Determining optimal policy for emergency department using Markov decision process

Emergency departments (ED) are faced with the challenge of capacity planning that caused by the high demand for patients and limited resources. Consequently, inadequate resources lead to increased delays, impacts on the quality of care and increase the health-care costs. Such circumstances necessitate utilizing operational research modules, such as the Markov decision process (MDP) to enable better decision-making. The purpose of this paper is to demonstrate the applicability and usage of MDP on ED.

The adoption of MDP provides invaluable insights into system operations based on the different system states (e.g. very busy to unoccupied) to ensure optimal assigning of resources and reduced costs. In this paper, a descriptive health system model based on the MDP is presented, and a numerical example is illustrated to elaborate its appropriateness in optimal policy decision determination.

Faced with numerous decisions, hospital managers have to ensure that the appropriate technique is used to minimize any undesired outcomes. MDP has been shown to be a robust approach which provides support to the critical decision-making processes. Additionally, MDP also provides insights on the associated costs which enable the hospital managers to efficiently allocate resources ensuring quality health care and increased throughput while minimizing costs.

Applying MDP in the ED is a unique and good starting. MDP is powerful tool helps in making a decision in the critical situations, and the ED needs such tool.