The Impact of Healthcare-Associated Infection on Mortality: Failure in Clinical Recognition Is Related with Inadequate Antibiotic Therapy

OBJECTIVETo facilitate surveillance and describe the burden of healthcare-associated infection (HAI) in nursing homes (NHs), we compared the quality of resident-level data collected by NH personnel and external staff.DESIGNA 1-day point-prevalence surveySETTING AND PARTICIPANTSOverall, 9 nursing homes among 4 Centers for Disease Control and Prevention (CDC) Emerging Infection Program (EIP) sites were included in this study.METHODSNH personnel collected data on resident characteristics, clinical risk factors for HAIs, and the presence of 3 HAI screening criteria on the day of the survey. Trained EIP surveillance officers collected the same data elements via retrospective medical chart review for comparison; surveillance officers also collected available data to identify HAIs (using revised McGeer definitions). Overall agreement was calculated among residents identified by both teams with selected risk factors and HAI screening criteria. The impact of using NH personnel to collect screening criteria on HAI prevalence was assessed.RESULTSThe overall prevalence of clinical risk factors among the 1,272 residents was similar between NH personnel and surveillance officers, but the level of positive agreement (residents with factors identified by both teams) varied between 39% and 87%. Surveillance officers identified 253 residents (20%) with ≥1 HAI screening criterion, resulting in 67 residents with an HAI (5.3 per 100 residents). The NH personnel identified 152 (12%) residents with ≥1 HAI screening criterion; 42 residents had an HAI (3.5 per 100 residents).CONCLUSIONWe identified discrepancies in resident-level data collection between surveillance officers and NH personnel, resulting in varied estimates of the HAI prevalence. These findings have important implications for the design and implementation of future HAI prevalence surveys.Infect Control Hosp Epidemiol 2016;1440–1445

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Are Invasive Procedures and a Longer Hospital Stay Increasing the Risk of Healthcare-Associated Infections among the Admitted Patients at Hiwot Fana Specialized University Hospital, Eastern Ethiopia?

Advances in Preventive Medicine ◽

10.1155/2020/6875463 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Moti Tolera ◽

Dadi Marami ◽

Degu Abate ◽

Merga Dheresa

Keyword(s):

Cigarette Smoking ◽

Hospital Stay ◽

University Hospital ◽

Infection Prevention And Control ◽

Healthcare Associated Infections ◽

Invasive Procedures ◽

Healthcare Associated Infection ◽

Eastern Ethiopia ◽

Healthcare Associated ◽

The Impact

Background. Healthcare-associated infection is a major public health problem, in terms of mortality, morbidity, and costs. Majorities of the cause of these infections were preventable. Understanding the potential risk factors is important to reduce the impact of these avoidable infections. The study was aimed to identify factors associated with healthcare-associated infections among patients admitted at Hiwot Fana Specialized University Hospital, Harar, Eastern Ethiopia. Methods. A cross-sectional study was carried out among 433 patients over a period of five months at Hiwot Fana Specialized University Hospital. Sociodemographic and clinical data were obtained from a patient admitted for 48 hours and above in the four wards (surgical, medical, obstetrics/gynecology, and pediatrics) using a structured questionnaire. A multivariate logistic regression model was applied to identify predictors of healthcare-associated infections. A p value <0.05 was considered statistically significant. Results. Fifty-four (13.7%) patients had a history of a previous admission. The median length of hospital stay was 6.1 days. Forty-six (11.7%) participants reported comorbid conditions. Ninety-six (24.4%) participants underwent surgical procedures. The overall prevalence of healthcare-associated infection was 29 (7.4%, 95% CI: 5.2–10.6). Cigarette smoking (AOR: 5.18, 95% CI: 2.15–20.47), staying in the hospital for more than 4 days (AOR: 4.29, 95% CI: 2.31–6.15), and undergoing invasive procedures (AOR: 3.58, 95% CI: 1.11–7.52) increase the odds of acquiring healthcare-associated infections. Conclusion. The cumulative prevalence of healthcare-associated infections in this study was comparable with similar studies conducted in developing countries. Cigarette smoking, staying in the hospital for more than 4 days, and undergoing invasive procedures increase the odds of healthcare-associated infections. These factors should be considered in the infection prevention and control program of the hospital.

