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Journal articles on the topic 'Nurse scheduling'
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Utina, Fitriani, Lailany Yahya, and Nurwan Nurwan. "Nonpreemptive Goal Programing Method in Optimization Nurse Scheduling by Considering Education Level." Jurnal ILMU DASAR 22, no. 2 (2021): 85. http://dx.doi.org/10.19184/jid.v22i2.16939.
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Nurse scheduling is one of the problems that often arise in hospital management systems. Head of ICU room and nurse to cooperate in making good nurse scheduling for the creation of optimal service. In this paper, we study a hospital nurse schedule design by considering the level of nurse education and the provision of holidays. Nurses with undergraduate education (S1) Nurses become leaders on every shift and are accompanied by nurses with diploma education (D3). The scheduling model in this study using the nonpreemptive goal programming method and LINGO 11.0 software. The preparation of the schedule of nurses assigned to this method can optimize the need for efficient nurses per shift based on education level. The data in the research was obtained by collecting administrative data at Aloei Saboe Gorontalo hospital. The data used are the published schedule by the head of the ICU room. In making a nurse schedule, there are limitations to consider such ashospital regulation. The results of the study obtained an optimal solution in the form of meeting all the desired obstacles. Computational results shows that nurse scheduling using the nonpreemptive goal programming method and LINGO 11.0 software better than the schedule created manually. Every shift is a maximum of one leader with an undergraduate education (S1) background and accompanied by a nurse with a diploma education (D3) background. Keywords: scheduling, goal programming, nonpreemptive goal programming.
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Leksakul, Komgrit, and Sukrit Phetsawat. "Nurse Scheduling Using Genetic Algorithm." Mathematical Problems in Engineering 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/246543.
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This study applied engineering techniques to develop a nurse scheduling model that, while maintaining the highest level of service, simultaneously minimized hospital-staffing costs and equitably distributed overtime pay. In the mathematical model, the objective function was the sum of the overtime payment to all nurses and the standard deviation of the total overtime payment that each nurse received. Input data distributions were analyzed in order to formulate a simulation model to determine the optimal demand for nurses that met the hospital’s service standards. To obtain the optimal nurse schedule with the number of nurses acquired from the simulation model, we proposed a genetic algorithm (GA) with two-point crossover and random mutation. After running the algorithm, we compared the expenses and number of nurses between the existing and our proposed nurse schedules. For January 2013, the nurse schedule obtained by GA could save 12% in staffing expenses per month and 13% in number of nurses when compare with the existing schedule, while more equitably distributing overtime pay between all nurses.
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Rizany, Ichsan, RR Tutik Sri Hariyati, and Efi Afiyanti. "Penjadwalan Dinas terhadap Kepuasan Perawat di Rumah Sakit Y Jakarta." Dunia Keperawatan: Jurnal Keperawatan dan Kesehatan 8, no. 2 (2020): 320. http://dx.doi.org/10.20527/dk.v8i2.8875.
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Nurse satisfaction in hospitals in Indonesia was still low. The low level of nurse discharge was influenced by a number of factors. The purpose of this study was to determine the relationship between nursing scheduling and patient satisfaction at Y Hospital Jakarta. The method used in this study was cross-sectional. The number of samples was 32 nurses (n = 32) through a stratified random sampling technique. The study was conducted at Y Hospital Jakarta. Inclusion criteria included implementing nurses who worked at least 1 year and were willing to become respondents. Data were analyzed by the Pearson correlation test. The results showed that the average patient satisfaction was 73, while the nurse's scheduling was 90.29. These results indicated that nurse satisfaction was still below the minimum service standard (SPM). This result also showed that there was a significant relationship between nursing scheduling and nurse satisfaction (p = 0.040; r = 0.349). The conclusion of this study was that there was a significant relationship between nursing scheduling and nurse satisfaction at Y Hospital. Recommendations were given to hospital managers to improve nurse satisfaction by managing to nurse scheduling properly
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Suppiah, Yasothei. "An Integer Programming Model for a Nurse Scheduling Problem." International Journal of Membrane Science and Technology 10, no. 2 (2023): 1180–85. http://dx.doi.org/10.15379/ijmst.vi.1401.
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This paper addresses a nurse scheduling problem that is present in a hospital. In order to accommodate the rising cost of sustaining and maintaining the hospital, there is a demand to analyse the manpower scheduling problem by not compromising the needs of the patients. Therefore, this study aims to apply a mathematical method to find the optimal number of nurses to be assigned for duties each day and shift in a hospital. An integer linear programming model is developed to represent the nurse scheduling problem. The mathematical model is solved by using the QM for windows software and the results provides an optimal solution to the nurse scheduling problem.
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Rerkjirattikal, Pavinee, Van-Nam Huynh, Sun Olapiriyakul, and Thepchai Supnithi. "A Goal Programming Approach to Nurse Scheduling with Individual Preference Satisfaction." Mathematical Problems in Engineering 2020 (November 22, 2020): 1–11. http://dx.doi.org/10.1155/2020/2379091.
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The use of scheduling optimization tools is essential in creating an efficient nurse shift-rotation schedule. A well-designed nurse scheduling technique can improve nurses’ job satisfaction and their intention to stay. This study develops a goal programming approach to nurse scheduling that simultaneously considers workload fairness and individual preferences on working shift and day off assignments. A case study of an operating room at a hospital in Thailand is used to illustrate the model capabilities for solving an actual nurse scheduling problem. The job satisfaction factors defined based on an interview and questionnaire survey are integrated into the model. When compared against the manual scheduling result, the optimal schedules can be implemented to improve the nurse’s perception of fairness and preference satisfaction. The analysis of fairness and multiple individual preferences based on a case study investigation is the main contribution of this study.
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Zunaedi, Rosly, Soenarnatalina Melaniani, and Ahsan Ahsan. "Assessment of The Characteristics of Nurse Scheduling in Hospital Ward." STRADA Jurnal Ilmiah Kesehatan 9, no. 2 (2020): 1755–62. http://dx.doi.org/10.30994/sjik.v9i2.528.
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Good scheduling arrangements are needed to prevent physical, emotional, and psychological exhaustion in nurses which will harm their performance. The aim is to see an assessment of the characteristics of nurse work scheduling in the hospital ward. This study used a descriptive survey design. The population in this study were all nurses in the ward of Lavalette Hospital - Malang. The sampling technique used was simple random sampling. Data collection using a scheduling characteristic questionnaire. Most of the respondents considered that the work scheduling criteria currently applied in the ward were in the sufficient category (80.2%). There are sub-variable coverage (309) and quality (321) less than the average value (322.08). The problems that arise in the nurse scheduling in the ward of Lavalette Hospital - Malang are the suitability of amount and distribution of nurses, quality of the schedule, an exchange between nurses, and time to prepare the schedule.
