Modeling a Public Hospital Outpatient Clinic in Peru using Discrete Simulation

Modeling and simulating hospital operations in a 3D environment

“…However, there are also dashboards which use simulation technologies to inform, guide and predict how clinical care and facility management may be impacted in a variety of scenarios. These have included studies looking at: improving radiation therapy planning (Werker et al 2009); reducing waiting times and delays (Harper and Gamlin 2003;Vanberkel and Blake 2007;Al-Araidah, Boran, and Wahsheh 2012); modelling outpatient departments (Quevedo and Chapilliquén 2015); modelling emergency departments (Zeng et al 2012;Cabrera et al 2012;Brenner et al 2010); maximizing utilization and capacities (Lee et al 2013;Ballard and Kuhl 2006); and measuring the impact of policy changes (Fletcher et al 2007).…”

“…These studies employ a range of simulation tools to achieve the core functionality of their simulation dashboards, such as agent-based modelling (Cabrera et al 2012), SIMUL8 (Harper and Gamlin 2003;Brenner et al 2010;Zeng et al 2012) and Arena (Werker et al 2009;Ballard and Kuhl 2006;Vanberkel and Blake 2007;Quevedo and Chapilliquén 2015;Al-Araidah, Boran, and Wahsheh 2012). SIMUL8 and Arena offer similar discrete-event simulation capabilities for complex systems analysis, such as drug dispensing and patient flows, with Arena additionally providing an option to visualize results in a 3D environment via a dashboard utilizing charts to visualize results as they are generated.…”

“…Previous healthcare related dashboards have been developed to analyze bed occupancies (Daley et al 2013), readmission prevention (Stadler et al 2016) and performance management (Mesabbah and Arisha 2016). Other dashboards have been built as Discrete-Event Simulators (DES) to estimate capacity levels (Werker et al 2009), measure policy impact (Fletcher et al 2007), simulate patient scheduling (Lee et al 2013;Werker et al 2009;Quevedo and Chapilliquén 2015;Harper and Gamlin 2003) and aid strategic decision making (Leskovar et al 2011;Vanberkel and Blake 2007;Ballard and Kuhl 2006).…”

Maximising Patient Throughput using Discrete-event Simulation

“…The use of discrete-event simulation to model hospital departments is well documented in the literature (Jun, Jacobson and Swisher, 1999;Anderson and Merode, 2007;Gunal and Pidd, 2010). Studies include making strategic decisions for various departments (Ballard and Kuhl, 2006;Denton et al, 2006;Vanberkel and Blake, 2007;Leskovar et al, 2011); estimating capacity levels and measuring waiting times (Werker et al, 2009); analysing patient flows (Brenner et al, 2010;Zeng et al, 2012); measuring policy impact (Fletcher et al, 2007); and simulating patient scheduling and utilisations (Harper and Gamlin, 2003;Werker et al, 2009;Lee et al, 2013;Quevedo and Chapilliquén, 2014). It has been argued that the extensive use of process modelling is limited in healthcare compared with other industries (Harper and Pitt, 2004) due to the complexity of the processes and the vast amounts of data required to provide accurate models (Antonacci et al, 2016).…”

Maximising Patient Throughput using Discrete-event Simulation

“…Studies include making strategic decisions for various departments (Ballard and Kuhl, 2006;Denton et al, 2006;Vanberkel and Blake, 2007;Leskovar et al, 2011); estimating capacity levels and measuring waiting times (Werker et al, 2009); analysing patient flows (Brenner et al, 2010;Zeng et al, 2012); measuring policy impact (Fletcher et al, 2007); and simulating patient scheduling and utilisations (Harper and Gamlin, 2003;Werker et al, 2009;Lee et al, 2013;Quevedo and Chapilliquén, 2014). It has been argued that the extensive use of process modelling is limited in healthcare compared with other industries (Harper and Pitt, 2004) due to the complexity of the processes and the vast amounts of data required to provide accurate models (Antonacci et al, 2016).…”