Mathematical model of the cost-effectiveness of the BioFire FilmArray Blood Culture Identification (BCID) Panel molecular rapid diagnostic test compared with conventional methods for identification of Escherichia coli bloodstream infections. (3rd November 2021) - Mponponsuo, Kwadwo; Leal, Jenine; Spackman, Eldon; Somayaji, Ranjani; Gregson, Daniel; Rennert-May, Elissa
Abstract: Background: Gram-negative pathogens, such as Escherichia coli, are common causes of bloodstream infections (BSIs) and increasingly demonstrate antimicrobial resistance. Molecular rapid diagnostic tests (mRDTs) offer faster pathogen identification and susceptibility results, but higher costs compared with conventional methods. We determined the cost-effectiveness of the BioFire FilmArray Blood Culture Identification (BCID) Panel, as a type of mRDT, compared with conventional methods in the identification of E. coli BSIs. Methods: We constructed a decision analytic model comparing BCID with conventional methods in the identification and susceptibility testing of hospitalized patients with E. coli BSIs from the perspective of the public healthcare payer. Model inputs were obtained from published literature. Cost-effectiveness was calculated by determining the per-patient admission cost, the QALYs garnered and the incremental cost-effectiveness ratios (ICERs) where applicable. Monte Carlo probabilistic sensitivity analyses and one-way sensitivity analyses were conducted to assess the robustness of the model. All costs reflect 2019 Canadian dollars. Results: The Monte Carlo probabilistic analyses resulted in cost savings ($27 070.83 versus $35 649.81) and improved QALYs (8.65 versus 7.10) in favour of BCID. At a willingness to pay up to $100 000, BCID had a 72.6%–83.8% chance of being cost-effective. One-way sensitivity analyses revealed length of stay and cost per day of hospitalization to have the most substantial impact on costs and QALYs. Conclusions: BCID was found to be cost-saving when used to diagnose E. coli BSI compared with conventional testing. Cost savings were most influenced by length of stay and cost per day of hospitalization.