On a timetabling problem in the health care system

Open Access

Issue		RAIRO-Oper. Res. Volume 56, Number 6, November-December 2022


Page(s)		4347 - 4362
DOI		https://doi.org/10.1051/ro/2022182
Published online		23 December 2022

H.H. Ali, H. Lamsali and S.N. Othman, Hospital scheduling analysis: a contemporary review and proposed schematic understanding. J. Adv. Res. Dyn. Control Syst. 10 (2018) 164–173. [Google Scholar]
P. Cappanera, F. Visintin and R. Rossi, The emergency department physician rostering problem: obtaining equitable solutions via network optimization. Flexible Serv. Manuf. J. 1 (2021) 1–44. [Google Scholar]
R. M’Hallah and A. Al-Roomi, The planning and scheduling of operating rooms: a simulation approach. Comput. Ind. Eng. 78 (2014) 235–248. [CrossRef] [Google Scholar]
K. Van den Heede, J. Cornelis, N. Bouckaert, L. Bruyneel, C. Van de Voorde and W. Sermeus, Safe nurse staffing policies for hospitals in England, Ireland, California, Victoria and Queensland: a discussion paper. Health Policy 124 (2020) 1064–1073. [CrossRef] [Google Scholar]
M. Hami, R. Tavakkoli-Moghaddam, F. Golpaygani and B. Vahedi-Nouri, A multi-objective model for a nurse scheduling problem by emphasizing human factors. Proc. Inst. Mech. Eng. Part H: J. Eng. Med. 234 (2020) 179–199. [CrossRef] [PubMed] [Google Scholar]
A. Abuhamdah, W. Boulila, G. Jaradat, A. Quteishat, M. Alsmadi and I. Almarashdeh, A novel population-based local search for nurse rostering problem. Int. J. Elect. Comput. Eng. 11 (2021) 471–480. [Google Scholar]
Y.-C. Huang, Y.-H. Hsieh and F.Y. Hsia, A study on nurse day-off scheduling under the consideration of binary preference. J. Ind. Prod. Eng. 33 (2016) 363–372. [Google Scholar]
N. Khalili, P. Shahnazari Shahrezaei and A.G. Abri, A multi-objective optimization approach for a nurse scheduling problem considering the fatigue factor (case study: Labbafinejad hospital). J. Appl. Res. Ind. Eng. 7 (2020) 396–423. [Google Scholar]
E.I. Bluth, T. Robin Goodman and C.E. Bender, The late-career radiologist: options and opportunities. RadioGraphics 38 (2018) 1617–1625. [Google Scholar]
M.J. Cote and M.A. Smith, Forecasting the demand for radiology services. Health Syst. 7 (2018) 79–88. [CrossRef] [PubMed] [Google Scholar]
P. Mukherjee, T.C. Lim, A. Chawla, H. Chou and W.C.G. Peh, Adaptability and responsiveness: keys to operational measures in a regional hospital radiology department during the current covid-19 pandemic. Br. J. Radiol. 2 (2020) 1–17. [Google Scholar]
A.T. Ernst, H. Jiang, M. Krishnamoorthy and D. Sier, Staff scheduling and rostering: a review of applications, methods and models. Eur. J. Oper. Res. 153 (2004) 3–27. [Google Scholar]
E.K. Burke, P. De Causmaecker, G.V. Berghe and H. Van Landeghem, The state of the art of nurse rostering. J. Scheduling 7 (2004) 441–499. [CrossRef] [MathSciNet] [Google Scholar]
T.A. Lang, M. Hodge, V. Olson, P.S. Romano and R.L. Kravitz, Nurse–patient ratios: a systematic review on the effects of nurse staffing on patient, nurse employee, and hospital outcomes. JONA: J. Nursing Admin. 34 (2004) 326–337. [CrossRef] [PubMed] [Google Scholar]
P. Griffiths, C. Saville, J. Ball, J. Jones, N. Pattison and T. Monks, Nursing workload, nurse staffing methodologies and tools: a systematic scoping review and discussion. Int. J. Nursing Stud. 103 (2020) 1–11. [Google Scholar]
E.H. Özder, E. Özcan and T. Eren, A systematic literature review for personnel scheduling problems. Int. J. Inf. Technol. Decis. Making 19 (2020) 1695–1735. [CrossRef] [Google Scholar]
Z.A. Abdalkareem, A. Amir, M.A. Al-Betar, P. Ekhan and A.I. Hammouri, Healthcare scheduling in optimization context: a review. Health Technol. 11 (2021) 445–469. [CrossRef] [PubMed] [Google Scholar]
