Classification of positive blood cultures: computer algorithms versus physicians' assessment--development of tools for surveillance of bloodstream infection prognosis using population-based laboratory databases.
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 pathog...
| Publicado en: | BMC Medical Research Methodology Vol. 12; no. 1; pp. 139 - 140 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104308235&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104308235 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14712288 1CI1 jtl: BMC Medical Research Methodology issn: 14712288 maglogo: N pubinfo: dt: 2012 vid: 12 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 104308235 104308235 NLM22970812 2011924798 10.1186/1471-2288-12-139 NLM22970812 PMC3546010 104308235 ppf: 139 ppct: 1 formats: tig: atl: Classification of positive blood cultures: computer algorithms versus physicians' assessment--development of tools for surveillance of bloodstream infection prognosis using population-based laboratory databases. aug: au: Gradel, Kim O Knudsen, Jenny Dahl Arpi, Magnus Ostergaard, Christian Schønheyder, Henrik C Søgaard, Mette affil: Research Unit of Clinical Epidemiology, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark. kim.gradel@ouh.regionsyddanmark.dk. sug: subj: Algorithms Bacteremia Diagnosis Diagnosis, Computer Assisted Aged Aged, 80 and Over Bacteremia Classification Bacteremia Epidemiology Bacteremia Mortality Community-Acquired Infections Diagnosis Community-Acquired Infections Epidemiology Cross Infection Diagnosis Cross Infection Epidemiology Resource Databases Denmark Epidemiological Research Female Human Infection Control Male Middle Age Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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