Volume 17, Issue 4 (2-2019)
jhosp 2019, 17(4): 57-65 |
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Dehghan I, Ostadi B, Hosseini S. Developing a Model for Dynamic Schedule of Heart Surgery based on Patient's Maximum Delay. jhosp 2019; 17 (4) :57-65
URL: http://jhosp.tums.ac.ir/article-1-6008-en.html
URL: http://jhosp.tums.ac.ir/article-1-6008-en.html
1- M.Sc. Student, Industrial Engineering, School of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
2- Assistant Professor, School of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran (*Corresponding author), Address: Room 909, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Nasr Bridge, Jalal AleAhmad Highway, Tehran, Iran, Email: bostadi@modares.ac.ir
3- Professor, Heart Valve Disease Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
2- Assistant Professor, School of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran (*Corresponding author), Address: Room 909, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Nasr Bridge, Jalal AleAhmad Highway, Tehran, Iran, Email: bostadi@modares.ac.ir
3- Professor, Heart Valve Disease Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
Abstract: (3580 Views)
Background: The operating rooms in each health center are one of the most sensitive units in the center, whereas scheduling and scheduling operations are in particular importance and their optimization has a significant effect on the optimization of the whole complex. The scheduling of heart surgery in addition to the limitations of manpower, time, and facilities includes the limitation of the patient's surgical deadline, which is the purpose of the surgical scheduling given this parameter.
Materials and Methods: In this quantitative study, an algorithm containing 3 + 1 function was proposed. This algorithm also addresses uncertainty while monitoring the limitations of available resources and the maximum delay for surgery. In this study, patients categorize to emergency and non-emergency patients which only the scheduling of non-emergency patients is considered. In this study 343 patient was studied.
Results: Based on a six-month period information reviewing from Shahid Rajaie Cardiovascular Center in Tehran, a 11% improvement has been made in respecting the maximum delay for the patient's referral process. The optimization rate is often related to the difference in patient selection based on their deadline for surgery, which in the present algorithm has been a major contributor to the denial of service patients. Another advantage of the proposed algorithm is the dynamic process of the algorithm and appropriate response to the changes.
Conclusion: The longer the length of the queue, the lower the chance of accepting non-emergency patients with the shorter maximum delays.
Materials and Methods: In this quantitative study, an algorithm containing 3 + 1 function was proposed. This algorithm also addresses uncertainty while monitoring the limitations of available resources and the maximum delay for surgery. In this study, patients categorize to emergency and non-emergency patients which only the scheduling of non-emergency patients is considered. In this study 343 patient was studied.
Results: Based on a six-month period information reviewing from Shahid Rajaie Cardiovascular Center in Tehran, a 11% improvement has been made in respecting the maximum delay for the patient's referral process. The optimization rate is often related to the difference in patient selection based on their deadline for surgery, which in the present algorithm has been a major contributor to the denial of service patients. Another advantage of the proposed algorithm is the dynamic process of the algorithm and appropriate response to the changes.
Conclusion: The longer the length of the queue, the lower the chance of accepting non-emergency patients with the shorter maximum delays.
Type of Study: Original Article |
Subject:
سیاست گذاری ، برنامه ریزی و رهبری و مدیریت در بیمارستان
Received: 2018/05/30 | Accepted: 2019/01/12 | Published: 2019/01/26
Received: 2018/05/30 | Accepted: 2019/01/12 | Published: 2019/01/26
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