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Samosir, Larry Ronaldo, and Faiz Ahyaningsih. "Application of the Goal Programming Method in Nurse Scheduling at RSUD Dr. Hadrianus Sinaga Pangururan." Indonesian Journal of Advanced Research 2, no. 7 (2023): 965–82. http://dx.doi.org/10.55927/ijar.v2i7.4898.
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The purpose of this study was to establish an effective and optimal nurse schedule at the Regional General Hospital dr. Hadrianus sinaga Pangururan. RSUD dr.Hadrianus Sinaga Pangururan is still scheduling nurses manually with a total of 20 nurses and has three work shifts namely morning, afternoon and evening. As a result of manual scheduling, it takes quite a long time and is less efficient due to imbalances in the distribution of shifts. The method used to solve nurse scheduling problems is Goal Programming. Goal Programming is the development of linear programs that are used to solve linear programming problems with multiple objective functions. In modeling this scheduling problem, there are two systems of constraints that must be met, namely the main constraints and additional constraints. The main obstacle is hospital rules that must be complied with while additional obstacles are hospital rules that are still given tolerance for violations. In modeling the nurse scheduling problem, each problem is converted into a mathematical model and the completion of the goal programming model is assisted by LINGO software. From the LINGO output, the results show that nurse scheduling using goal programming meets all system constraints, while the hospital's manual schedule does not meet system constraints.
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Hung, Rudy. "Hospital Nurse Scheduling." JONA: The Journal of Nursing Administration 25, no. 7 (1995): 21–23. http://dx.doi.org/10.1097/00005110-199507000-00010.
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Rosenbloom, E. S., and N. F. Goertzen. "Cyclic nurse scheduling." European Journal of Operational Research 31, no. 1 (1987): 19–23. http://dx.doi.org/10.1016/0377-2217(87)90131-7.
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Hesaraki, Alireza F., Nico P. Dellaert, and Ton de Kok. "Integrating nurse assignment in outpatient chemotherapy appointment scheduling." OR Spectrum 42, no. 4 (2020): 935–63. http://dx.doi.org/10.1007/s00291-020-00596-8.
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Abstract In outpatient chemotherapy, nurses administer the drugs in two steps. In the first few minutes of each appointment, a nurse prepares the patient for infusion (drug administration). During the remainder of the appointment, the patient is monitored by nurses and if needed taken care of. One nurse must be assigned to prepare the patient and set up the infusion device. However, a nurse who is not busy setting up may simultaneously monitor up to a certain number of patients who are already receiving infusion. The prescribed infusion durations are significantly different among the patients on a day at a clinic. We formulate this problem as a multi-criterion mixed integer program. The appointments should be scheduled with start times close to patients’ ready times, balanced workload among nurses, few nurse changes during appointments, and few nurse full-time equivalent (FTE) assigned to the schedule of the day. As the number of nurse FTEs is an output of the model rather than a fixed input, the clinic can use the nursing capacity more efficiently, i.e., with less labor cost. We develop a 3-stage heuristic for finding criterion points with the minimum weighted average deferring time of appointments for the minimum feasible number of nurse FTEs or a desired value above that. By not constraining the number of chairs or beds, we can find solutions with better (dominating) criterion points. Drug preparation, oncologist visit, and the laboratory test can be scheduled based on the drug administration appointment start time. Thus, the drug administration resources are efficiently used with desirable performance in taking the interests and requirements of various stakeholders into consideration: patients, nurses, oncologists, pharmacy, and the clinic.
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Christopher, A. OYELEYE, and O. OLADELE Grace. "MODIFIED GENETIC ALGORITHM FOR SOLVING NURSE SCHEDULING PROBLEM." International Research Journal of Computer Science VII, no. IV (2020): 33–41. https://doi.org/10.26562/irjcs.2020.v0704.002.
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The Nurse scheduling problem (NSP) represents a difficult class of Multi-objective optimization problems consisting of number of interfering objectives between the hospitals and individual nurses. Several constraint-based optimization techniques have been proposed to solve automated nursing scheduling problems in an acceptable computation time but most of these techniques are characterized by premature convergences which inhibit optimal global solution. Thus, a Modified Genetic Algorithm (MGA) was developed to solve Nurse Scheduling Problem. The Modified Genetic Algorithm will be implemented by using Matrix Laboratory (MATLAB) software.
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Rizany, Ichsan, Tutik Sri Hariyati, and Sri Purwaningsih. "OPTIMALISASI FUNGSI KEPALA RUANGAN DALAM PENETAPAN JADWAL DINAS PERAWAT BERBASIS KOMPETENSI: PILOT STUDY." Jurnal Persatuan Perawat Nasional Indonesia (JPPNI) 1, no. 3 (2017): 244. http://dx.doi.org/10.32419/jppni.v1i3.35.
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e"> ABSTRAKTujuan penelitian: melakukan pemberdayaan fungsi kepala ruangan dalam implementasi jadwaldinas berbasis kompetensi di rumah sakit umum vertikal kelas A yang menjadi rumah sakit pusatrujukan nasional. Metode: pendekatan pilot studi yang dilaksanakan dari analisis situasi, pembuatanplan of action, implementasi, evaluasi dan analisis gap menggunakan literatur review. Pilot studidilakukan selama ± 7 minggu kepada 43 perawat dan 16 kepala ruangan sebagai responden.Analisis situasi dilakukan dengan menggunakan diagram fi sh bone. Hasil: Masalah utama ialahbelum optimalnya pelaksanaan jadwal dinas berbasis kompetensi. Implementasi yang dilakukanialah brainstorming kepada kepala ruangan tentang pentingnya kompetensi dalam pelaksanaanjadwal dinas dan melakukan uji coba jadwal dinas berbasis kompetensi. Hasil uji coba didapatkanbahwa 100% kepala ruangan merasa jadwal dinas berbasis kompetensi lebih efektif. Hasil kuesionermenunjukkan adanya peningkatan pengetahuan kepala ruangan tentang pentingnya kompetensidalam penjadwalan perawat menjadi 8,6 dan rata-rata penilaian diri (self asessment) dari kepalaruangan tentang evaluasi pembuatan jadwal dinas berbasis kompetensi sebesar 7,88 dari 10 poin.Pelaksanaan penjadwalan berbasis kompetensi mendapat hambatan berupa kurangnya jumlahtenaga perawat, karakteristik perawat, dan pemerataaan kompetensi. Simpulan: pemberdayaanfungsi kepala ruangan dalam implementasi jadwal dinas berbasis kompetensi lebih efektif danmemudahkan pekerjaan kepala ruangan dalam pengaturan jadwal dinas. Peran kepala ruangansangat penting dalam pembuatan jadwal dinas berbasis kompetensi. Peran kepala bidangkeperawatan sangat membantu sistem jadwal dinas dengan membuat kebijakan yang tepat dansejalan dengan misi pelayanan keperawatan untuk memberikan pelayanan berkualitas dan aman.Kata Kunci: jadwal dinas, kompetensi, perawat.OPTIMIZATION THE FUNCTION OF THE HEAD NURSE IN DETERMINING COMPETENCEBASED NURSE SERVICE SCHEDULE: A PILOT STUDYABSTRACTObjective: To empower the function of head nurse in implementing competence-based nurse serviceschedule in grade A hospital which serves as a national referral hospital. Methods: This studyemployed a pilot study approach that was performed in situation analysis, making of Plan of Action,implementation, evaluation and gap analysis using literature review. The pilot study was conductedfor approximately 7 weeks to 43 nurses and 16 head nurses as respondents. The situation analysiswas performed using fi shbone diagram. Results: The main problem was unoptimal implementationof competence-based nurse service schedule. The implementation done was brainstorming tothe head nurses about importance of competence in the implementation of service schedule andconducting trial of the competence-based nurse service schedule. The trial results indicated that100% of the head nurses thought that the competence-based nurse service schedule was moreeffective. The questionnaire results indicated increased head nurses’ knowledge of the importanceof competence in nurse scheduling by 8.6, and average self-assessment of the head nurseson the evaluation of competency-based nurse service scheduling by 7.88 out of 10 points. Theimplementation of competence-based scheduling was obstructed by lack of the number of nurses,characteristics of nurses and even distribution of competence. Conclusion: The empowerment ofthe function of head nurses in the implementation of competence-based nurse service schedule wasmore effectively and could facilitate the work of head nurses in managing the service schedule. The role of head nurses was very important in competence-based nursing service scheduling. The roleof head nurses was useful in nurse service schedule system by making appropriate policy and wasin line with the mission of nursing care in providing quality and safe service.Keywords: nurse scheduling, competence, nurse
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Rizany, Ichsan, Hanny Handiyani, Hening Pujasari, Dadan Erwandi, and Cicilia Ika Wulandari. "Self-scheduling for nurse: A concept analysis." Multidisciplinary Reviews 8, no. 1 (2024): 2025021. http://dx.doi.org/10.31893/multirev.2025021.
