Effect of Accounting for Multiple Concurrent Catheters on Central Line–Associated Bloodstream Infection Rates: Practical Data Supporting a Theoretical Concern

Abstract

Central line-associated bloodstream infection (CLABSI) rates are gaining importance as they become publicly reported metrics and potential pay-for-performance indicators. However, the current conventional method by which they are calculated may be misleading and unfairly penalize high-acuity care settings, where patients often have multiple concurrent central venous catheters (CVCs). We compared the conventional method of calculating CLABSI rates, in which the number of catheter-days is used (1 patient with n catheters for 1 day has 1 catheter-day), with a new method that accounts for multiple concurrent catheters (1 patient with n catheters for 1 day has n catheter-days), to determine whether the difference appreciably changes the estimated CLABSI rate. Cross-sectional survey. Academic, tertiary care hospital. Adult patients who were consecutively admitted from June 10 through July 9, 2009, to a cardiac-surgical intensive care unit and a surgical intensive and surgical intermediate care unit. Using the conventional method, we counted 485 catheter-days throughout the study period, with a daily mean of 18.6 catheter-days (95% confidence interval, 17.2-20.0 catheter-days) in the 2 intensive care units. In contrast, the new method identified 745 catheter-days, with a daily mean of 27.5 catheter-days (95% confidence interval, 25.6-30.3) in the 2 intensive care units. The difference was statistically significant (P < .001). The new method that accounted for multiple concurrent CVCs resulted in a 53.6% increase in the number of catheter-days; this increased denominator decreases the calculated CLABSI rate by 36%. The undercounting of catheter-days for patients with multiple concurrent CVCs that occurs when the conventional method of calculating CLABSI rates is used inflates the CLABSI rate for care settings that have a high CVC burden and may not adjust for underlying medical illness. Additional research is needed to validate and generalize our findings.