Advertisement

Journal of Combinatorial Optimization

, Volume 37, Issue 1, pp 337–362 | Cite as

Patient scheduling in hemodialysis service

  • Zhenyuan LiuEmail author
  • Jiongbing Lu
  • Zaisheng Liu
  • Guangrui Liao
  • Hao Howard Zhang
  • Junwu Dong
Article
First Online:
  • 138 Downloads

Abstract

The patient scheduling presents a number of operations management challenges in hemodialysis service center. The homogeneity of the break time between treatments, satisfying the patients preferences on time, space and equipment and the multi-function dialysis devices make for an interesting and complex scheduling problem that could benefit from computerized decision support. In this paper, patient scheduling problem in hemodialysis service is formulated as a synthetic-objective optimization model combined with several criteria on minimizing the gross utilization cost of devices, the number of night treatment, satisfying the patients preferences and the equilibrium of the devices. A basic heuristics and a rollout algorithm based on the heuristics are developed for solving the problem where three levels of treatment schedule sets are constructed one by one. The performances of the rollout algorithm and the basic heuristics are compared on the real cases. Computational results show that significant improvement of patients degree of satisfaction can be achieved with the rollout algorithm while simultaneously considering to reduce the number of night shifts.

Keywords

Patient scheduling Hemodialysis service Synthetic-objective optimization Heuristics Rollout algorithm 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

This work is supported partially by the Fundamental Research Funds for the Central Universities, HUST: 2017KFYXJJ178 and the Yellow Crane Talents Foundation of Wuhan, China.

