scholarly journals 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

2015 ◽  
Vol 37 (1) ◽  
pp. 19-25 ◽  
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

scholarly journals 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

2021 ◽  
pp. 1-14 ◽  
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.

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

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.

Comparison of Data Collection for Healthcare-Associated Infection Surveillance in Nursing Homes

2016 ◽  
Vol 37 (12) ◽  
pp. 1440-1445 ◽  
Author(s):  
Lauren Epstein ◽  
Nimalie D. Stone ◽  
Lisa LaPlace ◽  
Jane Harper ◽  
Ruth Lynfield ◽  
...  
Keyword(s):  
Risk Factors ◽  
Nursing Homes ◽  
Data Collection ◽  
Clinical Risk Factors ◽  
Healthcare Associated Infection ◽  
Screening Criteria ◽  
Clinical Risk ◽  
Level Data ◽  
Healthcare Associated ◽  
The Impact

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

scholarly journals 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?

2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
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.

Sign in / Sign up

Export Citation Format

Share Document