Operating rooms scheduling for elective surgeries in a hospital affected by war-related incidents

• Main Authors: Ali, Hussein Hasan, Lamsali, Hendrik, Othman, Siti Norezam
• Format: Article
• Language: English
• Published: Springer US 2019
• Subjects: HD28 Management. Industrial Management
• Online Access: http://repo.uum.edu.my/26874/1/JMS%202019%2043%20139.pdf; http://repo.uum.edu.my/26874/; http://doi.org/10.1007/s10916-019-1263-z

Hospital scheduling presents huge challenges for the healthcare industry. Various studies have been conducted in many different countries with focus on both elective and non-elective surgeries. There are important variables and factors that need to be taken into considerations. Different methods and approaches have also been used to examine hospital scheduling. Notwithstanding the continuous changes in modern healthcare services and, in particular, hospital operations, consistent reviews and further studies are still required. The importance of hospital scheduling, particularly, has become more critical as the trade-off between limited resources and overwhelming demand is becoming more evident. This situation is even more pressing in a volatile country where shootings and bombings in public areas happened. Hospital scheduling for elective surgeries in volatile country such as Iraq is therefore often interrupted by non-elective surgeries due to war-related incidents. Hence, this paper intends to address this issue by proposing a hospital scheduling model with focus on neuro-surgery department. The aim of the model is to maximize utilization of operating room while concurrently minimizing idle time of surgery. The study focused on neurosurgery department in Al-Shahid Ghazi Al-Hariri hospital in Baghdad, Iraq. In doing so, a Mixed-integer linear programming (MILP) model is formulated where interruptions of non-elective surgery are incorporated into the main elective surgery based model. Computational experiment is then carried out to test the model. The result indicates that the model is feasible and can be solved in reasonable times. Nonetheless, its feasibility is further tested as the problems size and the computation times is getting bigger and longer. Application of heuristic methods is the way forward to ensure better practicality of the proposed model. In the end, the potential benefit of this study and the proposed model is discussed.