Modeling the Dynamic Outcomes of Infection Prevention Behaviors in an ICU Environment

Objective: The research opportunity addressed in this study is in understanding how socio-technical system interactions within healthcare settings can be optimized to promote patient safety, particularly in the context of infection risk analysis during critical clinician-patient interactions and throughout the care delivery. Background: Preventing the risk of pathogen spread in healthcare environments that cause Hospital Acquired Infections (HAIs) is an ongoing challenge both in the U.S. and globally. In complex inpatient care delivery settings, variability in clinical staff's infection control behaviors, such as hand hygiene compliance, can hinder achievement of optimal HAI risk prevention objectives. Method: The authors employed Agent-based Modeling (ABM) in conjunction with the Theory of Planned Behavior (TPB) as a framework for evaluating the simulated results of safety behaviors like hand hygiene compliance impact both patient and overall environmental infectivity. Results: This study demonstrates that using a computational approach to evaluate operational factors in care delivery settings can effectively forecast the impact of human behaviors like hand hygiene compliance on patient safety and environmental infectivity levels. Conclusion: This approach provides valuable insights for designing and operating healthcare environments by highlighting the importance of integrating behavioral theories and computational modeling to improve infection control practices. Application: The implications of this study healthcare designers and hospital operations professionals suggest that applying ABM to evaluate physical design interventions within the care environment that bolster clinicians' Perceived Behavioral Control and their intentions to perform safe infection risk prevention practices offers a viable method for understanding and improving the design dynamics healthcare settings.