Analytical models to determine room requirements in outpatient clinics

  • Authors:
  • Peter J. Hulshof;Peter T. Vanberkel;Richard J. Boucherie;Erwin W. Hans;Mark Houdenhoven;Jan-Kees C. Ommeren

  • Affiliations:
  • Center for Healthcare Operations Improvement and Research, University of Twente, Enschede, The Netherlands 7500 AE and Reinier de Graaf Groep, Delft, The Netherlands 2600 GA;Center for Healthcare Operations Improvement and Research, University of Twente, Enschede, The Netherlands 7500 AE;Center for Healthcare Operations Improvement and Research, University of Twente, Enschede, The Netherlands 7500 AE;Center for Healthcare Operations Improvement and Research, University of Twente, Enschede, The Netherlands 7500 AE;Haga Ziekenhuis, Den Haag, The Netherlands 2504 LN;Stochastic Operations Research, University of Twente, Enschede, The Netherlands 7500 AE

  • Venue:
  • OR Spectrum
  • Year:
  • 2012

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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.