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Importance of risk adjusting central line-associated bloodstream infection rates in children
Lakshmi Srinivasan1,2, Ashley Oliver1, Yuan-Shung V Huang3
1The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Insights
Developing a new risk model for central line-associated bloodstream infections (CLABSI) in children is crucial. This model accounts for patient complexity, improving the accuracy of CLABSI rate assessments in pediatric hospitals.
Area of Science:
- Pediatric Healthcare Epidemiology
- Infection Control and Prevention
- Health Services Research
Background:
- Central line-associated bloodstream infection (CLABSI) is a significant healthcare-associated infection in pediatric populations.
- Existing risk adjustment methods for CLABSI do not adequately account for individual patient complexities and acuity.
- Accurate risk adjustment is essential for benchmarking hospital performance and evaluating quality improvement initiatives.
Purpose of the Study:
- To develop and validate a risk adjustment model for CLABSI in hospitalized children.
- To compare observed CLABSI rates with expected rates derived from the new risk model.
- To assess the impact of patient-specific factors on CLABSI risk in pediatric populations.
Main Methods:
- Prospective cohort study utilizing electronic health record data from a quaternary children's hospital.
- Inclusion of hospitalized children with central catheters.
- Multivariable logistic regression modeling incorporating factors like age, comorbidities, catheter characteristics, and intensive care unit (ICU) level care requirements.
Main Results:
- The final risk model included 10 significant predictors of CLABSI, including number of organ systems requiring ICU level care (OR 1.24, 95% CI 1.12-1.37).
- Observed CLABSI rates were lower than expected rates in later years, though not statistically significant.
- The model highlights the importance of patient acuity and disease complexity in CLABSI risk.
Conclusions:
- Failure to adjust for patient factors, particularly acuity and complexity, can lead to misinterpretation of CLABSI rates.
- Accurate risk adjustment is vital for the reliable evaluation of quality improvement efforts in pediatric CLABSI prevention.
- The developed model offers a more precise method for assessing CLABSI risk in hospitalized children.
Objective:
Central line-associated bloodstream infection (CLABSI) is one of the most prevalent pediatric healthcare-associated infections and is used to benchmark hospital performance. Pediatric patients have increased in acuity and complexity over time. Existing approaches to risk adjustment do not control for individual patient characteristics, which are strong predictors of CLABSI risk and vary over time. Our objective was to develop a risk adjustment model for CLABSI in hospitalized children and compare observed to expected rates over time.
Design And Setting:
We conducted a prospective cohort study using electronic health record data at a quaternary Children's Hospital.
Patients:
We included hospitalized children with central catheters.
Methods:
Risk factors identified from published literature were considered for inclusion in multivariable modeling based on association with CLABSI risk in bivariable analysis and expert input. We calculated observed and expected (risk model-adjusted) annual CLABSI rates.
Results:
Among 16,411 patients with 520,209 line days, 633 patients experienced 796 CLABSIs. The final model included age, behavioral health condition, non-English speaking, oncology service, port catheter type, catheter dwell time, lymphatic condition, total parenteral nutrition, and number of organ systems requiring ICU level care. For every organ system receiving ICU level care the odds ratio for CLABSI was 1.24 (95% CI 1.12-1.37). Although not statistically different, observed rates were lower than expected rates for later years.
Conclusions:
Failure to adjust for patient factors, particularly acuity and complexity of disease, may miss clinically significant differences in CLABSI rates, and may lead to inaccurate interpretation of the impact of quality improvement efforts.
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