Discrete event simulation and agent-based modelling of distributed situation awareness in patient flow management

Patient flow management heavily relies on effective communication or transactions of situation awareness (SA) amongst hospital staff to minimize patients’ length of stay. Modelling SA transactions quantitatively could help identify inefficiencies and test potential solutions. This paper presents quantitative modelling of distributed situation awareness (DSA) with discrete event simulation (DES) and agent-based modelling (ABM) to capture and assess the transactions and distribution of SA for intrahospital transportation in patient flow management. The quantitative model was built on a qualitative DSA combined network for intrahospital transportation, observations, and historical data, followed by validation with t-tests by comparing transport time and number of patients transported between model outputs and historical data. Further, the model was used to test two proposed interventions for eliminating SA deficiencies revealed by prior qualitative DSA research: (1) updating the charge nurse before picking up patients, and (2) updating the X-ray unit before arriving. T-tests on the simulation results of 1500 replications revealed that the first intervention yielded significant reductions in mean transport time and cancelation rate, while the second intervention yielded a significant increase in transport time compared to the historical operational data. To our knowledge, this work is the first quantitative modelling research on DSA that is being assessed against operational data. The findings affirm that DSA is a promising framework for analyzing communication and coordination in complex systems and assessing system-level SA quantitatively.