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Trends of Healthcare-associated Infections in a Tuinisian University Hospital and Impact of COVID-19 Pandemic

INQUIRY The Journal of Health Care Organization Provision and Financing ◽

10.1177/00469580211067930 ◽

2021 ◽

Vol 58 ◽

pp. 004695802110679

Author(s):

Hela Ghali ◽

Asma Ben Cheikh ◽

Sana Bhiri ◽

Selwa Khefacha ◽

Houyem Said Latiri ◽

...

Keyword(s):

Risk Factors ◽

Urinary Tract ◽

Protective Factor ◽

Bloodstream Infections ◽

Point Prevalence ◽

University Hospital ◽

Healthcare Associated Infection ◽

Tract Infections ◽

Healthcare Associated ◽

The Impact

Background Although efforts to manage coronavirus disease 2019 (COVID-19) pandemic have understandably taken immediate priority, the impacts on traditional healthcare-associated infection (HAI) surveillance and prevention efforts remain concerning. Aim To describe trends in HAIs in a Tunisian university hospital through repeated point prevalence surveys over 9 years, assess the impact of measures implemented for COVID-19 pandemic, and to identify associated factors of HAI. Methods The current study focused on data collected from annual point prevalence surveys conducted from 2012 to 2020. All types of HAIs as defined by the Centers for Disease Control and Prevention (CDC) were included. Data collection was carried out using NosoTun plug. Univariate and multivariate logistic analysis were used to identify HAI risk factors. Results Overall, 2729 patients were observed in the 9 surveys; the mean age was 48.3 ± 23.3 years and 57.5% were male. We identified 267 infected patients (9.8%) and 296 HAIs (10.8%). Pneumonia/lower respiratory tract infections were the most frequent HAI (24%), followed by urinary tract infection (20.9%).The prevalence of infected patients increased from 10.6% in 2012 to 14.9% in 2020. However, this increase was not statistically significant. The prevalence of HAIs increased significantly from 12.3% to 15.5% ( P =.003). The only decrease involved is bloodstream infections (from 2% to 1%). Independent risk factors significantly associated with HAI were undergoing surgical intervention (aOR = 1.7), the use of antibiotic treatment in previous 6 months (aOR = 1.8), peripheral line (aOR=2), parenteral nutrition (aOR=2.4), urinary tract within 7 days (aOR=2.4), central line (aOR = 6.3), and prosthesis (aOR = 12.8), length of stay (aOR = 3), and the year of the survey. Young age was found as protective factor (aOR = .98). Conclusion Contrary to what was expected, we noticed an increase in the HAIs rates despite the preventive measures put in place to control the COVID-19 pandemic. This was partly explained by the vulnerability of hospitalized patients during this period.

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The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: A summary of data reported to the National Healthcare Safety Network

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2021.362 ◽

2021 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Lindsey M. Weiner-Lastinger ◽

Vaishnavi Pattabiraman ◽

Rebecca Y. Konnor ◽

Prachi R. Patel ◽

Emily Wong ◽

...

Keyword(s):

