Determining efficient scheduling approach of doctors for operating rooms: An analysis on Al-Shahid Ghazi Al-Hariri hospital in Baghdad
Government hospitals in Iraq have long been suffering from overcrowded patients, and shortages of doctors and nurses. Unstable environment with occurrences of random warrelated incidents has put further burden on hospitals’ limited resources particularly the surgical department. Large number of pre-...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2018
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| Online Access: | https://etd.uum.edu.my/9545/1/s95988_01.pdf https://etd.uum.edu.my/9545/2/s95988_02.pdf https://etd.uum.edu.my/9545/3/s95988_references.docx https://etd.uum.edu.my/9545/ |
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| Summary: | Government hospitals in Iraq have long been suffering from overcrowded patients, and shortages of doctors and nurses. Unstable environment with occurrences of random warrelated incidents has put further burden on hospitals’ limited resources particularly the surgical department. Large number of pre-scheduled elective surgeries has occasionally been interrupted by the incoming war-related incidents patients. This in turn has put tremendous pressure on the hospital management to maximize utilization of its operating rooms’ resources including surgeons and nurses, whilst simultaneously minimizing idle time. Al-Shahid Ghazi Al-Hariri hospital in Baghdad is presently experiencing these issues. Therefore, this study has been undertaken with the aims to identify efficient scheduling approach for elective surgeries for operating rooms in Al-Shahid Ghazi Al-Hariri hospital while considering interruptions from non-elective surgery (incoming patients from warrelated incidents). Specifically, this study intends to develop a Mixed Integer Linear Programming (MILP) model to maximize the utilizations of operating rooms, availability of surgeons as well as to minimize potential idle time. A meta-heuristic approach in the form of a Tabu Search is then employed to generate an acceptable solution and utilizing time more efficiently. Real data was collected from the hospital in the form of interviews, observations and secondary reports. The initial MILP computational results show that the proposed model has successfully produced optimal solutions by improving the utilization of operating rooms. Notwithstanding, the difficulty to produce results in reasonable time for larger problem instances has led to the application of a more efficient meta-heuristic approach. The Tabu Search results indicated better performance of the model with good quality solutions in fewer computation times. The finding is important as it determines the feasibility of the proposed model and its potential benefit to all relevant stakeholders. |
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