187. Improving Emergency Department services scheduling through a hybrid Discrete Event Simulation and AI approach: an applied case study to the University Hospital of Bologna
Contributed abstract in session FA-5: Emergency Department /3, stream Regular talks.
Friday, 9:20-10:30Room: Room S6
Authors (first author is the speaker)
| 1. | Luca Zattoni
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| DEI, University of Bologna | |
| 2. | Andrea Eusebi
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| DEI, University of Bologna | |
| 3. | Cristiano Fabbri
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| DEI, University of Bologna | |
| 4. | Marco Leonessi
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| IRCCS Azienda Ospedaliero Universitaria di Bologna | |
| 5. | Enrico Malaguti
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| DEI, University of Bologna | |
| 6. | Paolo Tubertini
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| IRCCS Azienda Ospedaliero Universitaria di Bologna |
Abstract
Emergency Department (ED) plays a central role in many hospital contexts: with the aging of population and the increasing request for emergency services, the pressure on this structure and its staff has increased as well. While this represents a challenge, it's also an opportunity to highlight the potential impact of an effective quantitative-based decision making. Length of stay (LOS) is often used as a measure of the ED performance, reflecting the patient's experience. High LOS values might be considered as a symptom of overcrowding: this is one of the main problems in ED, as it could result in discomfort as well as aggravating patient conditions, and its causes usually lie in oversaturation of resources and inefficient services scheduling. In the scientific literature, simulation methods have been proved to be an effective tool to evaluate the ED dynamics, capable of considering the high variability in patients' emergency pathways, due to clinical criteria and required services. We propose a decision support framework, using a hybrid Discrete Event Simulation and Deep Learning paradigm, that aims to prevent overcrowding through dynamic queue management. By exploiting both structured and textual patient data, a predictive model is used to estimate the pathways development. This can be given as an input to the simulation replicating the behaviour of the system, so as to evaluate different policies for scheduling the required services, while considering patients' priorities.
Keywords
- Emergency Department
- Modelling and simulation
Status: accepted
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