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205551 Determining the Economic Value of Implementing Universal Methicillin-resistant Staphylococcus aureus (MRSA) Surveillance in an Acute Care HospitalTuesday, November 10, 2009: 12:50 PM
Background: MRSA is a substantial problem in many hospitals. We aimed to determine whether universal surveillance of all hospital admissions to identify and subsequently isolate MRSA positive patients would be cost-effective.
Methods: Using TreeAge Pro 2009, we developed a stochastic decision analytic computer simulation model with dynamic transmission components representing the decision whether to perform universal MRSA surveillance from the societal perspective. MRSA positive patients would then be isolated. MRSA positive patients who are not isolated, because they either were not tested or had a false negative test, would transmit colonization to a number of other patients, determined by the generation number (R0). Newly colonized patients then had probabilities of developing different infections and outcomes from MRSA. The model determined the incremental cost-effectiveness ratio (ICER) of universal surveillance versus no surveillance as in 2008 dollars per quality-adjusted life years (QALY). Sensitivity analyses systematically varied the prevalence of MRSA from 5% to 90%, the R0 from 0.25 to 3.0. Results: Performing universal surveillance was the dominant strategy (less costly and more effective) at the following prevalence and R0 combinations: R0 =1.5, prevalence ≥ 0.15; R0 =2.0, prevalence ≥ 0.10; R0 =2.5, prevalence ≥ 0.05; R0 =3.0, prevalence ≥ 0.05. Universal surveillance remained cost-effective (ICER<$0,000/QALY) at the following combinations: R0=0.25, prevalence ≥ 0.05; R0 =0.5, prevalence ≥ 0.05; R0 =1.0, prevalence ≥ 0.05; R0 =1.5, prevalence 0.05, 0.1; R0 =2.0, prevalence ≥ 0.05. Conclusions: Universal MRSA surveillance appears to be cost effective at a wide range of R0 and prevalence values.
Learning Objectives: Keywords: Antibiotic Resistance, Economic Analysis
Presenting author's disclosure statement:
Qualified on the content I am responsible for because: I designed the model and analyzed the data. I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.
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