Background.
Control of C. difficile infection (CDI) is an increasingly difficult problem for healthcare institutions. There are commonly recommended strategies to combat CDI transmission such as oral vancomycin for CDI treatment, increased hand hygiene with soap and water for healthcare workers, daily environmental disinfection of infected patient rooms, and contact isolation of diseased patients. However, the efficacy of these strategies, particularly for endemic CDI, has not been well studied. The objective of this research is to develop a valid agent-based simulation model (ABM) to study C. difficile transmission and control in a mid-sized hospital.
Methods.
We develop an ABM of a mid-sized hospital with agents such as patients, healthcare workers, and visitors. We model the natural progression of CDI in a patient using a Markov chain and the transmission of CDI through agent and environmental interactions. We derive input parameters from aggregate patient data from the 2007-2010 Wisconsin Hospital Association and published medical literature. We define a calibration process, which we use to estimate transition probabilities of the Markov model by comparing simulation results to benchmark values found in published literature.
Results.
Comparing CDI control strategies implemented individually, routine bleach disinfection of CDI+ patient rooms provides the largest reduction in nosocomial asymptomatic colonizations (21.8%) and nosocomial CDIs (42.8%). Additionally, vancomycin treatment provides the largest reduction in relapse CDIs (41.9%), CDI-related mortalities (68.5%), and total patient LOS (21.6%).
Conclusion.
We develop a generalized ABM for CDI control that can be customized and further expanded to specific institutions and/or scenarios. Additionally, we estimate transition probabilities for a Markov model of natural CDI progression in a patient through calibration.
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