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Quality nursing care must be supported by appropriate nurse scheduling arrangements. Inappropriate nursing scheduling harms nurses’ work. Clarification of terms is necessary to inform nurses and service managers, promote consistent theoretical and operational definitions in research, and develop prevention strategies to provide quality nursing care. This research aims to clarify the meaning of the concept of self-scheduling. The design used is concept analysis. Data sources were searched from electronic databases (Sciendirect, Google Schoolar, Taylor & Francis, SpringerLink, and IEEE). The Walker & Avant method was applied to guide the concept analysis to identify and define attributes, antecedents, and consequences. Self-scheduling has seven attributes: service schedule, flexibility, autonomy, demands, conditions and capabilities, and responsibility. The antecedents include the number of staff, competence, self-efficacy, motivation, work experience, education, age, and career ladder. Proper self-scheduling has positive effects, such as on job satisfaction, work safety, patient safety, and work‒life balance. The negative consequences of self-scheduling include workload, fatigue and stress. The conclusion is that self-scheduling is very important, and the implementation of self-scheduling on nurses' service schedules that are not quite right contributes to shift work and patient safety.
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Ika Nur Habibah, Fawwaz Ali Akbar, and Made Hanindia Prami Swari. "Aplikasi Penjadwalan Daftar Jaga Perawat Dengan Menerapkan Algoritma Genetika." Jurnal Ilmiah Teknik Informatika dan Komunikasi 5, no. 2 (2025): 419–35. https://doi.org/10.55606/juitik.v5i2.1126.
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A web-based nurse scheduling application utilizing a genetic algorithm is designed to optimize the arrangement of nurses’ work schedules in hospitals, which is often a challenge due to the need to consider various critical factors. The purpose of developing this application is to assist head nurses in efficiently creating nurse work schedules, while considering shift distribution, weekly working hour limits, provision of two days off per week, and the prohibition of assigning a night shift followed directly by a morning shift to ensure sufficient rest for nurses. This application is built using the CodeIgniter 3 framework, PHP programming language, and MySQL database. By leveraging the genetic algorithm, the system can automatically find the best schedule combinations and reduce violations of nurse scheduling rules. Test results show that the application can automatically generate schedules that comply with hospital regulations and requirements, and significantly accelerate the scheduling process compared to manual methods. Furthermore, the fitness value and schedule generation time produced are influenced by parameters such as population size, number of generations, mutation rate, and tournament size used.
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D’souza, Brayal, Shreyas Suresh Rao, Chepudira Ganapathy Muthana, et al. "ROTA: A system for automated scheduling of nursing duties in a tertiary teaching hospital in south India." Health Informatics Journal 27, no. 2 (2021): 146045822110014. http://dx.doi.org/10.1177/14604582211001426.
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The nursing schedule generation is an important activity that takes a considerable amount of time for managers to prepare and amend. It involves the optimal allocation of nurses to shifts, factoring various constraints like shift timings, holidays, leaves, and emergencies. This paper provides the design and development details for an automated nurse scheduling system called “ROTA,” implemented for a 2032 bed multi-specialty tertiary teaching hospital, having 1800 staff nurses and 98 wards. The system generates daily, weekly, monthly schedules, nurse face sheets, duty allocation charts, swapping schedules, and training details for nurses. The system improved managerial control and saved a considerable amount of time for nurses to prepare the schedule. A survey conducted to gauge the system’s satisfaction level showed that 91% of nurses were satisfied with ROTA. Overall, the system saved 78% of nurse scheduling time, resulting in a 3% cost reduction for the hospital.
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Mohd Nasir, Diana Sirmayunie, Nurul Hahani Che Baharom, Nor Hayati Shafii, and Nor Azriani Mohamad Nor. "Cyclical Nurse Scheduling in Shah Alam Hospital Using Goal Programming." Journal of Computing Research and Innovation 6, no. 1 (2021): 1–10. http://dx.doi.org/10.24191/jcrinn.v6i1.175.
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A shift work schedule is extremely important to obtain the optimum result of work allocation since it involves 24 hours of continuous services. Every nurse could not avoid shift work schedule since their services are very important towards the patients in the hospital. The major objective of the study is to propose a cyclical nurse scheduling in the Coronary Care Unit (CCU) at Shah Alam hospital using Goal Programming. It is to help the head nurse to spend less effort on building new schedules periodically and increase the satisfaction among nurses by providing fairness towards their schedules. There were nine hard constraints and three soft constraints for the nurse scheduling model. The results presented the optimal solution where all goals were achieved thus, it provided a fair schedule for 15 nurses in 15 days. Then, the schedule pattern was rotated among nurses based on the 15 schedules set in 225 days. The first schedule set will be used by the nurse for the first 15 days, then will be continuously rotated for another 15 days until all the nurses reached and experienced every 15 sets of the schedule. The schedule was generated using LINGO software which it took a short time to solve the problem.
