Abstract
Outpatient clinics traditionally organize processes such that the doctor remains in a consultation room while patients visit for consultation, we call this the Patient-to-Doctor policy (PtD-policy). A different approach is the Doctor-to-Patient policy (DtP-policy), whereby the doctor travels between multiple consultation rooms, in which patients prepare for their consultation. In the latter approach, the doctor saves time by consulting fully prepared patients. We use a queueing theoretic and a discrete-event simulation approach to provide generic models that enable performance evaluations of the two policies for different parameter settings. These models can be used by managers of outpatient clinics to compare the two policies and choose a particular policy when redesigning the patient process. We use the models to analytically show that the DtP-policy is superior to the PtD-policy under the condition that the doctor’s travel time between rooms is lower than the patient’s preparation time. In addition, to calculate the required number of consultation rooms in the DtP-policy, we provide an expression for the fraction of consultations that are in immediate succession; or, in other words, the fraction of time the next patient is prepared and ready, immediately after a doctor finishes a consultation. We apply our methods for a range of distributions and parameters and to a case study in a medium-sized general hospital that inspired this research.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Baesler FF, Jahnsen HE, DaCosta M (2003) Emergency departments I: the use of simulation and design of experiments for estimating maximum capacity in an emergency room. In: Chick S, Sánchez PJ, Ferrin D, Morrice DJ (eds) Proceedings of 35th Winter Simulation Conference. ACM, New York, pp 1903–1906
Bailey NTJ (1952) A study of queues and appointment systems in hospital out-patient departments, with special reference to waiting-times. J R Stat Soc 14: 185–199
Boucherie RJ, Chao X, Miyazawa M (2003) Arrival first queueing networks with applications in kanban production systems. Perform Eval 51(2–4): 83–102
Brahimi M, Worthington DJ (1991) Queueing models for out-patient appointment systems—a case study. J Oper Res Soc 42(9): 733–746
Buitenhek R (1998) Performance evaluation of dual resource manufacturing systems. Ph.D. thesis, University of Twente, The Netherlands
Cayirli T, Veral E (2003) Outpatient scheduling in health care: a review of literature. Prod Oper Manag 12(4): 519–549
Chand S, Moskowitz H, Norris JB, Shade S, Willis DR (2009) Improving patient flow at an outpatient clinic: study of sources of variability and improvement factors. Health Care Manag Sci 12(3): 325–340
Côté MJ (1999) Patient flow and resource utilization in an outpatient clinic. Socio Econ Plan Sci 33(3): 231–245
De Angelis V, Felici G, Impelluso P (2003) Integrating simulation and optimisation in health care centre management. Eur J Oper Res 150(1): 101–114
Duguay C, Chetouane F (2007) Modeling and improving emergency department systems using discrete event simulation. Simulation 83(4): 311–320
GHZ website (2011) Website of Groene Hart Ziekenhuis (in Dutch). http://www.ghz.nl. Accessed 16 April 2011
Harper PR, Gamlin HM (2003) Reduced outpatient waiting times with improved appointment scheduling: a simulation modelling approach. OR Spectr 25(2): 207–222
Ho CJ, Lau HS (1992) Minimizing total cost in scheduling outpatient appointments. Manag Sci 38(12): 1750–1764
Isken MW, Ward TJ, McKee TC (1999) Simulating outpatient obstetrical clinics. In: Farrington PA, Nembhard HB, Sturrock DT, Evans GW (eds) Proceedings of 31st Winter Simulation Conference. ACM, New York, pp 1557–1563
Jiang L, Giachetti RE (2008) A queueing network model to analyze the impact of parallelization of care on patient cycle time. Health Care Manag Sci 11(3): 248–261
Johnston MJ, Samaranayake P, Dadich A, Fitzgerald JA (2009) Modelling radiology department operation using discrete event simulation. Working paper
Kopzon A, Nazarathy Y, Weiss G (2009) A push–pull network with infinite supply of work. Queueing Syst 62(1): 75–111
Law AM (2009) Simulation modeling and analysis, 4th edn. McGraw-Hill, New York
Levy H, Sidi M (1990) Polling systems: applications, modeling, and optimization. IEEE Trans Commun 38(10): 1750–1760
Robinson LW, Chen RR (2003) Scheduling doctors’ appointments: optimal and empirically-based heuristic policies. IIE Trans 35(3): 295–307
Swisher JR, Jacobson SH (2002) Evaluating the design of a family practice healthcare clinic using discrete-event simulation. Health Care Manag Sci 5(2): 75–88
Swisher JR, Jacobson SH, Jun JB, Balci O (2001) Modeling and analyzing a physician clinic environment using discrete-event (visual) simulation. Comput Oper Res 28(2): 105–125
Takagi H (1998) Queueing analysis of polling models: progress in 1990–1994. In: Frontiers in queueing: models and applications in science and engineering. CRC Press, Inc., Boca Raton, pp 119–146
Vissers J, Beech R (2005) Health operations management: patient flow logistics in health care. Routledge, London
Zonderland ME, Boer F, Boucherie RJ, de Roode A, Kleef JW (2009) Redesign of a university hospital preanesthesia evaluation clinic using a queuing theory approach. Anesth Analg 109(5): 1612–1614
Open Access
This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Author information
Authors and Affiliations
Corresponding author
Additional information
This research is supported by the Dutch Technology Foundation STW, applied science division of NWO and the Technology Program of the Ministry of Economic Affairs. We thank the hospitals RIVAS Gorinchem, Reinier de Graaf Gasthuis, Haga Ziekenhuis, and Groene Hart Ziekenhuis for inspiring us and providing data.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
About this article
Cite this article
Hulshof, P.J.H., Vanberkel, P.T., Boucherie, R.J. et al. Analytical models to determine room requirements in outpatient clinics. OR Spectrum 34, 391–405 (2012). https://doi.org/10.1007/s00291-012-0287-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00291-012-0287-2