A game theoretic model of the behavioural gaming that takes place at the EMS - ED interface

Panayides, Michalis; Knight, Vince; Harper, Paul Robert

doi:10.1016/j.ejor.2022.07.001

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…The findings offer insurers directives for selecting payment models. Panayides et al [37] apply a game-theoretic model involving three parties, including emergency services. Simulation can also be used to analyze the interaction between multiple hospitals [38,39].…”

Section: Introductionmentioning

confidence: 99%

The Effects of Contract Mechanisms between the Government and Private Hospitals on the Social Utility

Teymourifar,

Kaya,

Ozturk

2023

Preprint

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In this work, we deal with a real healthcare system, in which public and private hospitals with different characteristics co-exist. While public hospitals have lower costs, they also suffer from long waiting times, diminishing the perceived quality of care for patients. Conversely, private hospitals, with their higher fees, offer shorter waiting periods, resulting in a more favorable perception of quality. A balanced healthcare system could offer societal benefits. Pricing strategies greatly influence a patient's hospital selection. For instance, reduced fees in private hospitals attract more patients, consequently reducing overcrowding in public facilities and elevating the overall quality of services provided. This study aims to develop pricing models to foster a balanced and socially advantageous healthcare system. Within this system, private hospital pricing is determined through contract mechanisms with the government. Thus, we delve into the ramifications of various contract models between the government and private hospitals on social utility. Our findings underscore the communal advantages of contract mechanisms. Furthermore, we generalize the proposed models to be applicable to similar systems.

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Section: Introductionmentioning

confidence: 99%

The Effects of Contract Mechanisms between the Government and Private Hospitals on the Social Utility

Teymourifar,

Kaya,

Ozturk

2023

Preprint

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Comprehensive review and future research agenda on discrete-event simulation and agent-based simulation of emergency departments

Ouda,

Sleptchenko,

Simsekler

2023

Simulation Modelling Practice and Theory

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Gamified recreational exercise focused on Markov Chains

Castellanos Flórez,

Duarte Amado,

Moreno Galvis

2024

Gamification and Augmented Reality

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The gamified recreational exercise focused on Markov Chains is an innovative methodology that combines learning with play to facilitate the understanding of statistical and mathematical concepts. Markov Chains are models that describe systems that transition between different states, where the probability of moving to a future state depends only on the current state and not on previous ones. By integrating game elements, such as challenges, rewards and competition, we seek to motivate students to actively engage in the learning process. This approach makes learning more engaging and gives participants a hands-on experience of how Markov Chains work in real situations. Exercises may include simulations, board games, or digital applications that represent scenarios where students must make decisions based on probabilities. Through gamification, teamwork and problem solving are encouraged, essential skills in today's world. The gamified recreational exercise is a favorable tool for teaching Markov Chains, it makes learning more dynamic and effective.

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A game theoretic model of the behavioural gaming that takes place at the EMS - ED interface

Cited by 3 publications

References 24 publications

The Effects of Contract Mechanisms between the Government and Private Hospitals on the Social Utility

The Effects of Contract Mechanisms between the Government and Private Hospitals on the Social Utility

Comprehensive review and future research agenda on discrete-event simulation and agent-based simulation of emergency departments

Gamified recreational exercise focused on Markov Chains

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