title: Measuring the effectiveness of hospital-acquired infection prevention.
abstract: This article deals with data on nosocomial infections acquired in the Geneva University Hospitals. Goal of the work is to derive a model from a hospital-acquired infection (HAI) prevalence survey of year Y and apply them to a prevalence survey of years Y+1, Y+2. This analysis permits to evaluate the effectiveness of preventive measures taken after the prevalence survey in year Y. It also analyzes the robustness of the SVM algorithm on time-variable attributes. The model build on the dataset of year Y gives better results than in a previous study. The application of the model on the Y+1 and Y+2 prevalence surveys shows simultaneously improvements and deteriorations of 5 performance measures. This highlights the effectiveness of prevention and reduces the risk of HAI after the prevalence survey of year Y. We introduce a new method to detect redundancy in a dataset with the SVM algorithm.
authors.affiliation: Medical Informatics Department, University and Hospitals of Geneva, Switzerland. jimison.iavindrasana@sim.hcuge.ch
authors.forename: Jimison
authors.initials: J
authors.lastname: Iavindrasana
authors.forename: Gilles
authors.initials: G
authors.lastname: Cohen
authors.forename: Adrien
authors.initials: A
authors.lastname: Depeursinge
authors.forename: Henning
authors.initials: H
authors.lastname: Müller
authors.forename: Rodolphe
authors.initials: R
authors.lastname: Meyer
authors.forename: Hugo
authors.initials: H
authors.lastname: Sax
authors.forename: Antoine
authors.initials: A
authors.lastname: Geissbuhler
mesh_terms: D000465:Algorithms; D003428:Cross Infection / Q000453:epidemiology* / Q000517:prevention & control*; D018563:Disease Notification / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D018571:Sentinel Surveillance; D013557:Switzerland / Q000453:epidemiology