B. Afshar-Nadjafi, Multi-skilling in scheduling problems: a review on models, methods and applications. Comput. Ind. Eng. 151 (2021) 1–14. [Google Scholar]
Ş. Gür and T. Eren, Scheduling and planning in service systems with goal programming: literature review. Mathematics 6 (2018) 2–65. [Google Scholar]
N.A. Abd-El-Aziz and E.A. Wahab, The relationship between staff nurses’ satisfaction with their schedule and patients’ satisfaction with quality of care. Egypt. Nursing J. 16 (2019) 147–154. [Google Scholar]
N. Stec, D. Arje, A.R. Moody, E.A. Krupinski and P.N. Tyrrell, A systematic review of fatigue in radiology: is it a problem? Am. J. Roentgenol. 210 (2018) 799–806. [CrossRef] [PubMed] [Google Scholar]
L.H. Garland, The radiological service – how many radiologists are advisable? Radiology 80 (1963) 686–687. [CrossRef] [PubMed] [Google Scholar]
J. Herron and J.H. Reynolds, Trends in the on-call workload of radiologists. Clin. Radiol. 61 (2006) 91–96. [CrossRef] [Google Scholar]
P. Charnock, C. Baker, S. Baily, J. Fazakerley, R. Jones, B.M. Moores and R. Wilde, Radiology workload analysis–role and relevance in radiation protection in diagnostic radiology, in World Congress on Medical Physics and Biomedical Engineering, September 7–12, 2009, Munich, Germany. Springer (2009) 128–131. [Google Scholar]
N.N. Thompson, P. Tanabe, E.B. Holladay, A. Bennett, A. Bugbee and C.A. Steward, The current state of medical laboratory staffing with certified versus noncertified personnel. Lab. Med. 40 (2009) 197–202. [CrossRef] [Google Scholar]
E. Picano, E. Vano, L. Domenici, M. Bottai and I. Thierry-Chef, Cancer and non-cancer brain and eye effects of chronic low-dose ionizing radiation exposure. BMC Cancer 12 (2012) 1–13. [CrossRef] [PubMed] [Google Scholar]
A.J. Quigley, S. Stafrace and D. McAteer, Trends in the volume of general radiology on-call over a 5 year period at a scottish teaching hospital from 2007 to 2011, in European Congress of Radiology-ECR 2012 (2007). [Google Scholar]
D. Dhanoa, T.S. Dhesi, K.R. Burton, S. Nicolaou and T. Liang, The evolving role of the radiologist: the vancouver workload utilization evaluation study. J. Am. College Radiol. 10 (2013) 764–769. [CrossRef] [Google Scholar]
S.L.S. MacDonald, I.A. Cowan, R.A. Floyd and R. Graham, Measuring and managing radiologist workload: a method for quantifying radiologist activities and calculating the full-time equivalents required to operate a service. J. Med. Imaging Radiat. Oncol. 57 (2013) 551–557. [CrossRef] [Google Scholar]
R.J. McDonald, K.M. Schwartz, L.J. Eckel, F.E. Diehn, C.H. Hunt, B.J. Bartholmai, B.J. Erickson and D.F. Kallmes, The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Acad. Radiol. 22 (2015) 1191–1198. [CrossRef] [Google Scholar]
S. Rohatgi, T.N. Hanna, C.W. Sliker, R.M. Abbott and R. Nicola, After-hours radiology: challenges and strategies for the radiologist. Am. J. Roentgenol. 205 (2015) 956–961. [CrossRef] [PubMed] [Google Scholar]
L.J. Smith, R. Kearvell, A.J. Arnold, K. Choma, A. Cooper, M.R. Young, D.L. Matthews, B. Hilder, D. Howson, K. Fox and K. Churcher, Radiation therapy staffing model 2014. J. Med. Radiat. Sci. 63 (2016) 209–216. [CrossRef] [PubMed] [Google Scholar]
R.L. Arenson, Factors affecting interpretative accuracy: how can we reduce errors? Radiology 287 (2018) 213–214. [CrossRef] [PubMed] [Google Scholar]
M.D.C. Fishman, T.S. Mehta, B. Siewert, C.E. Bender and J.B. Kruskal, The road to wellness: engagement strategies to help radiologists achieve joy at work. Radiographics 38 (2018) 1651–1664. [Google Scholar]
T.N. Hanna, C. Lamoureux, E.A. Krupinski, S. Weber and J.-O. Johnson, Effect of shift, schedule, and volume on interpretive accuracy: a retrospective analysis of 2.9 million radiologic examinations. Radiology 287 (2018) 205–212. [CrossRef] [PubMed] [Google Scholar]
