A knowledge-based scheduling system for Emergency Departments |
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| Authors: | ?afak K?r?? Nihat Yüzügüllü Nurdan Ergün A Alper Çevik |
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| Affiliation: | 1. Dumlup?nar University, Department of Industrial Engineering, Turkey;2. Eski?ehir Osmangazi University, Department of Industrial Engineering, Turkey;3. Eski?ehir Osmangazi University, Department of Emergency Medicine, Turkey;1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;2. School of Business, Renmin University of China, Beijing 100872, China;1. Industrial & Transportation Engineering Department, Universidade Federal do Rio Grande do Sul – UFRGS, 90035-190, Porto Alegre, RS, Brazil;2. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul 136-713, Republic of Korea;3. Departamento de Engenharia Mecânica, Universidade Federal de Minas Gerais – UFMG, Belo Horizonte, Brazil;1. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China;2. Centre for Systems Informatics Engineering, City University of Hong Kong, Hong Kong, China;1. University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK;2. School of Business and Economics, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK;3. Warwick Business School, University of Warwick, Coventry CV4 7AL, UK |
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| Abstract: | A knowledge-based reactive scheduling system is proposed to answer the requirements of Emergency Departments (EDs). The algorithm includes detailed patient priority, arrival time, flow time and doctor load. The main aim is to determine the patients who have higher priorities initially, and then minimize their waiting times. To achieve this aim, physicians and the other related workers can use an interactive system. In this study, we evaluated the existing system by comparing the proposed system. Also, reactive scheduling cases were evaluated for some items such as decreasing the number of doctors, changing durations and entering of an urgent patient to the system. All experiments were performed with proposed algorithm and right shift rescheduling approach. |
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