The algorithms used in electronic surveillance systems may need to be adjusted for specific patient populations to better identify central line-associated bloodstream infections, according to a study published in Infection Control & Hospital Epidemiology.
Researchers reviewed intensive care unit patients with positive blood cultures and determined CLABSIs using two sources: routine and fully automated surveillance. They then added new rules to the algorithm to identify secondary sites and applied the rules to an ICU population and a non-ICU population.
Of the 643 positive ICU blood cultures reviewed, the fully automated electronic surveillance identified 68 CLABSIs, 38 of which were confirmed by routine surveillance. The researchers ran the fully automated surveillance systems again with the added rules.
They found surveillance models with the following two new rules worked best when positive blood cultures in an ICU population: matching organisms (by genus and species) cultured from any other site and matching any organisms cultured from sterile site
The researchers note the new rules didn't improve the algorithm's performance when applied to positive blood cultures in a non-ICU population.
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