C.E. Saville, P. Griffiths, J.E. Ball and T. Monks, How many nurses do we need? A review and discussion of operational research techniques applied to nurse staffing. Int. J. Nursing Stud. 97 (2019) 7–13. [CrossRef] [Google Scholar]
S. Taylor-Phillips and C. Stinton, Fatigue in radiology: a fertile area for future research. Br. J. Radiol. 92 (2019) 20190043. [CrossRef] [PubMed] [Google Scholar]
R.S. Ayyala, G.L. Baird, R.W. Sze, B.P. Brown and G.A. Taylor, The growing issue of burnout in radiology – a survey-based evaluation of driving factors and potential impacts in pediatric radiologists. Pediatric Radiol. 50 (2020) 1071–1077. [CrossRef] [PubMed] [Google Scholar]
R.J.M. Bruls and R.M. Kwee, Workload for radiologists during on-call hours: dramatic increase in the past 15 years. Insights Imaging 11 (2020) 1–7. [CrossRef] [PubMed] [Google Scholar]
A. Artanto, L. Chairani, M.N. Belia and A. Ghiffari, The relationship between shift work and occupational fatigue on nurses working on the pediatrics and internal wards of Muhammadiyah Palembang hospital. Br. Int. Exact Sci. J. 3 (2021) 144–150. [Google Scholar]
L. Bam, C. Cloete and I.H. de Kock, Determining diagnostic radiographer staffing requirements: a workload-based approach. Radiography 28 (2022) 276–282. [Google Scholar]
J.D. Boice Jr, S.S. Cohen, M.T. Mumma, S.C. Howard, R.C. Yoder and L.T. Dauer, Mortality among medical radiation workers in the United States, 1965–2016. Int. J. Radiat. Biol. (2022) 1–63. DOI: 10.1080/09553002.2021.1967508. [Google Scholar]
S.L. Brzozowski, H. Cho, É.N.A. Knudsen and L.M. Steege, Predicting nurse fatigue from measures of work demands. Appl. Ergon. 92 (2021) 103337. [CrossRef] [Google Scholar]
H.M. Elweshahi, J.F. Mekky, H.E.A. Elwafa and M.H. Ashry, Sleep and emotional disturbances among the health workers during the covid-19 pandemic in Egypt. Egypt. J. Psychiatry 42 (2021) 1–29. [Google Scholar]
S. McRae, Long-term forecasting of regional demand for hospital services. Oper. Res. Health Care 28 (2021) 100289. [CrossRef] [Google Scholar]
A. Oliveira, V. Gowda and S.G. Jordan, It takes a village: a multimodal approach to addressing radiologist burnout. Curr. Prob. Diagn. Radiol. 51 (2021) 289–292. [Google Scholar]
J.R. Parikh and C.E. Bender, How radiology leaders can address burnout. J. Am. College Radiol. 18 (2021) 679–684. [CrossRef] [Google Scholar]
A.R. Sharkey, P. Gambhir, S. Saraskani, R. Walker, A. Hajilou, P. Bassett, N. Sandhu, P. Croasdale, I. Honey, A. Diamantopoulos and V. Goh, Occupational radiation exposure in doctors: an analysis of exposure rates over 25 years. Br. J. Radiol. 94 (2021) 20210602. [CrossRef] [PubMed] [Google Scholar]
D.E. Twigg, L. Whitehead, G. Doleman and S. El-Zaemey, The impact of nurse staffing methodologies on nurse and patient outcomes: a systematic review. J. Adv. Nursing 77 (2021) 4599–4611. [CrossRef] [PubMed] [Google Scholar]
R. Wynne, P.M. Davidson, C. Duffield, D. Jackson and C. Ferguson, Workforce management and patient outcomes in the intensive care unit during the covid-19 pandemic and beyond: a discursive paper. J. Clinical Nursing 1 (2021) 1–10. [Google Scholar]
R. M’Hallah and A. Alkhabbaz, Scheduling of nurses: a case study of a Kuwaiti health care unit. Oper. Res. Health Care 2 (2013) 1–19. [Google Scholar]
A.A. El Adoly, M. Gheith and M. Nashat Fors, A new formulation and solution for the nurse scheduling problem: a case study in Egypt. Alexandria Eng. J. 57 (2018) 2289–2298. [CrossRef] [Google Scholar]
T.C. Wong, M. Xu and K.S. Chin, A two-stage heuristic approach for nurse scheduling problem: a case study in an emergency department. Comput. Oper. Res. 51 (2014) 99–110. [Google Scholar]
