Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1937-5956.2011.01297.x
Title: A universal appointment rule in the presence of no-shows and walk-ins
Authors: Cayirli, T.
Yang, K.K.
Quek, S.A. 
Keywords: appointment scheduling
healthcare
nonlinear regression
simulation
Issue Date: 2012
Source: Cayirli, T., Yang, K.K., Quek, S.A. (2012). A universal appointment rule in the presence of no-shows and walk-ins. Production and Operations Management 21 (4) : 682-697. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1937-5956.2011.01297.x
Abstract: This study introduces a universal "Dome" appointment rule that can be parameterized through a planning constant for different clinics characterized by the environmental factorsâno-shows, walk-ins, number of appointments per session, variability of service times, and cost of doctor's time to patients' time. Simulation and nonlinear regression are used to derive an equation to predict the planning constant as a function of the environmental factors. We also introduce an adjustment procedure for appointment systems to explicitly minimize the disruptive effects of no-shows and walk-ins. The procedure adjusts the mean and standard deviation of service times based on the expected probabilities of no-shows and walk-ins for a given target number of patients to be served, and it is thus relevant for any appointment rule that uses the mean and standard deviation of service times to construct an appointment schedule. The results show that our Dome rule with the adjustment procedure performs better than the traditional rules in the literature, with a lower total system cost calculated as a weighted sum of patients' waiting time, doctor's idle time, and doctor's overtime. An open-source decision-support tool is also provided so that healthcare managers can easily develop appointment schedules for their clinical environment. © 2011 Production and Operations Management Society.
Source Title: Production and Operations Management
URI: http://scholarbank.nus.edu.sg/handle/10635/44099
ISSN: 10591478
DOI: 10.1111/j.1937-5956.2011.01297.x
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

51
checked on Dec 5, 2017

WEB OF SCIENCETM
Citations

42
checked on Nov 16, 2017

Page view(s)

44
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.