Developing a Model for Dynamic Schedule of Heart Surgery based on Patient\'s Maximum Delay
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
| Published: |
Tehran University of Medical Sciences
2019-02-01
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| Series: | بیمارستان |
| Subjects: | |
| Online Access: | http://jhosp.tums.ac.ir/article-1-6008-en.html |
| Summary: | 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 patientchr('39')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 patientchr('39')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. |
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| ISSN: | 2008-1928 2228-7450 |