Skip to main content
Log in

Appointment scheduling optimization with two stages diagnosis for clinic outpatient

  • Original Paper
  • Published:
Computational Statistics Aims and scope Submit manuscript

Abstract

This paper attempts to compare the performance between a single-stage appointment scheduling system and two-stage appointment scheduling system. For this purpose, a queuing model is firstly formulated with the objective of maximizing the weighted hospitals benefit minus the cost of patient waiting and doctor overtime, for a two-stage appointment scheduling system considering no-shows. To facilitate the comparison, we can alter the number of diagnosis stages by adjusting the probabilities that patients need to do further examinations, e.g., X-rays or blood tests. The single-stage queuing model assumes that all patients will finish their treatment after their first diagnosis, and other assumptions are the same as that in a two-stage appointment scheduling system. The performances of two-stage appointment scheduling systems varying with no-show probabilities and probabilities that patients have a second-stage diagnosis are presented. Experimental results indicate that the optimal number of patients needs to be more than the capacity of doctors in the first few slots, and less than those in the last few slots. We need to weigh the probability of no-shows and the probability of doing further examinations (second-stage) when determining the total number of patients to be scheduled. Under a higher no-show probability, arranging more patients than the workload reduces the waste of doctors capacity; and on the contrary, under a higher probability of doing examinations, arranging fewer patients than the workload can reduce system congestion.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Ahmadi-Javid A, Jalali Z, Klassen KJ (2016) Outpatient appointment systems in healthcare : a review of optimization studies. Eur J Oper Res 258(1):3–34

    Article  MathSciNet  MATH  Google Scholar 

  • Bailey N (1952) A study of queues and appointment systems in hospital out-patient departments with special reference to waiting-times. J R Stat Soc B 14(2):185–199

    Google Scholar 

  • Castro E, Petrovic S (2012a) Combined mathematical programming and heuristics for a radiotherapy pre-treatment. J Sched 15(3):333–346 scheduling problem

    Article  MathSciNet  Google Scholar 

  • Castro E, Petrovic S (2012b) Combined mathematical programming and heuristics for a radiotherapy pre-treatment scheduling problem. J Sched 15(3):333–346

    Article  MathSciNet  Google Scholar 

  • Cayirli T, Veral E (2003) Outpatient scheduling in health care : a review of literature. Prod Oper Manag 12(4):519–549

    Article  Google Scholar 

  • Conforti D, Guerriero F, Guido R (2008) Optimization models for radiotherapy patient scheduling. 4OR-Q J Oper Res 6(3):263–278

    Article  MathSciNet  MATH  Google Scholar 

  • Conforti D, Guerriero F, Guido R (2010) Non-block scheduling with priority for radiotherapy treatments. Eur J Oper Res 201(1):289–296

    Article  MATH  Google Scholar 

  • Conforti D, Guerriero F, Guido R, Veltri M (2011) An optimal decision-making approach for the management of radiotherapy patients. OR Spektrum 33(1):123–148

    Article  MathSciNet  MATH  Google Scholar 

  • Gupta D, Denton B (2008) Appointment scheduling in health care: challenges and opportunities. IIE Trans 40:800–819

    Article  Google Scholar 

  • 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 Syst 1(2):129–175

    Article  Google Scholar 

  • Kaandorp G, Koole G (2007) Optimal outpatient appointment scheduling. Health Care Manag Sci 10:217–229

    Article  Google Scholar 

  • Kemper B, Klaassen CA, Mandjes M (2014) Optimized appointment scheduling. Eur J Oper Res 239(1):243–255

    Article  MathSciNet  MATH  Google Scholar 

  • Kuiper A, Kemper B, Mandjes M (2015) A computational approachto optimized appointment scheduling. Queueing Syst 79(1):5–36

    Article  MathSciNet  MATH  Google Scholar 

  • Laganga LR, Lawrence SR (2007) Clinic overbooking to improve patient access and increase provider productivity. Decis Sci 38(2):251–276

    Article  Google Scholar 

  • LaGanga LR, Lawrence SR (2012) Appointment overbooking in health care clinics to improve patient service and clinic performance. Prod Oper Manag Soc 21(5):847–888

    Google Scholar 

  • Lambrecht SM (2009) An advanced queueing model to analyze appointment-driven service systems. Comput Oper Res 36(10):2773–2785

    Article  MATH  Google Scholar 

  • Lin J, Muthuraman K, Lawley M (2011) Optimal and approximate algorithms for sequential clinical scheduling with no-shows. IIE Trans Healthc Syst Eng 1(1):20–36

    Article  Google Scholar 

  • Liu N, Ziya S (2015) Panel size and overbooking decisions for appointment-based services under patients no-shows. Prod Oper Manag 23(12):2209–2223

    Article  Google Scholar 

  • Osorio C, Bierlaire M (2009) An analytic finite capacity queueing network model capturing the propagation of congestion and blocking. Eur J Oper Res 196(3):9966–1007

    Article  MATH  Google Scholar 

  • Prez E, Ntaimo L, Wilhelm WE, Bailey C, McCormack P (2011) Patient and resource scheduling of multi-step medical procedures in nuclear medicine. IIE Trans Healthc Syst Eng 1(3):168–184

    Article  Google Scholar 

  • Prez E, Ntaimo L, Malav CO, Bailey C, McCormack P (2013) Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine. Health Care Manag Sci 16(4):281–299

    Article  Google Scholar 

  • Rais A, Viana A (2010) Operations research in healthcare: a survey. Int Trans Oper Res 18:1–31

    Article  MathSciNet  Google Scholar 

  • Robinson LW, Chen RR (2010) A comparison of traditional and open-access policies for appointment scheduling. Manuf Serv Oper Manag 12:330–346

    Article  Google Scholar 

  • Samorani M, LaGanga LR (2015) Outpatient appointment scheduling given individual day-dependent no-show predictions eur. J Oper Res 240(1):245–257

    Article  MathSciNet  MATH  Google Scholar 

  • Turkcan A, Zeng B, Lawley M (2012) Chemotherapy operations planning and scheduling. IIE Trans Healthc Syst Eng 2(1):31–49

    Article  Google Scholar 

  • Vissers J (2011) Or in healthcare: a European perspective. Eur J Oper Res 212(2):223–234

    Article  MathSciNet  Google Scholar 

  • Wang J, Fung RY (2014) An integer programming formulation for outpatient scheduling with patient preference. Ind Eng Manag Syst 13(2):193–202

    Google Scholar 

  • Wang WY, Gupta D (2011) Adaptive appointment systems with patient preferences. Manuf Serv Oper Manag 13(3):373–389

    Article  Google Scholar 

  • Wolsey GNL (2014) Integer and optimization. In: Integer and optimization. Wiley

  • Yan C, Tang J, Jiang B, Fung RY (2015) Comparison of traditional and open-access appointment scheduling for exponentially distributed service time. J Healthc Eng 6(3):345

    Article  Google Scholar 

  • Zeng B, Turkcan A, Lin J, Lawley M (2010) Clinic scheduling models with overbooking for patients with heterogeneous no-show probabilities. Ann Oper Res 178(1):121–144

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This paper is financially supported by National Natural Science Foundation of China (71420107028, 71501027).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiafu Tang.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, X., Tang, J. & Yan, C. Appointment scheduling optimization with two stages diagnosis for clinic outpatient. Comput Stat 35, 469–490 (2020). https://doi.org/10.1007/s00180-019-00876-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00180-019-00876-0

Keywords

Navigation