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Zhang, Zhichao. "Nurse Scheduling Algorithms based on Different Scenarios." Frontiers in Computing and Intelligent Systems 4, no. 2 (2023): 12–16. http://dx.doi.org/10.54097/fcis.v4i2.9700.
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This algorithm is based on a combination of integer programming, genetic algorithm, and decision tree to study nurse scheduling management problems in different scenarios. Firstly, the usage scenarios are classified based on the number of department members and energy levels. Then, the initial solution is obtained through integer programming based on information such as the actual energy level of nurses in the hospital. Finally, genetic algorithm is used to optimize the initial solution to obtain a final solution that is more in line with practical requirements. This algorithm can automatically classify or manually set use scenarios, and automatically obtain shift scheduling information by entering personalized parameters, which can meet the personal shift scheduling needs of nurses to the greatest extent, and can greatly reduce the high-frequency shift scheduling workload of Matron.
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Nuñez, Guia Marie R., and Joan P. Bacarisas. "Perceived Roles and Support of Preceptors on Work Role Functions of Nurses in Ormoc City." International Journal of Research and Scientific Innovation XII, no. III (2025): 186–220. https://doi.org/10.51244/ijrsi.2025.12030013.
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Work role function is important in every organization especially when coupled with roles and support. This study examined the interrelationship among personal characteristics, perceived roles and support, and work role function of nurses in selected hospitals in Ormoc City, Leyte, during the fourth quarter of 2024. It explored how age, sex, marital status, education, and hospital classification influenced nurses’ perceptions of roles, support, and work demands, including scheduling, physical, mental, social, and flexibility aspects. The study also assessed the correlation between senior nurse support and nurses’ work role functioning. Statistical treatments used included frequency distribution and simple percentage, mean score and standard deviation, summation of scores, chi square with Cramer’s V and Pearson r. Younger, single nurses expressed higher preceptorship needs, while those with advanced education reported greater confidence in handling work demands. Findings showed that senior nurse support positively correlated with work demands across scheduling, output, physical, mental, social, and flexibility dimensions. Effective preceptorship improved adaptability, resilience, and decision-making skills, reducing burnout and enhancing job satisfaction. In conclusion, preceptorship and senior nurse support are crucial for optimizing work role functioning in demanding healthcare settings. Recommendations included structured mentorship programs, ergonomic training, enhanced mental health support, and flexible scheduling. Future research should examine the long-term impacts of preceptorship and tailor interventions to diverse nurse demographics, contributing to improved staff well-being and patient care outcomes.
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Cheng, Mingang, Hiromi Itoh Ozaku, Noriaki Kuwahara, Kiyoshi Kogure, and Jun Ota. "Dynamic Scheduling in Inpatient Nursing." International Journal of Automation Technology 3, no. 2 (2009): 174–84. http://dx.doi.org/10.20965/ijat.2009.p0174.
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To shorten the notoriously long waits for service in hospitals in Japan and to improve efficiency, we propose a scheduling algorithm with a 2-layer local search based on simulated annealing -- permutating (switching) (i) tasks among nurses and (ii) subtasks on each nurse. The scheduling algorithm generates a solution initializing our proposed dynamic scheduling to iteratively generate new, feasible schedules based on the scheduling algorithm to accommodate interruptions while preventing nurses' work hours from increasing. To verify the effectiveness of our proposed scheduling, we executed a set of nursing scheduling problems taken from those actually observed and focused on those that featuring frequent interruptions.
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Hu, Y., and T. Zhu. "N27 Impact of Anaesthetic Nurse Scheduling Patterns on Resuscitation Outcomes after Painless Gastrointestinal Endoscopy in Patients with Inflammatory Bowel Disease." Journal of Crohn's and Colitis 19, Supplement_1 (2025): i2483. https://doi.org/10.1093/ecco-jcc/jjae190.1559.
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Abstract Background Nurse anesthetists in the post-anesthetic care unit (PACU) of the Gastrointestinal Endoscopy Center monitor and manage complications following endoscopy procedures. We examined the impact of nurse anesthetist scheduling patterns on resuscitation efficiency of inflammatory bowel disease (IBD) patients in the anesthesia recovery room after painless gastrointestinal endoscopy. Methods This was a retrospective analysis of IBD patients who underwent resuscitation following painless gastrointestinal endoscopy at a large tertiary care IBD clinic. Two anesthetic nurse practitioner scheduling models were compared: In 2022 (before-reform, BR), the scheduling model consisted of three anesthetic nurse practitioners (N1, N2, N3) with a nurse-to-resuscitation bed ratio of 1.5:1. In 2023 (after-reform, AR), the scheduling template was adjusted to reduce one N2 anesthesia nurse (nurse-to-resuscitation bed ratio of 1:1). The number of consultations, length of stay, complications, anesthesia nurses' satisfaction and patient satisfaction were compared between BR and AR groups. Results 211 and 246 patients with IBD were resuscitated in the PACU after painless gastrointestinal endoscopy in 2022 and 2023, respectively. The median length of stay in the PACU decreased significantly from 27.30 min (25.10–28.98) before the reform to 22.30 min (20.20–24.70) after the reform (p<0.001). There was no significant difference in the occurrence of complications following the implementation of the reform (hypoxemia, hypotension, nausea and vomiting, abdominal distension, pain, coughing, hypersomnia) (p=0.354). The anesthesia nurse practitioners were more satisfied with the reformed scheduling pattern, which mirrored the improved satisfaction among IBD patients. Conclusion The reformed anesthesia nurse scheduling model yielded improved resuscitation efficiency, reduced costs, and improved satisfaction of nurse anesthetists and IBD patients. Further studies are required to validate these findings. References [1].Elmunzer BJ, Anderson MA, Mishra G, Rex DK, Yadlapati R, Shaheen NJ. Quality Indicators Common to All Gastrointestinal Endoscopic Procedures. Am J Gastroenterol. 2024 . [2].ASGE Ensuring Safety in the Gastrointestinal Endoscopy Unit Task Force, , Calderwood AH, et al. Guidelines for safety in the gastrointestinal endoscopy unit. Gastrointest Endosc. 2014. 79(3): 363-72. [3].Luckowski A. Safety priorities in the PACU. Nursing. 2019. 49(4): 62-65. [4].Dolinger M, Torres J, Vermeire S. Crohn's disease. Lancet. 2024. 403(10432): 1177-1191.
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Zheng, Shaoxin, Ting Li, Ming Han, and Meijuan Wu. "Coping strategies for nurse burnout：Combination of psychological counselling and institutional safeguards." International Theory and Practice in Humanities and Social Sciences 2, no. 4 (2025): 181–94. https://doi.org/10.70693/itphss.v2i4.321.
