Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital
Effective crew scheduling in hospitals with multiple personnel groups is essential for time efficiency and fair workload distribution. This study focuses on optimizing shift scheduling for a team of nurses, doctors, and caregivers working in the Pediatric Intensive Care Unit (PICU) of a university h...
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MDPI AG
2025-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/7/3610 |
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| author | Müfide Narlı Onur Derse |
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| description | Effective crew scheduling in hospitals with multiple personnel groups is essential for time efficiency and fair workload distribution. This study focuses on optimizing shift scheduling for a team of nurses, doctors, and caregivers working in the Pediatric Intensive Care Unit (PICU) of a university hospital. The model is implemented and solved using GAMS 23.5 software to minimize total staffing costs while ensuring balanced shift allocations. The scheduling process in PICUs is influenced by multiple factors, including staff skills, experience levels, personal preferences, contractual agreements, and hospital demands. Since these factors affect doctors, nurses, and caregivers differently, the model considers each personnel group separately while integrating them into a unified optimization framework. The proposed model successfully generates an annual optimal shift schedule for 10 doctors, 14 nurses, and 9 caregivers, ensuring equitable workload distribution and compliance with hospital regulations. By implementing this scheduling approach, employee satisfaction is enhanced, service quality is improved, and administrative workload is reduced. Additionally, the model ensures a well-balanced distribution of responsibilities, minimizes scheduling inefficiencies, and significantly reduces the time required for shift planning. Ultimately, this study provides a fast, fair, and cost-effective solution for hospital workforce management. |
| format | Article |
| id | doaj-art-e26b0ec209274e54bc9f8fd2d03e948b |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-e26b0ec209274e54bc9f8fd2d03e948b2025-08-20T02:09:13ZengMDPI AGApplied Sciences2076-34172025-03-01157361010.3390/app15073610Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University HospitalMüfide Narlı0Onur Derse1Department of Industrial Engineering, Faculty of Engineering, Çukurova University, Adana 01330, TürkiyeDepartment of Industrial Engineering, Faculty of Engineering, Tarsus University, Mersin 33400, TürkiyeEffective crew scheduling in hospitals with multiple personnel groups is essential for time efficiency and fair workload distribution. This study focuses on optimizing shift scheduling for a team of nurses, doctors, and caregivers working in the Pediatric Intensive Care Unit (PICU) of a university hospital. The model is implemented and solved using GAMS 23.5 software to minimize total staffing costs while ensuring balanced shift allocations. The scheduling process in PICUs is influenced by multiple factors, including staff skills, experience levels, personal preferences, contractual agreements, and hospital demands. Since these factors affect doctors, nurses, and caregivers differently, the model considers each personnel group separately while integrating them into a unified optimization framework. The proposed model successfully generates an annual optimal shift schedule for 10 doctors, 14 nurses, and 9 caregivers, ensuring equitable workload distribution and compliance with hospital regulations. By implementing this scheduling approach, employee satisfaction is enhanced, service quality is improved, and administrative workload is reduced. Additionally, the model ensures a well-balanced distribution of responsibilities, minimizes scheduling inefficiencies, and significantly reduces the time required for shift planning. Ultimately, this study provides a fast, fair, and cost-effective solution for hospital workforce management.https://www.mdpi.com/2076-3417/15/7/3610healthcare systempediatric intensive care unitoptimizationscheduling |
| spellingShingle | Müfide Narlı Onur Derse Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital Applied Sciences healthcare system pediatric intensive care unit optimization scheduling |
| title | Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital |
| title_full | Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital |
| title_fullStr | Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital |
| title_full_unstemmed | Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital |
| title_short | Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital |
| title_sort | optimal crew scheduling in an intensive care unit a case study in a university hospital |
| topic | healthcare system pediatric intensive care unit optimization scheduling |
| url | https://www.mdpi.com/2076-3417/15/7/3610 |
| work_keys_str_mv | AT mufidenarlı optimalcrewschedulinginanintensivecareunitacasestudyinauniversityhospital AT onurderse optimalcrewschedulinginanintensivecareunitacasestudyinauniversityhospital |