Skip to main content
SpringerLink
Log in

Multi-objective admission planning problem: a two-stage stochastic approach

  • Published:
Health Care Management Science Aims and scope Submit manuscript

Abstract

Effective admission planning can improve inpatient throughput and waiting times, resulting in better quality of service. The uncertainty in the patient arrival and the availability of resources makes the patient’s allocation difficult to manage. Thus, in the admission process hospitals aim to accomplish targets of resource utilization and to lower the cost of service. Both objectives are related and in conflict. In this paper, we present a bi-objective stochastic optimization model to study the trade-off between the resource utilization and the cost of service, taking into account demand and capacity uncertainties. Real data from the surgery and medical areas of a Chilean public hospital are used to illustrate the approach. The results show that the solutions of our approach outperform the actual practice in the Chilean hospital.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Adan I, Bekkers J, Dellaert N, Jeunet J, Vissers J (2011) Improving operational effectiveness of tactical master plans for emergency and elective patients under stochastic demand and capacitated resources. Eur J Oper Res 213(1):290–308

    Article  Google Scholar 

  2. Adan I, Bekkers J, Dellaert N, Vissers J, Yu X (2009) Patient mix optimisation and stochastic resource requirements: a case study in cardiothoracic surgery planning. Health Care Management Science 12(2):129

    Article  Google Scholar 

  3. Alvarez PP, Vera JR (2014) Application of robust optimization to the sawmill planning problem. Ann Oper Res 219(1):457–475

    Article  Google Scholar 

  4. Bekker R, Koeleman PM (2011) Scheduling admissions and reducing variability in bed demand. Health Care Management Science 14(3):237

    Article  Google Scholar 

  5. Birge JR, Louveaux F (2011) Introduction to stochastic programming. Springer Science & Business Media, Berlin

    Book  Google Scholar 

  6. Conejo AJ, Carrión M, Morales JM, et al. (2010) Decision making under uncertainty in electricity markets, vol 1. Springer, Berlin

    Book  Google Scholar 

  7. Deb K (2014) Multi-objective optimization. Search methodologies. Springer, New York, pp 403–49

    Google Scholar 

  8. Dobson G, Lee H-H, Pinker E (2010) A model of icu bumping. Operations Research 58(6):1564–1576

    Article  Google Scholar 

  9. Durán G., Rey PA, Wolff P (2017) Solving the operating room scheduling problem with prioritized lists of patients. Ann Oper Res 258(2):395–414

    Article  Google Scholar 

  10. Gallivan S, Utley M, Treasure T, Valencia O (2002) Booked inpatient admissions and hospital capacity: mathematical modelling study. Bmj 324(7332):280–282

    Article  Google Scholar 

  11. Gemmel P, Van Dierdonck R (1999) Admission scheduling in acute care hospitals: does the practice fit with the theory? International Journal of Operations & Production Management 19(9):863–878

    Article  Google Scholar 

  12. Green LV (2002) How many hospital beds? Inquiry: the Journal of Health Care Organization, Provision, and Financing 39(4):400–412

    Article  Google Scholar 

  13. Green LV (2005) Capacity planning and management in hospitals. In: Operations research and health care. Springer. pp 15–41

  14. Guerriero F, Guido R (2011) Operational research in the management of the operating theatre: a survey. Health Care Management Science 14(1):89–114

    Article  Google Scholar 

  15. Helm JE, AhmadBeygi S, Van Oyen MP (2011) Design and analysis of hospital admission control for operational effectiveness. Prod Oper Manag 20(3):359–374

    Article  Google Scholar 

  16. Hulshof PJ, Boucherie RJ, Hans EW, Hurink JL (2013) Tactical resource allocation and elective patient admission planning in care processes. Health Care Management Science 16(2):152–166

    Article  Google Scholar 

  17. Hulshof PJ, Mes MR, Boucherie RJ, Hans EW (2016) Patient admission planning using approximate dynamic programming. Flex Serv Manuf J 28(1–2):30–61

    Article  Google Scholar 

  18. Kortbeek N, Braaksma A, Burger CA, Bakker PJ, Boucherie RJ (2015) Flexible nurse staffing based on hourly bed census predictions. Int J Prod Econ 161:167–180