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With the increasing complexity of the healthcare environment, the issue of nurse burnout has gradually received attention. Based on the operating room, emergency centre, ICU and outpatient clinic of a tertiary hospital in Guangzhou City, this study explores the relationship between the scheduling system, psychological support and nurse burnout, and provides a basis for the development of intervention strategies; this study uses Burnout Theory and Demand-Control-Support Model as the theoretical basis for designing a questionnaire containing three dimensions: scheduling system, psychological support and nurse burnout. Burnout Theory and Demand-Control-Support Model As the theoretical basis, this study designed a questionnaire containing three dimensions: scheduling system, psychological support and burnout. Descriptive statistics, reliability and validity tests, and correlation analyses were conducted using SPSS 22.0 on 124 nurses; the study showed that nurses generally had a high level of burnout (mean value 4.82), scheduling system had a significant negative correlation with psychological support (r=-0.390, p<0.01), scheduling system had a weak negative correlation with burnout (r=- 0.212, p<0.01), and scheduling system had a weak negative correlation with burnout (r=- 0.212, p<0.01). 0.212, p<0.05), and a non-significant correlation between psychological support and burnout (r=0.36, p=0.688), proving that the current psychological support measures have limited effect or are insufficient to meet the needs of the nursing workforce; the existing scheduling arrangement leads to work-life imbalance, which increases the need for psychological support; however, the existing psychological support measures have not yet been effective in improving burnout.
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Ananda, Rizky, Zulfahmi Indra, and Hamidah Nasution. "Application of Graph Coloring on Nurse Work Scheduling at H. Adam Malik Hospital Medan Using the Tabu Search Algorithm." ZERO: Jurnal Sains, Matematika dan Terapan 6, no. 1 (2022): 1. http://dx.doi.org/10.30829/zero.v6i1.12451.
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<p>Complex problems that usually occur in every hospital, one of which is scheduling with so many aspects, for example: the number of nurses, the distribution of nurse shifts, time off or leave and others. With the manual method that is still used in compiling the nurse's work schedule, it makes it difficult for an irregular and regular schedule. In solving the scheduling problem, the graph coloring method can be used. This scheduling problem can be solved by graph coloring. One solution to solve the problem of concluding graphs in scheduling is the Tabu Search Algorithm. A method that works as an effective problem solving method in finding the best solution to a problem. A method is used to solve the problem by making a representation in the form of a graph where the nurse is a node and grouping nurses as an edge by implementing the graph coloring into the Tabu Search Algorithm.</p>
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Sugianto, Kartika Mawar Sari, Rr Tutik Sri Hariyati, Hening Pujasari, Enie Novieastari, and Hanny Handiyani. "Nurse workforce scheduling: A qualitative study of Indonesian nurse managers’ experiences during the COVID-19 pandemic." Belitung Nursing Journal 8, no. 1 (2022): 53–59. http://dx.doi.org/10.33546/bnj.1735.
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Background: The increase in COVID-19 cases in Indonesia has resulted in changes in the hospital workflow, including the staffing process and scheduling, especially in the isolation units. Nurse managers are working hard in the scheduling system to ensure high-quality care is provided with the best human resources.
 Objective: This study aimed to explore the experiences of nurse managers in managing staff nurses’ work schedules during the COVID-19 pandemic.
 Methods: A qualitative descriptive design was used in this study. Eleven nurse managers from three COVID-19 referral hospitals were selected using purposive sampling. Data were collected using online semi-structured interviews. Thematic analysis was used for data analysis, and data were presented using a thematic tree. Consolidated criteria for reporting qualitative research (COREQ) checklist was used as a reporting guideline of the study.
 Results: Four themes were developed: (i) Nurse shortage, (ii) Strategically looking for ways to fulfill the workforce, (iii) Change of shift schedule, and (iv) Expecting guidance from superiors and compliance from staff.
 Conclusion: The lack of nurse staff is a problem during a pandemic. Thus, managing personnel effectively, mobilizing and rotating, and recruiting volunteers are strategies to fulfill the workforce during the pandemic. Using a sedentary shift pattern and sufficient holidays could prevent nurses from falling ill and increase compliance with scheduling. In addition, a staffing calculation formula is needed, and top nursing managers are suggested to provide guidance or direction to the head nurses to reduce confusion in managing the work schedule during the pandemic.
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Oyekunle, Adetoun, and Sherif Olanrewaju. "Predictors and Impact of Burnout among Nurses in Nigerian Tertiary Hospitals: A General Review." South Asian Research Journal of Nursing and Healthcare 7, no. 02 (2025): 28–35. https://doi.org/10.36346/sarjnhc.2025.v07i02.001.
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Background: Burnout among Nigerian nurses in tertiary hospitals is a significant issue, leading to adverse effects on both nurse wellbeing and patient outcomes. Purpose: This review aims to explore the key predictors of burnout among nurses in Nigerian tertiary hospitals and examine the coping strategies and interventions that can mitigate its impact. Methods: A literature review was conducted focusing on work-related, socio-demographic, and systemic factors influencing burnout. Findings: Key predictors of burnout among Nigerian nurses include high nurse-patient ratios, long working hours, and inadequate administrative support. Effective coping strategies include implementing peer support programs, scheduling regular breaks, promoting work-life balance through flexible scheduling, and improving staffing levels to mitigate burnout. Implications for Policy and Practice: There is a need for systemic reforms, including improved staffing ratios, better working conditions, and mental health support for nurses. These changes are crucial for reducing burnout and enhancing nurse retention to improve care quality and patient safety.
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Zolkefli, Yusrita, and Mohamad Yusri Haji Zolkefli. "Revisiting Nurse Scheduling Practice." INTERNATIONAL JOURNAL OF CARE SCHOLARS 6, no. 2 (2023): 74–76. http://dx.doi.org/10.31436/ijcs.v6i2.313.
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Rahman, Syawalludin, Yeni Mulyani, and Ichsan Rizany. "Penjadwalan Dinas Perawat berhubungan dengan Kepuasan Pasien di Ruang Rawat Inap RSUD Ulin Banjarmasin." Dunia Keperawatan 6, no. 1 (2018): 41. http://dx.doi.org/10.20527/dk.v6i1.5081.
