title: An evaluation of classification rules based on date of symptom onset to identify health-care associated infections.
abstract: The date of symptom onset is often used to distinguish health-care-associated from community-acquired infections. Those patients developing symptoms early in an inpatient stay are considered to have community-acquired infection, while those developing symptoms later are considered nosocomially infected. The authors evaluate the performance of this approach, showing how misclassification rates depend on the disease incubation period and the incidence rate ratio of infection among inpatients versus community members. The authors provide quantitative results for selecting classification rules that designate infections as health care associated or community acquired. These techniques allow the selection of disease-specific cutoffs to distinguish community- from nosocomially acquired infections that perform well for important illnesses. For example, a rule classifying those who develop flu symptoms in the first 1.5 days of their hospital stay as having community-acquired influenza and those developing symptoms later as having nosocomial infection has a positive predictive value and a negative predictive value of at least 87%. A cutoff of 6 days will identify community-acquired Legionnaires' disease with a positive predictive value and a negative predictive value of at least 77%. These results increase the utility of classifying infections by use of the date of onset by providing theoretically sound measures of performance, and they are applicable beyond the hospital setting.
authors: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. jlessler@jhsph.edu
authors: Justin
authors: J
authors: Lessler
authors: Ron
authors: R
authors: Brookmeyer
authors: Trish M
authors: TM
authors: Perl
mesh_terms: D017714:Community-Acquired Infections / Q000145:classification / Q000175:diagnosis / Q000453:epidemiology; D003428:Cross Infection / Q000145:classification* / Q000175:diagnosis*; D006801:Humans; D015994:Incidence; D013997:Time Factors