State Level ◽

Bloodstream Infections ◽

Surgical Site Infections ◽

Infection Prevention And Control ◽

Healthcare Associated Infection ◽

National Healthcare ◽

National Healthcare Safety Network ◽

Tract Infections ◽

Healthcare Associated ◽

The Impact

Abstract Objectives: To determine the impact of the coronavirus disease 2019 (COVID-19) pandemic on healthcare-associated infection (HAI) incidence in US hospitals, national- and state-level standardized infection ratios (SIRs) were calculated for each quarter in 2020 and compared to those from 2019. Methods: Central–line–associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated events (VAEs), select surgical site infections, and Clostridioides difficile and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia laboratory-identified events reported to the National Healthcare Safety Network for 2019 and 2020 by acute-care hospitals were analyzed. SIRs were calculated for each HAI and quarter by dividing the number of reported infections by the number of predicted infections, calculated using 2015 national baseline data. Percentage changes between 2019 and 2020 SIRs were calculated. Supporting analyses, such as an assessment of device utilization in 2020 compared to 2019, were also performed. Results: Significant increases in the national SIRs for CLABSI, CAUTI, VAE, and MRSA bacteremia were observed in 2020. Changes in the SIR varied by quarter and state. The largest increase was observed for CLABSI, and significant increases in VAE incidence and ventilator utilization were seen across all 4 quarters of 2020. Conclusions: This report provides a national view of the increases in HAI incidence in 2020. These data highlight the need to return to conventional infection prevention and control practices and build resiliency in these programs to withstand future pandemics.

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The prevalence of suspected ventilator-associated pneumonia in Scottish intensive care units

Journal of the Intensive Care Society ◽

10.1177/1751143719854984 ◽

2019 ◽

Vol 21 (2) ◽

pp. 140-147

Author(s):

Robert Hart ◽

Scott McNeill ◽

Sarah Maclean ◽

Jamie Hornsby ◽

Sarah Ramsay

Keyword(s):

Data Collection ◽

Ventilator Associated Pneumonia ◽

Healthcare Associated Infection ◽

Screening Process ◽

Mechanically Ventilated ◽

Endotracheal Tubes ◽

Data Comparison ◽

Healthcare Associated ◽

The Impact ◽

Meaningful Data

Ventilator-associated pneumonia is the most common healthcare-associated infection in mechanically ventilated patients. Despite this, accurate diagnosis of ventilator-associated pneumonia is difficult owing to the variety of criteria that exist. In this prospective national audit, we aim to quantify the existence of patients with suspected ventilator-associated pneumonia that would not be detected by our standard healthcare-associated infection screening process. Furthermore, we aim to assess the impact of tracheostomy insertion, subglottic drainage endotracheal tubes and chlorhexidine gel on ventilator-associated pneumonia rate. Of the 227 patients recruited, suspected ventilator-associated pneumonia occurred in 32 of these patients. Using the HELICS definition, 13/32 (40.6%) patients were diagnosed with ventilator-associated pneumonia (H-posVAP). Suspected ventilator-associated pneumonia rate was increased in our tracheostomy population, decreased in the subglottic drainage endotracheal tube group and unchanged in the chlorhexidine group. The diagnosis of ventilator-associated pneumonia remains a contentious issue. The formalisation of the HELICS criteria by the European CDC should allow standardised data collection throughout Europe, which will enable more consistent data collection and meaningful data comparison in the future. Our data add weight to the argument against routine oral chlorhexidine. The use of subglottic drainage endotracheal tubes in preventing ventilator-associated pneumonia is interesting and requires further investigation.

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Impact of Antibiotic Therapy in the Microbiological Yield of Healthcare–Associated Ventriculitis and Meningitis

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz050 ◽

2019 ◽

Vol 6 (3) ◽

Cited By ~ 2

Author(s):

Thomas Rogers ◽

Kevin Sok ◽

Timothy Erickson ◽

Elizabeth Aguilera ◽

Susan H Wootton ◽

...

Keyword(s):

Cerebrospinal Fluid ◽

Antibiotic Therapy ◽

Gram Stain ◽

Healthcare Associated ◽

The Impact

Abstract The impact of antibiotic therapy on the diagnosis of healthcare–associated ventriculitis and meningitis (HCAVM) is unknown. Antibiotics were administered before obtaining cerebrospinal fluid (CSF) in 217 out of 326 (66%) patients with HCAVM, and they impacted the sensitivity of the cerebrospinal fluid Gram stain and culture (P ≤ .004).