References

  1. Ahmadi-Javid A, Jalali Z, Klassen KJ (2017) Outpatient appointment systems in healthcare: a review of optimization studies. Eur J Oper Res 258(1):3–34MathSciNetzbMATHGoogle Scholar
  2. Azadeh A, Baghersad M, Farahani MH, Zarrin M (2015) Semi-online patient scheduling in pathology laboratories. Artif Intell Med 64(3):217–226Google Scholar
  3. Bertazzi L (2012) Minimum and worst-case performance ratios of rollout algorithms. J Optim Theory Appl 152(2):378–393MathSciNetzbMATHGoogle Scholar
  4. Bertsekas DP, Tsitsiklis JN, Wu C (1997) Rollout algorithms for combinatorial optimization. J Heuristics 3(3):245–262zbMATHGoogle Scholar
  5. Bruecker PD, Bergh JVD, Belin J, Demeulemeester E (2015) Workforce planning incorporating skills: state of the art. Eur J Oper Res 243(1):1–16MathSciNetzbMATHGoogle Scholar
  6. Cayirli T, Veral E (2003) Outpatient scheduling in health care: a review of literature. Prod Oper Manag 12(4):519–549Google Scholar
  7. Condotta A, Shakhlevich NV (2014) Scheduling patient appointments via multilevel template: a case study in chemotherapy. Oper Res Health Care 3(3):129–144Google Scholar
  8. Guerriero F (2008) Hybrid rollout approaches for the job shop scheduling problem. J Optim Theory Appl 139(2):419–438MathSciNetzbMATHGoogle Scholar
  9. Guerriero F, Mancini M (2005) Parallelization strategies for rollout algorithms. Comput Optim Appl 31(2):221–244MathSciNetzbMATHGoogle Scholar
  10. Guerriero F, Mancini M, Musmanno R (2002) New rollout algorithms for combinatorial optimization problems. Optim Methods Softw 17(4):627–654MathSciNetzbMATHGoogle Scholar
  11. Guerriero F, Pisacane O, Rende F (2015) Comparing heuristics for the product allocation problem in multi-level warehouses under compatibility constraints. Appl Math Model 39(23–24):7375–7389Google Scholar
  12. Gupta D, Denton B (2008) Appointment scheduling in health care: challenges and opportunities. Iie Trans 40(9):800–819Google Scholar
  13. Hadidi A (2015) A survey of approaches for university course timetabling problem. Comput Ind Eng 86(C):43–59Google Scholar
  14. Holland J (1994) Scheduling patients in hemodialysis service centers. Prod Inventory Manag J 35(2):76–80Google Scholar
  15. Hulshof PJH, Kortbeek N, Boucherie RJ, Hans EW, Bakker PJM (2012) Taxonomic classification of planning decisions in health care: a structured review of the state of the art in or/ms. Health Systms 1(2):129–175Google Scholar
  16. Jha V, Garcia-Garcia G, Iseki K, Li Z, Naicker S, Plattner B, Saran R, Wang AY, Yang CW (2013) Chronic kidney disease: global dimension and perspectives. Lancet 382(9888):260Google Scholar
  17. Mccollum B, Schaerf A, Paechter B, Mcmullan P, Lewis R, Parkes AJ, Gaspero LD, Qu R, Burke EK (2010) Setting the research agenda in automated timetabling: the second international timetabling competition. Informs J Comput 22(1):120–130zbMATHGoogle Scholar
  18. Meskens N, Duvivier D, Hanset A (2013) Multi-objective operating room scheduling considering desiderata of the surgical team. Decis Support Syst 55(2):650–659Google Scholar
  19. Ogulata S, Mokoyuncu CE, Koyuncu M (2009) A simulation approach for scheduling patients in the department of radiation oncology. J Med Syst 33(3):233–239Google Scholar
  20. Peña MT, Proaño RA, Kuhl ME (2013) Optimization of inpatient hemodialysis scheduling considering efficiency and treatment delays. Dissertations and Theses—Gradworks (43)Google Scholar
  21. Petrovic S, Leung W, Song X, Sundar S (2006) Algorithms for radiotherapy treatment booking. In: Proceedings of the 25th workshop of the UK planning and scheduling special interest group (PlanSIG2006), pp 105–112Google Scholar
  22. Pillay N (2016) A review of hyper-heuristics for educational timetabling. Ann Oper Res 239(1):3–38MathSciNetzbMATHGoogle Scholar
  23. Pinedo ML (2012) Scheduling: theory, algorithms, and systems. Springer, BerlinzbMATHGoogle Scholar
  24. Power A, Duncan N, Goodlad C (2009) Management of the dialysis patient for the hospital physician. Postgrad Med J 85(1005):376–381Google Scholar
  25. Qu R, Burke EK, Mccollum B, Merlot LTG, Lee SY (2009) A survey of search methodologies and automated system development for examination timetabling. J Sched 12(1):55–89MathSciNetzbMATHGoogle Scholar
  26. Riff MC, Cares JP, Neveu B (2016) Rason: A new approach to the scheduling radiotherapy problem that considers the current waiting times. Exp Syst Appl 64:287–295Google Scholar
  27. Riise A, Mannino C, Lamorgese L (2016) Recursive logic-based benders decomposition for multi-mode outpatient scheduling. Eur J Oper Res 255(3):719–728MathSciNetzbMATHGoogle Scholar
  28. Saremi A, Jula P, Elmekkawy T, Wang GG (2015) Bi-criteria appointment scheduling of patients with heterogeneous service sequences. Exp Syst Appl Int J 42(8):4029–4041Google Scholar
  29. Tomoyuki T, Takeshi N, Hideki K, Kosaku N, Tadao A, Makoto H, Tadayuki K, Kazutaka K, Hidehisa S, Hideki H (2015) Cost-effectiveness of maintenance hemodialysis in japan. Ther Apher Dial 19(5):441–449Google Scholar
  30. Uyar AS, Ozcan E, Urquhart N (2013) Automated scheduling and planning from theory to practice. Stud Comput Intell 21(5):42–43zbMATHGoogle Scholar
  31. Wu Y, Dong M, Zheng Z (2014) Patient scheduling with periodic deteriorating maintenance on single medical device. Comput Oper Res 49(49):107–116MathSciNetzbMATHGoogle Scholar
  32. Xu N, Mckee SA, Nozick LK, Ufomata R (2008) Augmenting priority rule heuristics with justification and rollout to solve the resource-constrained project scheduling problem. Comput Oper Res 35(10):3284–3297zbMATHGoogle Scholar
  33. Yan C, Tang J, Jiang B, Fung RYK (2015) Sequential appointment scheduling considering patient choice and service fairness. Int J Prod Res 53(24):7376–7395Google Scholar
  34. Yao ZM, Bai LJ, Meng HY (2012) Design and application of an automatic scheduling optimized algorithm for hemodialysis machine. Meas Control Technol 31(9):51–55Google Scholar
  35. Zhang X, Wang H, Wang X (2015) Patients scheduling problems with deferred deteriorated functions. J Comb Optim 30(4):1027–1041MathSciNetzbMATHGoogle Scholar
  36. Zhong L, Luo S, Wu L, Xu L, Yang J, Tang G (2014) A two-stage approach for surgery scheduling. J Combin Optim 27(3):545–556MathSciNetzbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of AutomationHuazhong University of Science and TechnologyWuhanChina
  2. 2.Key Laboratory of Education Ministry for Image Processing and Intelligent ControlWuhanChina
  3. 3.Department of Radiation OncologyUniversity of Maryland School of MedicineBaltimoreUSA
  4. 4.Pu ai HospitalWuhanChina

Personalised recommendations

Cite article

Buy options