Appropriate maintenance of central lines (CL) is important to prevent central line-associated
bloodstream infections (CLABSI). Daily assessment of CL maintenance with feedback
was instituted as a CLABSI prevention effort. The objective of this study was to determine
if observer bias influenced CL maintenance bundle observation compliance data.
We developed and implemented a maintenance bundle based on CLABSI prevention guidelines
at a 1266-bed academic hospital. Observers were trained to audit CL for compliance
with maintenance bundle components, including: alcohol-impregnated disinfection caps
on unused CL ports and infusion tubing, dressings clean and dry, no oozing at insertion
site greater than the size of a quarter, dressings occlusive and intact, transparent
dressing change recorded within 7-day timeframe, and within 48 hours for gauze dressings.
Observations were performed by unit based observers and non-unit based nurse observers
house-wide. Bundle compliance between unit based observer and non-unit based observer
was compared using Mantel-Haenszel chi-square analysis.
Between 8/1/2018 and 11/1/2019 there were 91,068 CL observations [63,945 (70.2%) by
unit-based and 27,123 (29.8%) by non-unit based observers]. Overall, 9,455 (10.4%)
CL observations were non-compliant with 1 or more bundle components. 3,019 (3.3%)
(14.11%)]. Unit-based observers were less likely to report CL observations that were
non-compliant with 1 or more bundle components compared to non-unit based observers
[3,808 (6%) vs. 5,647 (20.8%), p < 0.001]. Unit-based observers were less likely to
document dressing non-compliance [2,163 (3.4%) vs. 3,586 (13.3%), p < 0.001] or alcohol-impregnated
disinfection cap non-compliance [943 (1.6%) vs. 2,076 (8.5%), p < 0.001] compared
to non-unit based observers.
Observer bias may impact reported compliance from unit-based observations, compared
to trained external observer data. Unit-based observers may be less likely to report
non-compliance with bundle components. The use of external observers should be considered
to reduce potential bias, and increase confidence in the accuracy of compliance data.