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ABSTRAKKepuasan pasien selama dirawat di suatu rumah sakit masih dalam kategori rendah. Rendahnya kepuasan pasien tersebut dipengaruhi beberapa faktor yang salah satunya adalah penjadwalan dinas perawat. Penelitian ini bertujuan untuk mengetahui hubungan penjadwalan dinas perawat dengan tingkat kepuasan pasien di ruang rawat inap RSUD Ulin Banjarmasin. Desain penelitian ini menggunakan korelasional dengan pendekatan cross sectional dan teknik pengambilan sampel accidental sampling. Responden penelitian berjumlah 92 orang. Waktu penelitian bulan Desember 2017 dan alat ukur yang digunakan berupa kuesioner. Hasil penelitian menunjukan bahwa gambaran penjadwalan dinas perawat rata-rata sebesar 37,29 mengarah ke rentang tinggi dan gambaran tingkat kepuasan pasien rata-rata sebesar 64,73 mengarah ke rentang rendah. Hasil analisis didapatkan adanya hubungan yang positif antara penjadwalan dinas perawat yang dipersepsikan pasien dengan tingkat kepuasan pasien di ruang rawat inap RSUD Ulin Banjarmasin. (P Value= 0,000). Saran penelitian ini diharapkan untuk kepala ruangan dan perawat agar bekerjasama dalam menentukan penjadwalan dinas yang baik dengan arahan manajer demi terciptanya pelayanan yang optimal untuk kepuasan pasien.Kata-kata kunci: Penjadwalan dinas perawat, Perawat, Tingkat kepuasan pasien, ABSTRACTPatient satisfaction during hospitalization is still in low category. The low patient satisfaction is influenced by several factors, one of which is the scheduling of nurse service. This study was made to know the correlation between scheduling of nurse service and patient satisfication level at RSUD Ulin Banjarmasin hospital. This research used correlation design with cross sectional approach and accidental sampling technique. Research respondents amounted to 92 people. December 2017 research period and measuring instruments used in the form of questionnaires. The result of the analysis shows that there is a positive relationship between scheduling of nurses service that is perceived by patient with patient satisfaction level in ward of RSUD Ulin Banjarmasin. (P Value = 0,000 <0.05). Suggestion of this research is expected to head of room and nurse to cooperate in determining good service scheduling with manager direction for the creation of optimal service for patient satisfaction.Keywords : Level of patient satisfaction, Nurse, Nursing schedulling
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Hasibuan, Mhd Panerangan, and Hendra Cipta. "Optimization of Nursing Scheduling in Emergency by Using Genetic Algorithm." Jurnal Pijar Mipa 19, no. 1 (2024): 99–106. http://dx.doi.org/10.29303/jpm.v19i1.6412.
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Scheduling nurse duty is one of the problems in health organizations that is quite complicated to solve. Starting from the uncertain number of patients, serious patient illnesses, characteristics of organizational groups, requests for nurses to take time off, and the qualifications and specialization of the nurses themselves are why scheduling in the ER is difficult to optimize. The same thing is being experienced by one of the health institutions, RSUD Dr. Pirngadi. Preparing schedules or determining the number of nurses on duty is still done manually, resulting in a lack of optimization in scheduling and the number of nurses who must be on duty, especially in the emergency department. In solving this problem, an appropriate method is needed so that the process of scheduling and optimizing the number of nurses can be formed properly. This research applies the Genetic Algorithm in optimal emergency department (IGD) nurse duty scheduling. Genetic algorithms, also called search algorithms, are based on the mechanisms of natural selection and genetics. Genetic algorithms are one of the appropriate methods for solving complex optimization problems. This method is good enough to optimize shift scheduling for the Emergency Room Nursing Service in a Hospital. This Genetic Algorithm can be a solution to multi-criteria and multi-objective problems modeled using biological and evolutionary processes. So, the concept of this method can be applied in optimizing the Nursing Service schedule. The results of calculations using the Genetic Algorithm show quite significant comparisons, including several nurses losing their positions and being eliminated by mutation because they could not compete with several other strong individuals.
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Ohki, Makoto. "Nurse Scheduling by Cooperative GA with Effective Virus Operator." International Journal of Applied Evolutionary Computation 5, no. 1 (2014): 19–29. http://dx.doi.org/10.4018/ijaec.2014010102.
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This paper proposes effective genetic operators for cooperative genetic algorithm (GA) to solve a nurse scheduling problem. A clinical director of a medical department makes a duty schedule of all nurses of the department every month. Such the scheduling is very complex task. It takes one or two weeks to create the nurse schedule even by a veteran director. In conventional ways using the cooperative GA, a crossover operator is only employed for the optimization, because it does not lose consistency between chromosomes. The authors propose a virus operator for the cooperative GA, which does not lose consistency of the nurse schedule. The cooperative GA with the new operator has brought a surprisingly good result, it has never been brought by the conventional algorithm.
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Abayomi-Alli, Adebayo A., Frances Omoyemen Uzedu, Sanjay Misra, Olusola O. Abayomi-Alli, and Oluwasefunmi T. Arogundade. "Hybrid Model of Genetic Algorithms and Tabu Search Memory for Nurse Scheduling Systems." International Journal of Service Science, Management, Engineering, and Technology 13, no. 1 (2022): 1–20. http://dx.doi.org/10.4018/ijssmet.297494.
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The main challenge of Nurse Scheduling Problem (NSP)is designing a nurse schedule that satisfies nurses preferences at minimal cost of violating the soft constraints. This makes the NSP an NP-hard problem with no perfect solution yet. In this study, two meta-heuristics procedures: Genetic Algorithm (GA) and Tabu Search (TS) memory was applied for the development of an automatic hospital nurse scheduling system (GATS_NSS). The data collected from the nursing services unit of a Federal Medical Centre (FMC) in Nigeria with 151 nursing staffs was preprocessed and adopted for training the GATS_NSS. The system was implemented in Java for Selection, Evaluation and Genetic Operators (Crossover and Mutation) of GA alongside the memory properties of TS. Nurses’ shift and ward allocation was optimized based on defined constraints of the case study hospital and the results obtained showed that GAT_NSS returned an average accuracy of 94%, 99% allocation rate, 0% duplication, 0.5% clash and an average improvement in the computing time of 94% over the manual approach.
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Ramadhani, Intan Ayu, and Yusmet Rizal. "Optimasi Penjadwalan Perawat IGD RSUD Arosuka dengan Metode 0-1 Fuzzy Goal Programming." Journal of Mathematics UNP 8, no. 2 (2023): 81. http://dx.doi.org/10.24036/unpjomath.v8i2.14441.
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Nurse scheduling problem is an important aspect in maintaining the quality of hospital services. The fact that the number of patients is greater than the limited number of nurses and there are rules from the hospital that must be complied with makes the nurse scheduling problem more complex. The purpose of this study was to the shape of the model and the results of optimizing the scheduling of emergency room nurses at Arosuka Hospital using the method 0-1 Fuzzy Goal Programming. Model 0-1 Fuzzy Goal Programming is the result of the application of set theory Fuzzy on Goal Programming that uses a decision variable of 0 or 1. By completing the scheduling model with help LINGO 20.0 software, the results show that with the methodl 0-1 Fuzzy Goal Programming has fulfilled all existing constraints, and can maximize all objectives. In the manual schedule there are sixty one activities which not corresponding with the policy, while with the 0-1 Fuzzy Goal Programming model it has been minimized so that there are only thirty three activities which not corresponding with the policy.
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Amindoust, Atefeh, Milad Asadpour, and Samineh Shirmohammadi. "A Hybrid Genetic Algorithm for Nurse Scheduling Problem considering the Fatigue Factor." Journal of Healthcare Engineering 2021 (March 31, 2021): 1–11. http://dx.doi.org/10.1155/2021/5563651.