E.K. Burke, J. Li and R. Qu, A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems. Eur. J. Oper. Res. 203 (2010) 484–493. [Google Scholar]
X. Zhong, J. Zhang and X. Zhang, A two-stage heuristic algorithm for the nurse scheduling problem with fairness objective on weekend workload under different shift designs. IISE Trans. Healthcare Syst. Eng. 7 (2017) 224–235. [CrossRef] [Google Scholar]
I.X. Tassopoulos, I.P. Solos and G.N. Beligiannis, A two-phase adaptive variable neighborhood approach for nurse rostering. Comput. Oper. Res. 60 (2015) 150–169. [Google Scholar]
L. Luo, X. Liu, X. Cui, Y. Cheng, X. Yu, Y. Li, L. Jiang and M. Tan, Applying queuing theory and mixed integer programming to blood center nursing schedules of a large hospital in China. Comput. Math. Methods Med. 2020 (2020) 9373942. [Google Scholar]
P. Cappanera, F. Visintin and R. Rossi, A two-phase approach to the emergency department physician rostering problem, in Health Care Systems Engineering: HCSE, Montréal, Canada, May 30–June 1, 2019. Vol. 316. Springer, Cham (2020) 79. [CrossRef] [Google Scholar]
P. Cappanera, F. Visintin and R. Rossi, The emergency department physician rostering problem: obtaining equitable solutions via network optimization. Flexible Serv. Manuf. J. (2021) 1–44. DOI: 10.1007/s10696-021-09426-7. [Google Scholar]
S. Topaloglu and H. Selim, Nurse scheduling using fuzzy modeling approach. Fuzzy Sets Syst. 161 (2010) 1543–1563. [CrossRef] [Google Scholar]
C.-C. Lin, J.-R. Kang, D.-J. Chiang and C.-L. Chen, Nurse scheduling with joint normalized shift and day-off preference satisfaction using a genetic algorithm with immigrant scheme. Int. J. Distrib. Sensor Networks 11 (2015) 1–19. [CrossRef] [Google Scholar]
T.-H. Wu, J.-Y. Yeh and Y.-M. Lee, A particle swarm optimization approach with refinement procedure for nurse rostering problem. Comput. Oper. Res. 54 (2015) 52–63. [CrossRef] [MathSciNet] [Google Scholar]
Z. Liu, Z. Liu, Z. Zhu, Y. Shen and J. Dong, Simulated annealing for a multi-level nurse rostering problem in hemodialysis service. Appl. Soft Comput. 64 (2018) 148–160. [CrossRef] [Google Scholar]
T. Miyamoto and K. Hidaka, Modified model of radiographer scheduling problem for sequential optimization, in 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE (2018) 273–277. [CrossRef] [Google Scholar]
W.H. El-Ashmawi and A.F. Ali, An enhanced jaya algorithm for solving nurse scheduling problem. Int. J. Grid Util. Comput. 10 (2019) 439–447. [CrossRef] [Google Scholar]
S. Haddadi, Three-phase method for nurse rostering. Int. J. Manage. Sci. Eng. Manage. 14 (2019) 193–205. [Google Scholar]
Q. Liu, B. Niu, J. Wang, H. Wang and L. Li, Nurse scheduling problem based on hydrologic cycle optimization, in 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE (2019) 1398–1405. [CrossRef] [Google Scholar]
P.-S. Chen and Z.-Y. Zeng, Developing two heuristic algorithms with metaheuristic algorithms to improve solutions of optimization problems with soft and hard constraints: an application to nurse rostering problems. Appl. Soft Comput. 93 (2020) 1–36. [Google Scholar]
P.-S. Chen, W.-T. Huang, T.-H. Chiang and G.Y. Chen, Applying heuristic algorithms to solve inter-hospital hierarchical allocation and scheduling problems of medical staff. Int. J. Comput. Intell. Syst. 13 (2020) 318–331. [CrossRef] [MathSciNet] [Google Scholar]
F. Guessoum, S. Haddadi and E. Gattal, Simple, yet fast and effective two-phase method for nurse rostering. Am. J. Math. Manage. Sci. 39 (2020) 1–19. [Google Scholar]
S. Haddadi, Plant propagation algorithm for nurse rostering. Int. J. Innovative Comput. App. 11 (2020) 204–215. [CrossRef] [Google Scholar]