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Evaluating the Use of the Case Mix Index for Risk Adjustment of Healthcare-Associated Infection Data: An Illustration using Clostridium difficile Infection Data from the National Healthcare Safety Network

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2015.252 ◽

2015 ◽

Vol 37 (1) ◽

pp. 19-25 ◽

Cited By ~ 12

Author(s):

Nicola D. Thompson ◽

Jonathan R. Edwards ◽

Margaret A. Dudeck ◽

Scott K. Fridkin ◽

Shelley S. Magill

Keyword(s):

Clostridium Difficile ◽

Risk Adjustment ◽

Fiscal Year ◽

Case Mix ◽

Healthcare Associated Infection ◽

National Healthcare ◽

Case Mix Index ◽

National Healthcare Safety Network ◽

Healthcare Associated ◽

The Impact

BACKGROUNDCase mix index (CMI) has been used as a facility-level indicator of patient disease severity. We sought to evaluate the potential for CMI to be used for risk adjustment of National Healthcare Safety Network (NHSN) healthcare-associated infection (HAI) data.METHODSNHSN facility-wide laboratory-identified Clostridium difficile infection event data from 2012 were merged with the fiscal year 2012 Inpatient Prospective Payment System (IPPS) Impact file by CMS certification number (CCN) to obtain a CMI value for hospitals reporting to NHSN. Negative binomial regression was used to evaluate whether CMI was significantly associated with healthcare facility-onset (HO) CDI in univariate and multivariate analysis.RESULTSAmong 1,468 acute care hospitals reporting CDI data to NHSN in 2012, 1,429 matched by CCN to a CMI value in the Impact file. CMI (median, 1.49; interquartile range, 1.36–1.66) was a significant predictor of HO CDI in univariate analysis (P<.0001). After controlling for community onset CDI prevalence rate, medical school affiliation, hospital size, and CDI test type use, CMI remained highly significant (P<.0001), with an increase of 0.1 point in CMI associated with a 3.4% increase in the HO CDI incidence rate.CONCLUSIONSCMI was a significant predictor of NHSN HO CDI incidence. Additional work to explore the feasibility of using CMI for risk adjustment of NHSN data is necessary.Infect. Control Hosp. Epidemiol. 2015;37(1):19–25

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Assessing The Impact of The National Healthcare Safety Network’s (NHSN’s) New Baseline on Acute Care Hospital Standardized Infection Ratios (SIRs)

Open Forum Infectious Diseases ◽

10.1093/ofid/ofx162.117 ◽

2017 ◽

Vol 4 (suppl_1) ◽

pp. S49-S50

Author(s):

Minn Soe ◽

Allan Nkwata ◽

Jonathan R Edwards ◽

Margaret Dudeck ◽

Daniel Pollock

Keyword(s):

Acute Care ◽

Risk Adjustment ◽

Acute Care Hospital ◽

Healthcare Facility ◽

Care Hospital ◽

Healthcare Associated Infection ◽

Quality Reporting ◽

National Healthcare ◽

Healthcare Associated ◽

The Impact

Abstract Background To more accurately measure the progress of healthcare-associated infection (HAI) prevention efforts, the CDC’s National Healthcare Safety Network (NHSN) surveillance system updated risk-adjustment models for computation of updated Standardized Infection Ratios (SIRs), the primary HAI summary measure by NHSN. This study sought to examine how the updated SIRs varied from the previous SIRs calculated using older baselines for acute care hospital HAIs. Methods We analyzed NHSN data for healthcare facility-onset laboratory-identified Clostridium difficile [CDI] and methicillin-resistant Staphylococcus aureus [MRSA] bacteremia reported in accordance with the CMS’ inpatient quality reporting program requirement. The unit of analysis was CMS certification number (CCN) facility reporting in 2015. We compared overall distributions of CCN-level SIRs (CCN-SIRs) between new risk-adjustment models using a 2015 baseline (SIR_NEW) and old models using a 2011 baseline (SIR_OLD) and tested location shift (median away from null) of pairwise differences. We also examined the magnitude of shift in SIR from old to new baseline. Results For each HAI, the national pooled mean SIR of the new baseline was ~1.0. For CDI, the overall distributions of CCN SIR_NEW and CCN-SIR_OLD were different, and the median of pairwise difference was away from null with CCN-SIR_NEW slightly higher. For MRSA, the SIR differences were not significant. Most CCN-SIRs (83% for CDI, 93% for MRSA) remained in the same significance category across the old and new baselines (“worse,” “better, ‘not different from national benchmark’), and few CCN-SIRs were reclassified to a less favorable category. For 75% of CCN-SIRs, their relative position in the quartile distributions of SIR_NEW and SIR_OLD remained the same. The discrepancies between SIR_NEW and SIR_OLD tended to be larger among CCNs with high SIRs. Conclusion The updated national pooled mean SIRs were close to 1.0, validating the potential use of new risk adjustment models and baseline as updated benchmarks for tracking CDI and MRSA prevention progress. The shifts in CCN-level SIRs between old and new baselines were not large, indicating a modest impact of new baselines at the CCN level, except among hospitals with high SIRs. Disclosures All authors: No reported disclosures.

