title: Validity analysis of a unique infection surveillance system in the intensive care unit by analysis of a data warehouse built through a workflow-integrated software application.
abstract: BACKGROUND
  An electronic decision support programme was developed within the intensive care unit (ICU) that provides an overview of all infection-related patient data, and allows ICU physicians to add clinical information during patient rounds, resulting in prospective compilation of a database.
  
  
  OBJECTIVE
  To assess the validity of computer-assisted surveillance (CAS) of ICU-acquired infection performed by analysis of this database.
  
  
  METHODS
  CAS was compared with prospective paper-based surveillance (PBS) for ICU-acquired respiratory tract infection (RTI), bloodstream infection (BSI) and urinary tract infection (UTI) over four months at a 36-bed medical and surgical ICU. An independent panel reviewed the data in the case of discrepancy between CAS and PBS.
  
  
  RESULTS
  PBS identified 89 ICU-acquired infections (13 BSI, 18 UTI, 58 RTI) and CAS identified 90 ICU-acquired infections (14 BSI, 17 UTI, 59 RTI) in 876 ICU admissions. There was agreement between CAS and PBS on 13 BSI (100 %), 14 UTI (77.8 %) and 42 RTI (72.4 %). Overall, there was agreement on 69 infections (77.5%), resulting in a kappa score of 0.74. Discrepancy between PBS and CAS was the result of capture error in 11 and 14 infections, respectively. Interobserver disagreement on probability (13 RTI) and focus (two RTI, one UTI) occurred for 16 episodes. The time required to collect information using CAS is less than 30% of the time required when using PBS.
  
  
  CONCLUSIONS
  CAS for ICU-acquired infection by analysis of a database built through daily workflow is a feasible surveillance method and has good agreement with PBS. Discrepancy between CAS and PBS is largely due to interobserver variability.
authors.affiliation: Department of Intensive Care, Ghent University Hospital, Ghent, Belgium. Electronic address: liesbet.debus@ugent.be.
authors.forename: L
authors.initials: L
authors.lastname: De Bus
authors.affiliation: Department of Intensive Care, Ghent University Hospital, Ghent, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Diet
authors.affiliation: Department of Information Technology, Ghent University - iMinds, Ghent, Belgium.
authors.forename: B
authors.initials: B
authors.lastname: Gadeyne
authors.affiliation: Department of Clinical Chemistry, Microbiology and Immunology, Ghent University Hospital, Ghent, Belgium.
authors.forename: I
authors.initials: I
authors.lastname: Leroux-Roels
authors.affiliation: Department of Clinical Chemistry, Microbiology and Immunology, Ghent University Hospital, Ghent, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Claeys
authors.affiliation: Department of Information Technology, Ghent University - iMinds, Ghent, Belgium.
authors.forename: K
authors.initials: K
authors.lastname: Steurbaut
authors.affiliation: Department of Intensive Care, Ghent University Hospital, Ghent, Belgium.
authors.forename: D
authors.initials: D
authors.lastname: Benoit
authors.affiliation: Department of Information Technology, Ghent University - iMinds, Ghent, Belgium.
authors.forename: F
authors.initials: F
authors.lastname: De Turck
authors.affiliation: Department of Intensive Care, Ghent University Hospital, Ghent, Belgium.
authors.forename: J
authors.initials: J
authors.lastname: Decruyenaere
authors.affiliation: Department of Intensive Care, Ghent University Hospital, Ghent, Belgium.
authors.forename: P
authors.initials: P
authors.lastname: Depuydt
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003428:Cross Infection / Q000175:diagnosis* / Q000453:epidemiology*; D020000:Decision Support Systems, Clinical; D004582:Electronics, Medical / Q000379:methods*; D062665:Epidemiological Monitoring; D005260:Female; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008875:Middle Aged; D012984:Software; D057188:Workflow; D055815:Young Adult
keywords: Computer-assisted surveillance; ICU-acquired infection; Infection surveillance; Information technology systems