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Nowadays and due to the pandemic of COVID-19, nurses are working under the highest pressure benevolently all over the world. This urgent situation can cause more fatigue for nurses who are responsible for taking care of COVID-19 patients 24 hours a day. Therefore, nurse scheduling should be modified with respect to this new situation. The purpose of the present research is to propose a new mathematical model for Nurse Scheduling Problem (NSP) considering the fatigue factor. To solve the proposed model, a hybrid Genetic Algorithm (GA) has been developed to provide a nurse schedule for all three shifts of a day. To validate the proposed approach, a randomly generated problem has been solved. In addition, to show the applicability of the proposed approach in real situations, the model has been solved for a real case study, a department in one of the hospitals in Esfahan, Iran, where COVID-19 patients are hospitalized. Consequently, a nurse schedule for May has been provided applying the proposed model, and the results approve its superiority in comparison with the manual schedule that is currently used in the department. To the best of our knowledge, it is the first study in which the proposed model takes the fatigue of nurses into account and provides a schedule based on it.
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Ko, Young-Woong, Dong-Hoi Kim, Saangyong Uhmn, and Jin Kim. "Nurse Scheduling Problem Using Backtracking." Advanced Science Letters 23, no. 4 (2017): 3792–95. http://dx.doi.org/10.1166/asl.2017.9023.
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Weil, G., K. Heus, P. Francois, and M. Poujade. "Constraint programming for nurse scheduling." IEEE Engineering in Medicine and Biology Magazine 14, no. 4 (1995): 417–22. http://dx.doi.org/10.1109/51.395324.
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Aickelin, Uwe, and Paul White. "Building Better Nurse Scheduling Algorithms." Annals of Operations Research 128, no. 1-4 (2004): 159–77. http://dx.doi.org/10.1023/b:anor.0000019103.31340.a6.
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Kostreva, Michael M., and Karen S. B. Jennings. "Nurse scheduling on a microcomputer." Computers & Operations Research 18, no. 8 (1991): 731–39. http://dx.doi.org/10.1016/0305-0548(91)90011-f.
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Simić, Svetlana, Emilio Corchado, Dragan Simić, Jovanka Đorđević, and Svetislav D. Simić. "A novel fuzzy metaheuristic approach in nurse rerostering problem." Logic Journal of the IGPL 28, no. 4 (2019): 583–95. http://dx.doi.org/10.1093/jigpal/jzz061.
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Abstract In the past 50 years nurse scheduling has received considerable attention in the research community. There are two cases regarding the nurse scheduling problem (NSP): the static and dynamic. Dynamic NSP, is often called nurse rerostering problem (NRRP), which presents reconstruction or modification of the predetermined roster for the current scheduling horizon. The aim of this paper is to present new hybrid strategy for nurse NRRP problem. The proposed methodology is based on efficient cooperation between fuzzy logic, ordered weighted averaging and variable neighbourhood descent search. Complete system is tested, and experimental results are based on real-world dataset obtained from the Oncology Institute of Vojvodina in Serbia.
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Moreno-Velásquez, Luis Fernando, F. Javier Díaz-Serna, and Daniel Morillo-Torre. "Dynamic multicriteria optimization for the nurse scheduling problem." Decision Science Letters 14, no. 2 (2025): 457–72. https://doi.org/10.5267/j.dsl.2024.12.009.
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This document addresses the Nurse Scheduling Problem (NSP) and presents a dynamic multi-criteria optimization model for its solution considering a predefined time horizon. The purpose is to maximize the level of "work well-being" of nurses formulated as the minimization of "aversion" which translates into costs or penalties for certain undesirable work shifts. For this, a series of criteria are defined to estimate the preference structure of nurses according to the hospital center specifications by assigning costs for undesirable shift assignments. The proposed methodology involves developing a heuristic to decompose the global problem into daily subproblems for which a dynamic algorithm is implemented that considers a cost accumulation process for all criteria and all nurses. Daily models are dynamically solved by modifying the coefficients of the well-being function to achieve equity throughout the planning period by updating and accumulating different averages. This methodology has shown satisfactory results for scheduling work shifts for doctors, paramedics, security guards, and drivers in numerous hospital centers in Colombia.
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Nababan, Junerdi, Tulus Tulus, and Zakarias Situmorang. "Analysis of Taklinear Performance and Integer Linear Programming Models in Nurses Scheduling Problems." SinkrOn 4, no. 2 (2020): 123. http://dx.doi.org/10.33395/sinkron.v4i2.10528.
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Almost all hospitals schedule nurses' work shifts manually, which is not effective, mistakes in scheduling nurses in hospitals can make them not work optimally so that they are prone to making mistakes and will endanger every patient in the hospital. In the research will be proposed integer linear programming model and branch and bound method, the purpose of this study is to develop an optimization model of nurse scheduling problems at the hospital. The optimization model will minimize the total deviation of nurses' working days from the standard workdays, the optimization model implemented in hospitals is processed using LINGO software.
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Huang, Li, Chunming Ye, Jie Gao, Po-Chou Shih, Franley Mngumi, and Xun Mei. "Personnel Scheduling Problem under Hierarchical Management Based on Intelligent Algorithm." Complexity 2021 (January 12, 2021): 1–14. http://dx.doi.org/10.1155/2021/6637207.
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This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness preferences. Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer (MOGWO) and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance (GD) and spacing (SP) of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness.
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Rodwell, John, Thomas Hendry, and Dianne Johnson. "Analyzing and Validating a Structure for Measuring the Nurse Practice Environment." International Journal of Environmental Research and Public Health 20, no. 7 (2023): 5266. http://dx.doi.org/10.3390/ijerph20075266.
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Nurse shortages pose a challenge in many countries and retaining existing nursing staff is crucial to addressing these shortages. To inform possible interventions aimed at retaining nurses, managers need a comprehensive understanding of the nature of the nurse practice environment. The scales from two of the main instruments used to assess nurses’ practice environments are tested. A survey of an online panel obtained responses from 459 Australian nurses. Analyses determined a combination of items with good construct validity and improved predictive utility for outcomes of interest for individual nurses. By essentially combining the best items from each instrument, a more comprehensive representation of the nurse work environment is obtained with improved predictive utility. The resulting combined set of scales is recommended for analyses of the nurse working environment and uses a combined set of scales from each of the two source instruments, namely: nurse participation in hospital affairs, recognition, nursing process, peer work standards, nursing competence, orientation, managers, resources, nurse–physician collaboration, and positive scheduling climate. Future research can then build on that strong set of items with a validated structure and predictive utility to inform management and interventions.
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Topaloglu, Seyda, and Hasan Selim. "Nurse scheduling using fuzzy modeling approach." Fuzzy Sets and Systems 161, no. 11 (2010): 1543–63. http://dx.doi.org/10.1016/j.fss.2009.10.003.