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Medical transport-associated infection: Review and commentary making a case for its legitimacy

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1354 ◽

2020 ◽

pp. 1-7

Author(s):

Diego Schaps ◽

Anjni Patel Joiner ◽

Deverick J. Anderson

Keyword(s):

Emergency Medical Services ◽

Prospective Studies ◽

Direct Result ◽

Future Research ◽

Review Of The Literature ◽

Healthcare Associated Infection ◽

Hygiene Practices ◽

Medical Transport ◽

Healthcare Associated ◽

The Impact

Abstract The purpose of this article is to summarize existing literature about healthcare-associated infection (HAI) in the medical transport environment and to define the term medical transport–associated infection (MTAI) to unify all previous work under a single umbrella with the objective of providing a standardized definition for future research. A review of the literature yielded 34 relevant articles. These studies show that there are pathogens in the ambulance environment, that emergency medical services (EMS) personnel do not regularly comply with hygiene practices, and that patients are potentially affected by HAI as a direct result of ambulance exposure. Prospective studies must be conducted to truly understand the impact that ambulance exposure has on HAIs. MTAI is a subset of HAI and is defined as any infection acquired as a direct effect of exposure in a medical transport setting.

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Probabilistic modelling of effects of antibiotics and calendar time on transmission of healthcare-associated infection

10.1101/2020.04.10.20060384 ◽

2020 ◽

Author(s):

Mirjam Laager ◽

Ben S Cooper ◽

David W Eyre

Keyword(s):

Temporal Trends ◽

Simulated Data ◽

Healthcare Associated Infection ◽

Calendar Time ◽

Transmission Parameters ◽

Number Of Patients ◽

Potential Risk Factors ◽

Healthcare Associated ◽

The Impact ◽

Over Time

AbstractHealthcare-associated infection and antimicrobial resistance are major concerns. However, the extent to which antibiotic exposure affects transmission and detection of infections such as MRSA is unclear. Additionally, temporal trends are typically reported in terms of changes in incidence, rather than analysing underling transmission processes. We present a data-augmented Markov chain Monte Carlo approach for inferring changing transmission parameters over time, screening test sensitivity, and the effect of antibiotics on detection and transmission. We expand a basic model to allow use of typing information when inferring sources of infections. Using simulated data, we show that the algorithms are accurate, well-calibrated and able to identify antibiotic effects in sufficiently large datasets. We apply the models to study MRSA transmission in an intensive care unit in Oxford, UK with 7924 admissions over 10 years. We find that falls in MRSA incidence over time were associated with decreases in both the number of patients admitted to the ICU colonised with MRSA and in transmission rates. In our inference model, the data were not informative about the effect of antibiotics on risk of transmission or acquisition of MRSA, a consequence of the limited number of possible transmission events in the data. Our approach has potential to be applied to a range of healthcare-associated infections and settings and could be applied to study the impact of other potential risk factors for transmission. Evidence generated could be used to direct infection control interventions.

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