Title of article :
Emergency department resource optimisation for improved performance: a review
Author/Authors :
Ahsan, Kazi Badrul School of Chemistry - Physics and Mechanical Engineering - Science and Engineering Faculty - Queensland University of Technology - 2 George Street - Brisbane, QLD 4000, Australia , Alam, M. R School of Chemistry - Physics and Mechanical Engineering - Science and Engineering Faculty - Queensland University of Technology - 2 George Street - Brisbane, QLD 4000, Australia , Gordon Morel, Doug School of Chemistry - Physics and Mechanical Engineering - Science and Engineering Faculty - Queensland University of Technology - 2 George Street - Brisbane, QLD 4000, Australia , Karim, M. A School of Chemistry - Physics and Mechanical Engineering - Science and Engineering Faculty - Queensland University of Technology - 2 George Street - Brisbane, QLD 4000, Australia
Abstract :
Emergency departments (EDs) have been becoming increasingly congested due to the combined impacts of growing demand, access block and increased clinical capability of the EDs. This congestion has known to have adverse impacts on the performance
of the healthcare services. Attempts to overcome with this challenge have focussed largely on the demand management and the application of system wide process targets such as the “four-hour rule” intended to deal with access blocks.
In addition, EDs have introduced various strategies such as “fast tracking”, “enhanced triage” and new models of care such
as introducing nurse practitioners aimed at improving throughput. However, most of these practices require additional
resources. Some researchers attempted to optimise the resources using various optimisation models to ensure best utilisation
of resources to improve patient flow. However, not all modelling approaches are suitable for all situations and there is no
critical review of optimisation models used in hospital EDs. The aim of this article is to review various analytical models
utilised to optimise ED resources for improved patient flow and highlight benefits and limitations of these models. A range
of modelling techniques including agent-based modelling and simulation, discrete-event simulation, queuing models, simulation
optimisation and mathematical modelling have been reviewed. The analysis revealed that every modelling approach and
optimisation technique has some advantages and disadvantages and their application is also guided by the objectives. The
complexity, interrelationships and variability of ED-related variables make the application of standard modelling techniques
difficult. However, these models can be used to identify sources of flow obstruction and to identify areas where investments in additional resources are likely to have most benefit.
Keywords :
Optimisation , Emergency departments , Patient flow , Simulation , DES , ABMS
Journal title :
Journal of Industrial Engineering International