Volume 7, Issue 2 (9-2020)
jhbmi 2020, 7(2): 133-149 |
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Mahmoodi S, Afshar Kazemi M A, Toloie Eshlaghy A, Shadnoosh N. Modeling a Smart Hospital Information Architecture Based on Internet of Things and Recommender Agent. jhbmi 2020; 7 (2) :133-149
URL: http://jhbmi.ir/article-1-443-en.html
URL: http://jhbmi.ir/article-1-443-en.html
Modeling a Smart Hospital Information Architecture Based on Internet of Things and Recommender Agent
Ph.D. in Industrial Management, Associate Professor, Industrial Management Dept., Central Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract: (4074 Views)
Introduction: Today, healthcare organizations worldwide are aware of the significance of technology and its impact on the quality of care. Hospitals are one of the most crucial systems in which the utilization of information is particularly important for several reasons. Using discrete-event simulation and developing a recommender agent, this study aimed to allocate IoT devices to patients in such a way as to minimize the number of medical errors and the length of treatment.
Method: To carry out this research, first, the current condition of the medical care system was modeled using discrete-event simulation. Then, the scenario of introducing IoT into the model was simulated. Finally, using agent-based modeling, the recommender agent was developed to optimize the allocation of IoT devices to the patients.
Results: Implementing recommender agent in the simulation model indicated that using IoT and recommender agent in medical processes leads to reducing medical errors and length of treatment.
Conclusion: Utilizing the IoT in medical processes reduces errors, although the extent of its effectiveness varies at different stages of treating various diseases. Since some disease-specific IoT devices overlap in their functions, and given the limited number of these devices in hospitals, it is recommended that a recommender agent be used to ensure maximum effectiveness. Recommender agents make informed decisions as to how IoT devices can be efficiently allocated to patients at each stage of their treatment.
Method: To carry out this research, first, the current condition of the medical care system was modeled using discrete-event simulation. Then, the scenario of introducing IoT into the model was simulated. Finally, using agent-based modeling, the recommender agent was developed to optimize the allocation of IoT devices to the patients.
Results: Implementing recommender agent in the simulation model indicated that using IoT and recommender agent in medical processes leads to reducing medical errors and length of treatment.
Conclusion: Utilizing the IoT in medical processes reduces errors, although the extent of its effectiveness varies at different stages of treating various diseases. Since some disease-specific IoT devices overlap in their functions, and given the limited number of these devices in hospitals, it is recommended that a recommender agent be used to ensure maximum effectiveness. Recommender agents make informed decisions as to how IoT devices can be efficiently allocated to patients at each stage of their treatment.
Type of Study: Original Article |
Subject:
Health Information Systems
Received: 2019/09/29 | Accepted: 2020/03/3
Received: 2019/09/29 | Accepted: 2020/03/3
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