title: A hospital-level cost-effectiveness analysis model for toxigenic Clostridium difficile detection algorithms.
abstract: BACKGROUND
  Despite thorough analyses of the analytical performance of Clostridium difficile tests and test algorithms, the financial impact at hospital level has not been well described. Such a model should take institution-specific variables into account, such as incidence, request behaviour and infection control policies.
  
  
  OBJECTIVE
  To calculate the total hospital costs of different test algorithms, accounting for days on which infected patients with toxigenic strains were not isolated and therefore posed an infectious risk for new/secondary nosocomial infections.
  
  
  METHODS
  A mathematical algorithm was developed to gather the above parameters using data from seven Flemish hospital laboratories (Bilulu Microbiology Study Group) (number of tests, local prevalence and hospital hygiene measures). Measures of sensitivity and specificity for the evaluated tests were taken from the literature. List prices and costs of assays were provided by the manufacturer or the institutions. The calculated cost included reagent costs, personnel costs and the financial burden following due and undue isolations and antibiotic therapies. Five different test algorithms were compared.
  
  
  CONCLUSIONS
  A dynamic calculation model was constructed to evaluate the cost:benefit ratio of each algorithm for a set of institution- and time-dependent inputted variables (prevalence, cost fluctuations and test performances), making it possible to choose the most advantageous algorithm for its setting. A two-step test algorithm with concomitant glutamate dehydrogenase and toxin testing, followed by a rapid molecular assay was found to be the most cost-effective algorithm. This enabled resolution of almost all cases on the day of arrival, minimizing the number of unnecessary or missing isolations.
authors.affiliation: Laboratory of Microbiology, Onze-Lieve-Vrouw Hospital, Aalst, Belgium. Electronic address: eline.verhoye@azdelta.be.
authors.forename: E
authors.initials: E
authors.lastname: Verhoye
authors.affiliation: Clinical Laboratory, Jan Yperman Hospital, Ieper, Belgium.
authors.forename: P
authors.initials: P
authors.lastname: Vandecandelaere
authors.affiliation: Laboratory of Microbiology, Onze-Lieve-Vrouw Hospital, Aalst, Belgium.
authors.forename: H
authors.initials: H
authors.lastname: De Beenhouwer
authors.affiliation: Clinical Laboratory, Hospital Oost-Limburg, Genk, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Coppens
authors.affiliation: Clinical Laboratory, Jessa Hospital, Hasselt, Belgium.
authors.forename: R
authors.initials: R
authors.lastname: Cartuyvels
authors.affiliation: Laboratory of Microbiology, General Hospital Sint-Lucas, Gent, Belgium.
authors.forename: A
authors.initials: A
authors.lastname: Van den Abeele
authors.affiliation: Clinical Laboratory, Imelda Hospital, Bonheiden, Belgium.
authors.forename: J
authors.initials: J
authors.lastname: Frans
authors.affiliation: Clinical Laboratory, Heilig Hart Hospital, Lier, Belgium.
authors.forename: W
authors.initials: W
authors.lastname: Laffut
mesh_terms: D000465:Algorithms; D001431:Bacteriological Techniques / Q000191:economics* / Q000379:methods*; D016360:Clostridioides difficile / Q000302:isolation & purification*; D003015:Clostridium Infections / Q000175:diagnosis*; D003362:Cost-Benefit Analysis; D003428:Cross Infection / Q000175:diagnosis*; D003967:Diarrhea / Q000175:diagnosis*; D017721:Hospital Costs; D006801:Humans; D018571:Sentinel Surveillance
keywords: Algorithm; Clostridium difficile; Cost-effectiveness model; Toxigenic