title: An automated algorithm to preselect patients to be assessed individually in point prevalence surveys for hospital-acquired infections in surgery.
abstract: In this pilot study, we evaluate an algorithm that uses predictive clinical and laboratory parameters to differentiate between patients with hospital-acquired infection (HAI) and patients without HAI. Seventy-four percent of the studied population of surgical patients could be reliably (negative predictive value of 98%) excluded from detailed assessment by the infection control practitioner.
authors.affiliation: Department of Medical Microbiology and Infectious Diseases, Erasmus Medical Center, Rotterdam, The Netherlands.
authors.forename: Roel H R A
authors.initials: RH
authors.lastname: Streefkerk
authors.forename: Peter W
authors.initials: PW
authors.lastname: Moorman
authors.forename: Gerard A
authors.initials: GA
authors.lastname: Parlevliet
authors.forename: Conrad
authors.initials: C
authors.lastname: van der Hoeven
authors.forename: Henri A
authors.initials: HA
authors.lastname: Verbrugh
authors.forename: Margreet C
authors.initials: MC
authors.lastname: Vos
authors.forename: Roel P
authors.initials: RP
authors.lastname: Verkooijen
mesh_terms: D000046:Academic Medical Centers; D000465:Algorithms; D003428:Cross Infection / Q000453:epidemiology*; D006760:Hospitalization; D006801:Humans; D016357:Infection Control Practitioners; D009426:Netherlands; D010865:Pilot Projects; D011237:Predictive Value of Tests; D015995:Prevalence; D012494:Sampling Studies; D013503:Surgery Department, Hospital