Optimising the booking horizon in healthcare clinics considering no-shows and cancellations

Gréanne Leeftink, Gabriela Martinez, Erwin W. Hans, Mustafa Y. Sir, Kalyan S. Pasupathy

Research output: Contribution to journalArticlepeer-review

Abstract

Patient no-shows and cancellations are a significant problem to healthcare clinics, as they compromise a clinic's efficiency. Therefore, it is important to account for both no-shows and cancellations into the design of appointment systems. To provide additional empirical evidence on no-show and cancellation behaviour, we assess outpatient clinic data from two healthcare providers in the USA and EU: no-show and cancellation rates increase with the scheduling interval, which is the number of days from the appointment creation to the date the appointment is scheduled for. We show the temporal cancellation behaviour for multiple scheduling intervals is bimodally distributed. To improve the efficiency of clinics at a tactical level of control, we determine the optimal booking horizon such that the impact of no-shows and cancellations through high scheduling intervals is minimised, against a cost of rejecting patients. Where the majority of the literature only includes a fixed no-show rate, we include both a cancellation rate and a time-dependent no-show rate. We propose an analytical queuing model with balking and reneging, to determine the optimal booking horizon. Simulation experiments show that the assumptions of this model are viable. Computational results demonstrate general applicability of our model by case studies of two hospitals.

Original languageEnglish (US)
Pages (from-to)3201-3218
Number of pages18
JournalInternational Journal of Production Research
Volume60
Issue number10
DOIs
StatePublished - 2022

Keywords

  • Applications in healthcare systems
  • appointment scheduling
  • cancellation rate
  • healthcare logistics
  • queueing analysis

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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