Cost-effectiveness of molecular diagnostic assays for the therapy of severe sepsis and septic shock in the emergency department.

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Cost-effectiveness of molecular diagnostic assays for the therapy of severe sepsis and septic shock in the emergency department.

PLoS One. 2019;14(5):e0217508

Authors: Zacharioudakis IM, Zervou FN, Shehadeh F, Mylonakis E

Abstract
OBJECTIVES: Sepsis presents a major burden to the emergency department (ED). Because empiric inappropriate antimicrobial therapy (IAAT) is associated with increased mortality, rapid molecular assays may decrease IAAT and improve outcomes. We evaluated the cost-effectiveness of molecular testing as an adjunct to blood cultures in patients with severe sepsis or septic shock evaluated in the ED.
METHODS: We developed a decision analysis model with primary outcome the incremental cost-effectiveness ratio expressed in terms of deaths averted. Costs were dependent on the assay price and the patients' length of stay (LOS). Three base-case scenarios regarding the difference in LOS between patients receiving appropriate (AAT) and IAAT were described. Sensitivity analyses regarding the assay cost and sensitivity, and its ability to guide changes from IAAT to AAT were performed.
RESULTS: Under baseline assumptions, molecular testing was cost-saving when the LOS differed by 4 days between patients receiving IAAT and AAT (ICER -$7,302/death averted). Our results remained robust in sensitivity analyses for assay sensitivity≥52%, panel efficiency≥39%, and assay cost≤$270. In the extreme case that the LOS of patients receiving AAT and IAAT was the same, the ICER remained≤$20,000/death averted for every studied sensitivity (i.e. 0.5-0.95), panel efficiency≥34%, and assay cost≤$313. For 2 days difference in LOS, the bundle approach was dominant when the assay cost was≤$135 and the panel efficiency was≥77%.
CONCLUSIONS: The incorporation of molecular tests in the management of sepsis in the ED has the potential to improve outcomes and be cost-effective for a wide range of clinical scenarios.

PMID: 31125382 [PubMed - in process]

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