An agent-based decision support model for assessment of stroke patient transport policies: The case of choosing hospital for diagnosis

Abstract: The Southern Swedish hospital region is the home of nearly 2 million people, inwhich 5,684 individuals were diagnosed by stroke during 2016, according tostatistics from the hospitals in the region. With this large number ofstroke-diagnosed patients across the region, an effective stroke transport policy isinevitably important to provide fast treatment for these patients.In this thesis, we developed an agent-based simulation model for evaluating theperformance of transport logistics policies. We followed the Design ScienceResearch methodology in order to design and develop the model. Using the model,we assessed two transport logistics policies for the Southern Swedish hospitalregion. We used a synthetic set of stroke patients, which we generated using Montecarlo simulation, for the processes of developing the model and assessing our twostroke transport logistics policies.We argue that the assessment of transport logistics policies is important for theability to improve the planning process, for example, when choosing hospital fordiagnosis of patients showing stroke symptoms. The optimization of the strokelogistics process aims to ensure the quality and operational efficiency of the hospitalsector as well as to increase the chance of survival of stroke patients.