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Ozkarahan, Irem. "A flexible nurse scheduling support system." Computer Methods and Programs in Biomedicine 30, no. 2-3 (1989): 145–53. http://dx.doi.org/10.1016/0169-2607(89)90066-7.
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Chandra, Alfian Bima, Ardana Putri Farahdiansari, and Rizky Stighfarrinata. "Optimasi Penjadwalan Perawat Dan Bidan Dengan Pendekatan Metode Algoritma Genetika Pada Puskesmas Kecamatan Purwosari." Jurnal Teknik Industri Terintegrasi 7, no. 1 (2024): 470–89. http://dx.doi.org/10.31004/jutin.v7i1.25768.
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Purwosari Community Health Center provides structured healthcare services with two types of services, inpatient and outpatient care. Although inpatient services run smoothly, nurse shift scheduling still relies on Microsoft Excel and often encounters schedule conflicts. To address this issue, the use of genetic algorithm method is proposed. Genetic algorithm offers multi-criteria and multi-objective solutions for scheduling, integrating concepts from genetics and scientific biological processes. Thus, the "schedule collision" problem can be effectively addressed, enhancing the efficiency of nurse shift scheduling in Purwosari Community Health Center's inpatient care.
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Arniawan, Arniawan, Nur Setiawati Dewi, and Septo Pawelas Arso. "Jenis Intervensi dalam Meningkatkan Kepuasan Kerja Perawat." Journal of Telenursing (JOTING) 5, no. 2 (2023): 1614–27. http://dx.doi.org/10.31539/joting.v5i2.6216.
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This study aims to determine the types of interventions that can increase the job satisfaction of nurses in hospitals through an article review approach. The research method used is scoping review through databases namely Pubmed, ScienceDirect, Scopus, SpringerLink, and Garuda Portal. The results of the study show that 15 interventions articles that can increase nurse job satisfaction include organizational culture, organizational commitment, implementation of nurse welfare programs, work professionalism, clinical supervision, implementation of sharia behavior in nursing services, scheduling management, leadership, democratic leadership, transformational leadership, style transformational leadership, organizational climate, application of the team method, application of the professional nursing practice model (MPKP), leadership style, and structural empowerment. In conclusion, this type of intervention is proven to increase the nurses job satisfaction.
 
 Keywords: Intervention, Job Satisfaction, Nurse
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Cetin Yagmur, Ece, and Ahmet Sarucan. "Nurse Scheduling with Opposition-Based Parallel Harmony Search Algorithm." Journal of Intelligent Systems 28, no. 4 (2019): 633–47. http://dx.doi.org/10.1515/jisys-2017-0150.
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Abstract One of the advances made in the management of human resources for the effective implementation of service delivery is the creation of personnel schedules. In this context, especially in terms of the majority of health-care systems, creating nurse schedules comes to the fore. Nurse scheduling problem (NSP) is a complex optimization problem that allows for the preparation of an appropriate schedule for nurses and, in doing so, considers the system constraints such as legal regulations, nurses’ preferences, and hospital policies and requirements. There are many studies in the literature that use exact solution algorithms, heuristics, and meta-heuristics approaches. Especially in large-scale problems, for which deterministic methods may require too much time and cost to reach a solution, heuristics and meta-heuristic approaches come to the fore instead of exact methods. In the first phase of the study, harmony search algorithm (HSA), which has shown progress recently and can be adapted to many problems is applied for a dataset in the literature, and the algorithm’s performance is evaluated by comparing the results with other heuristics which is applied to the same dataset. As a result of the evaluation, the performance of the classical HSA is inadequate when compared to other heuristics. In the second phase of our study, by considering new approaches proposed by the literature for HSA, the effects on the algorithm’s performance of these approaches are investigated and we tried to improve the performance of the algorithm. With the results, it has been determined that the improved algorithm, which is called opposition-based parallel HSA, can be used effectively for NSPs.
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J. Lim, Gino, Arezou Mobasher, and Murray J. Côté. "Multi-objective Nurse Scheduling Models with Patient Workload and Nurse Preferences." Management 2, no. 5 (2012): 149–60. http://dx.doi.org/10.5923/j.mm.20120205.03.
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Wright, P. Daniel, and Stephen Mahar. "Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction." Omega 41, no. 6 (2013): 1042–52. http://dx.doi.org/10.1016/j.omega.2012.08.004.
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Rajeswari, M., J. Amudhavel, Sujatha Pothula, and P. Dhavachelvan. "Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem." Computational Intelligence and Neuroscience 2017 (2017): 1–26. http://dx.doi.org/10.1155/2017/6563498.
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The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.
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Penedo, Rafaela Mossarelli, and Wilza Carla Spiri. "Meaning of the Systematization of Nursing Care for nurse managers." Acta Paulista de Enfermagem 27, no. 1 (2014): 86–92. http://dx.doi.org/10.1590/1982-0194201400016.
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OBJECTIVE: To understand the meaning that the nurse managers attributed to the nursing process, developed in their daily work.METHODS: The phenomenological method was used, referencing the structure of the situated phenomenon. The subjects were thirteen nurses, managers of a university hospital. The analysis included transcription and readings of depositions aimed at the essence, by means of thematization, interpretation and synthesis of the phenomenon.RESULTS: The thematic categories were: human resources in achieving the systematization of nursing care; their relevance to the work of the nurse, difficulties in its implementation; qualification for its realization.CONCLUSION: The meaning that nurse managers attribute to the systematization of nursing care are related to the legal aspects of professional practice, teamwork, and to the adequate scheduling of human resources.
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Zunaedi, Rosly, and Soenarnatalina M. Ahsan. "Application Model of Nurse Electronic Rostering Software (NERS) In Hospital Ward." INDONESIAN NURSING JOURNAL OF EDUCATION AND CLINIC (INJEC) 6, no. 2 (2022): 192. http://dx.doi.org/10.24990/injec.v6i2.370.
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Introduction: Good scheduling arrangements are needed so that there is no physical, emotional and psychological fatigue to nurses, which will have a negative impact on the performance of nurses in providing services to patients. This study aims to develop an application model for the electronic rostering of nurses in the ward. Methods: The design in this study was Research and Development (R&D). The population of this study was all nurses who worked in the inpatient room. The sampling technique used was simple random sampling. Data for the assessment of scheduling characteristics were collected using questionnaire based on formulation of the problem and Focus Group Discussion (FGD). Data analysis is in descriptive form. Results: Most of the respondents considered that ward scheduling characteristics were sufficient (80.2%). The development of electronic rostering model emphasizes on optimizing the needs and distribution of nurses, equalizing shift and off, and reducing time for preparing schedules. The development of an electronic rostering model was also adjusted to the policies of the hospital regarding the nurses’ work scheduling method so that it can be implemented appropriately in the ward. Conclusion: The development of an electronic work scheduling model for nurses in the inpatient room includes: division based on the level of patient dependence, scheduling flexibility by proposing early holidays and leave, and reducing the duration of nurses' rostering preparation.