Effectiveness and cost of implementing an active surveillance screening policy for Acinetobacter baumannii: A Monte Carlo simulation model

Background Acinetobacter baumannii infections are common and associated with high mortality and costs. Early identification of asymptomatic carriers can reduce patient-to-patient transmission, but the sensitivity of A baumannii surveillance tools is poor, and thus active surveillance is not routine practice. This study examined whether an active surveillance screening policy can reduce the transmission, mortality, and costs associated with A baumannii . Methods A simulation model was developed to determine the impact of active screening on patient outcomes. Model parameters included A baumannii prevalence, screening sensitivity and specificity, probability of transmission, progression from colonization to infection, mortality, and cost of screening, contact precautions, and infection. A scenario analysis was performed to evaluate the robustness of the results when varying the sensitivity of the screening test and the prevalence rate of A baumannii . Results Assuming a screening sensitivity of 55%, active screening reduced A baumannii transmissions, infections, and deaths by 48%. As the screening sensitivity approached 90%, the reduction in transmissions, infections, and deaths reached 78%. For all scenarios tested, active surveillance was cost saving (19%-53% reduction in mean hospital cost per patient) except at a carrier prevalence of ≤2% and screening test sensitivity of ≤55%. Conclusions In institutions where A baumannii is endemic or during epidemics, implementing a surveillance program is cost-saving and can greatly reduce transmissions and deaths. Methodologies to improve the sensitivity of surveillance testing will help optimize the clinical impact of active screening programs on preventing the spread of A baumannii in health care facilities.