Classification of positive blood cultures: computer algorithms versus physicians' assessment--development of tools for surveillance of bloodstream infection prognosis using population-based laboratory databases

Abstract

Background: Information from blood cultures is utilized for infection control, public health surveillance, and clinical outcome research. This information can be enriched by physicians' assessments of positive blood cultures, which are, however, often available from selected patient groups or pathogens only. The aim of this work was to determine whether patients with positive blood cultures can be classified effectively for outcome research in epidemiological studies by the use of administrative data and computer algorithms, taking physicians' assessments as reference.

Methods: Physicians' assessments of positive blood cultures were routinely recorded at two Danish hospitals from 2006 through 2008. The physicians' assessments classified positive blood cultures as: a) contamination or bloodstream infection; b) bloodstream infection as mono- or polymicrobial; c) bloodstream infection as community- or hospital-onset; d) community-onset bloodstream infection as healthcare-associated or not. We applied the computer algorithms to data from laboratory databases and the Danish National Patient Registry to classify the same groups and compared these with the physicians' assessments as reference episodes. For each classification, we tabulated episodes derived by the physicians' assessment and the computer algorithm and compared 30-day mortality between concordant and discrepant groups with adjustment for age, gender, and comorbidity.

Results: Physicians derived 9,482 reference episodes from 21,705 positive blood cultures. The agreement between computer algorithms and physicians' assessments was high for contamination vs. bloodstream infection (8,966/9,482 reference episodes [96.6%], Kappa = 0.83) and mono- vs. polymicrobial bloodstream infection (6,932/7,288 reference episodes [95.2%], Kappa = 0.76), but lower for community- vs. hospital-onset bloodstream infection (6,056/7,288 reference episodes [83.1%], Kappa = 0.57) and healthcare-association (3,032/4,740 reference episodes [64.0%], Kappa = 0.15). The 30-day mortality in the discrepant groups differed from the concordant groups as regards community- vs. hospital-onset, whereas there were no material differences within the other comparison groups.

Conclusions: Using data from health administrative registries, we found high agreement between the computer algorithms and the physicians' assessments as regards contamination vs. bloodstream infection and monomicrobial vs. polymicrobial bloodstream infection, whereas there was only moderate agreement between the computer algorithms and the physicians' assessments concerning the place of onset. These results provide new information on the utility of computer algorithms derived from health administrative registries.

Figure 1

Flowchart of positive blood cultures, reference episodes, computer episodes, and patients. For definitions, see Table 1. As the same patients may appear in different categories, the number of patients does not necessarily correlate with differences between boxes.

Figure 2

Kaplan-Meier mortality curves up to day 30 for patient groups derived from computer algorithms or physicians’ assessments. Contamination vs. bloodstream infection: contamination according to computer algorithm and physicians’ assessment (green solid line); bloodstream infection according to computer algorithm and physicians’ assessment (red solid line); contamination according to computer algorithm, bloodstream infection according to physicians’ assessment (black dashed line); bloodstream infection according to computer algorithm, contamination according to physicians’ assessment (blue dashed line). Monomicrobial vs. polymicrobial: monomicrobial according to computer algorithm and physicians’ assessment (green solid line); polymicrobial according to computer algorithm and physicians’ assessment (red solid line); monomicrobial according to computer algorithm, polymicrobial according to physicians’ assessment (black dashed line); polymicrobial according to computer algorithm, monomicrobial according to physicians’ assessment (blue dashed line). Community- vs. hospital-onset: community-onset according to computer algorithm and physicians’ assessment (green solid line); hospital-onset according to computer algorithm and physicians’ assessment (red solid line); community-onset according to computer algorithm, hospital-onset according to physicians’ assessment (black dashed line); hospital-onset according to computer algorithm, community-onset according to physicians’ assessment (blue dashed line). Healthcare- vs. no healthcare-association: no healthcare-association according to computer algorithm and physicians’ assessment (green solid line); healthcare-association according to computer algorithm and physicians’ assessment (red solid line); no healthcare-association according to computer algorithm, healthcare-association according to physicians’ assessment (black dashed line); healthcare-association according to computer algorithm, no healthcare-association according to physicians’ assessment (blue dashed line).