, showed that HCAI reduced survival only among patients without severe underlying diseases. Certain types of HCAI increased the risk of death. The McCabe classification had advantages over the Charlson index as a predictor of death, because it was easier to collect from a prevalence survey.