A model to reduce the risk of infection transmission in ICUs

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Shreyas Limaye
University of Washington, Seattle

Christina Mastrangelo
University of Washington, Seattle

This study takes a systemic view at the operational level of ICU in order to reduce transmission of hospital-associated infections. It suggests an integrated methodology that combines cognitive modeling, simulation, risk analysis, and generalized linear models to improve the quality of health care provided at the Children's Hospital, Seattle.

Hospital-associated infections are a major national concern. According to the Centers for Disease Control and Prevention (CDC), nearly two million patients every year acquire an infection while being treated for another illness or injury, and nearly 88,000 die as a direct or indirect consequence of the infection. Resulting economic costs due to required supportive therapies and prolonged hospital stays are high, in spite of the fact that for common hospital-associated infections, best practices to reduce the occurrence are well documented in the literature.

Instead of tackling individual infections, there is a need to develop an effective means for tackling the problem of hospital-associated infections from a systems perspective. This research focuses on developing a model for evaluating the occurrence of overall risk of an event in the ICU where an event refers to the transmission of hospital-associated infections. In addition to modeling the physical and methodological aspects of the ICU environment, it will combine cognitive theories, nonlinear statistical algorithms, and risk analysis models. This talk will present the methodology that was developed in collaboration with Children's Hospital, Seattle.