    Article  Google Scholar 

  19. Kusters RJ, Groot PM (1996) Modelling resource availability in general hospitals design and implementation of a decision support model. Eur J Oper Res 88(3):428–445

    Article  Google Scholar 

  20. Lamiri M, Xie X, Dolgui A, Grimaud F (2008) A stochastic model for operating room planning with elective and emergency demand for surgery. Eur J Oper Res 185(3):1026–1037

    Article  Google Scholar 

  21. Min D, Yih Y (2010) An elective surgery scheduling problem considering patient priority. Comput Oper Res 37(6):1091–1099

    Article  Google Scholar 

  22. Mullen PM (2003) Prioritising waiting lists: how and why? Eur J Oper Res 150(1):32–45

    Article  Google Scholar 

  23. Peters-Groot P (1993) Decision support for admission planning under multiple resource constraints. PhD thesis. Technische Universiteit Eindhoven

  24. Pozo D, Sauma EE, Contreras J (2013) A three-level static milp model for generation and transmission expansion planning. IEEE Transactions on Power Systems 28(1):202–210

    Article  Google Scholar 

  25. Samudra M, Van Riet C, Demeulemeester E, Cardoen B, Vansteenkiste N, Rademakers FE (2016) Scheduling operating rooms: achievements, challenges and pitfalls. J Sched 19(5): 493–525

    Article  Google Scholar 

  26. Tamiz M, Mirrazavi S, Jones D (1999) Extensions of pareto efficiency analysis to integer goal programming. Omega 27(2): 179–188

    Article  Google Scholar 

  27. Testi A, Tànfani E (2009) Tactical and operational decisions for operating room planning: efficiency and welfare implications. Health Care Management Science 12(4):363

    Article  Google Scholar 

  28. Testi A, Tanfani E, Valente R, Ansaldo G, Torre G (2008) Prioritizing surgical waiting lists. J Eval Clin Pract 14(1):59–64

    Article  Google Scholar 

  29. Thompson S, Nunez M, Garfinkel R, Dean MD (2009) Or practice—efficient short-term allocation and reallocation of patients to floors of a hospital during demand surges. Operations Research 57(2):261–273

    Article  Google Scholar 

  30. Vissers J, Adan IJ, Bekkers JA (2005) Patient mix optimization in tactical cardiothoracic surgery planning: a case study. IMA J Manag Math 16(3):281–304

    Article  Google Scholar 

  31. Vissers JM, Adan IJ, Dellaert NP (2007) Developing a platform for comparison of hospital admission systems: an illustration. Eur J Oper Res 180(3):1290–1301

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by CONICYT under Grant 6635/2014 and FONDEF project CA13I10319. Author J. Vera would like to acknowledge the support of Iniciativa Milenio grant ICM/FIC RC130003. The authors would like to thank the collaboration of the managers of the Chilean Hospital used in this research as they provide data and insights used to solve the problem presented in this paper.

Author information

Authors and Affiliations

  1. Department of Industrial and Systems Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

    Ana Batista & Jorge Vera

  2. Center for Energy Science and Technology, Skolkovo Institute of Science and Technology, Moscow, Russia

    Ana Batista & David Pozo

  3. Institute for Mathematical and Computational Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

    Jorge Vera

Authors
  1. Ana Batista
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jorge Vera
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David Pozo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ana Batista.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: Result tables

Appendix: Result tables

Tables 6 and 7, show the values of the patient allocation related to Internal, External, Temporary assignment and Unmet demand as well, according to the weight, λ.

Table 6 Patient allocation values (internal - external) in % by the weight λ, ut = 85%
Full size table
Table 7 Patient allocation values (temporary - unmet) in % by the weight λ, ut = 85%
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Batista, A., Vera, J. & Pozo, D. Multi-objective admission planning problem: a two-stage stochastic approach. Health Care Manag Sci 23, 51–65 (2020). https://doi.org/10.1007/s10729-018-9464-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10729-018-9464-4

Keywords

Search

Navigation