Clostridium difficile (C. difficile) is the main infectious cause of hospital-acquired diarrhea, responsible for as much as 20% of all cases. C. difficile infection (CDI) affects 500,000 Americans each year, causes 29,000 deaths and over 1 billion dollars in direct healthcare costs annually. The incidence and severity of CDI is increasing and containment has been designated a public health priority by the NIH. Transmission of C. difficile occurs in healthcare settings and prevention of transmission is essential to reduce the burden of healthcare-associated CDI yet prevention is challenging and continues to elude us. To identify effective CDI control strategies, it is essential to 1) better understand the transmission dynamics of C. difficile and 2) determine the comparative performance of different containment measures across different hospital settings where procedures and practices may vary considerably. We previously developed an agent-based simulation model to evaluate CDI transmission in a generic hospital using expert opinion and data from literature. The objective in this application is to refine and expand our agent-based model by replicating three different hospital sites, using data from these sites to validate the model, modeling health care workers more realistically by differentiating health care worker types, in addition to implementing novel CDI prevention interventions with high fidelity such as antibiotic stewardship and patient and visitor hand hygiene. The implementation of the interventions will be accomplished using the Systems Engineering Initiative for Patient Safety which allows a comprehensive work system analysis essential to implementing complex behavioral interventions in healthcare settings. This will be the first CDI transmission model combining an agent-based model to predict the effect of interventions and the SEIPS framework to successfully implement potentially promising interventions. If successful, this work will change the paradigm in how CDI prevention is approached in healthcare settings with the goal of eliminating CDI as a complication of healthcare.
Healthcare-associated infections are common and costly?yet they are preventable. A particularly challenging healthcare-associated infection is Clostridium difficile infection (CDI), which affects 500,000 Americans each year, causes 29,000 deaths and costs our healthcare system over 1 billion dollars annually. Challenges to preventing CDI could be overcome if we had the ability to predict which interventions and implementation strategies work best in different settings and to deploy interventions with high fidelity using a systems engineering approach that takes into the account the complexities of the healthcare system. The proposed research will test the effectiveness of 1) a mathematical modeling strategy to devise optimal interventions and 2) a systems engineering approach to implement promising interventions for reducing CDI.