M. Hamid, R. Tavakkoli-Moghaddam, F. Golpaygani and B. Vahedi-Nouri, A multi-objective model for a nurse scheduling problem by emphasizing human factors. Proc. Inst. Mech. Eng. Part H: J. Eng. Med. 234 (2020) 179–199. [CrossRef] [PubMed] [Google Scholar]
M.R. Hassani and J. Behnamian, A scenario-based robust optimization with a pessimistic approach for nurse rostering problem. J. Comb. Optim. 41 (2021) 143–169. [CrossRef] [MathSciNet] [Google Scholar]
R. Ramli, S.N. Ima Ahmad, S. Abdul-Rahman and A. Wibowo, A tabu search approach with embedded nurse preferences for solving nurse rostering problem. Int. J. Simul. Multi. Design Optim. 11 (2020) 1–10. [CrossRef] [EDP Sciences] [Google Scholar]
P. Rerkjirattikal, V.-N. Huynh, S. Olapiriyakul and T. Supnithi, A goal programming approach to nurse scheduling with individual preference satisfaction. Math. Prob. Eng. 2020 (2020) 1–27. [Google Scholar]
P. Strandmark, Y. Qu and T. Curtois, First-order linear programming in a column generation-based heuristic approach to the nurse rostering problem. Comput. Oper. Res. 120 (2020) 104945. [CrossRef] [MathSciNet] [Google Scholar]
L. Wolbeck, N. Kliewer and I. Marques, Fair shift change penalization scheme for nurse rescheduling problems. Eur. J. Oper. Res. 284 (2020) 1121–1135. [CrossRef] [Google Scholar]
S. Achmad, A. Wibowo and D. Diana, Ant colony optimization with semi random initialization for nurse rostering problem. Int. J. Simul. Multi. Design Optim. 12 (2021) 31. [CrossRef] [EDP Sciences] [Google Scholar]
M.J. Pahlevanzadeh, F. Jolai, F. Goodarzian and P. Ghasemi, A new two-stage nurse scheduling approach based on occupational justice considering assurance attendance in works shifts by using z-number method: a real case study. RAIRO: Oper. Res. 55 (2021) 3317–3338. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
A. Amindoust, M. Asadpour and S. Shirmohammadi, A hybrid genetic algorithm for nurse scheduling problem considering the fatigue factor. J. Health Care Eng. 2021 (2021) 2040–2295. [Google Scholar]
S. Lan, W. Fan, S. Yang, N. Mladenović and P.M. Pardalos, Solving a multiple-qualifications physician scheduling problem with multiple types of tasks by dynamic programming and variable neighborhood search. J. Oper. Res. Soc. 2021 (2021) 1–16. [Google Scholar]
P.-S. Chen, C.-C. Tsai, J.-F. Dang and W.-T. Huang, Developing three-phase modified bat algorithms to solve medical staff scheduling problems while considering minimal violations of preferences and mean workload. Technol. Health Care 31 (2021) 1–22. [Google Scholar]
L. Huang, C. Ye, J. Gao, P.-C. Shih, F. Mngumi and X. Mei, Personnel scheduling problem under hierarchical management based on intelligent algorithm. Complexity 2021 (2021) 1–10. [Google Scholar]
M.P. Ariyani, C.N. Rosyidi and A. Aisyati, An optimization model of nurse scheduling using goal programming method: a case study, in IOP Conference Series: Materials Science and Engineering. Vol. 1096. IOP Publishing (2021) 1–22. [Google Scholar]
E. Özcan, T. Danşan, R. Yumuşak, Ş. Gür and T. Eren, Goal programming approach for the radiology technician scheduling problem. Sigma J. Eng. Nat. Sci. 37 (2019) 1411–1420. [Google Scholar]
N. Al-Hinai, N. Al-Yazidy, A. Al-Hooti and E. Al-Shereiqi, A goal programming model for nurse scheduling at emergency department, in Proceedings of the International Conference on Industrial Engineering and Operations Management (2018) 99–103. [Google Scholar]
L. Hakim and T. Bakhtiar, The nurse scheduling problem: a goal programming and nonlinear optimization approaches, in IOP Conference Series: Materials Science and Engineering. Vol. 166. IOP Publishing (2017) 1–24. [Google Scholar]
A.F. Simon, J.H. Holmes and E.S. Schwartz, Decreasing radiologist burnout through informatics-based solutions. Clin. Imaging 59 (2020) 167–171. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.