Hybrid simulation for modelling healthcare-associated infections : promising but challenging

Nguyen, Le Khanh Ngan and Megiddo, Itamar and Howick, Susan (2020) Hybrid simulation for modelling healthcare-associated infections : promising but challenging. Clinical Infectious Diseases. ISSN 1058-4838

[img] Text (Nguyen-etal-CID-2020-Hybrid-simulation-for-modelling-healthcare-associated-infections)
Nguyen_etal_CID_2020_Hybrid_simulation_for_modelling_healthcare_associated_infections.pdf
Accepted Author Manuscript
Restricted to Repository staff only until 31 August 2021.

Download (207kB) | Request a copy from the Strathclyde author

    Abstract

    Healthcare-Associated Infections (HAIs) are a major public health problem as they pose a serious risk for patients and providers, increasing morbidity, mortality, and length of stay as well as costs to patients and the health system. Prevention and control of HAIs has, therefore, become a priority for most healthcare systems. Systems simulation models have provided insights into the dynamics of HAIs and help to evaluate the effect of infection control interventions. However, as each systems simulation modeling method has strengths and limitations, combining these methods in hybrid models can offer a better tool to gain complementary views on, and deeper insights into, HAIs. Hybrid models can, therefore, assist decision-making at different levels of management, and provide a balance between simulation performance and result accuracy. This paper discusses these benefits in more depth but also highlights some challenges associated with the use of hybrid simulation models for modeling HAIs.