A Universal Appointment Rule in the Presence of No‐Shows and Walk‐Ins

Abstract

This study introduces a universal “Dome” appointment rule that can be parameterized through a planning constant for different clinics characterized by the environmental factors—no‐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.

Managing waiting times to predict no-shows and cancelations at a children’s hospital

“…Research on how to manage waiting lists has mainly focused on mathematical models that help hospitals better manage resources. Queuing theory has been the most common methodology applied, and the possibility of missed appointments has been taken into account in these models (Cayirli, Yang & Quek, 2012;Green, 2010;Green & Yankovic 2011;Liu, 2016).…”

An MDP model for walk-in patient admission management in primary care clinics

“…Only a few recent studies consider the appointment scheduling systems of the clinics accepting walk-in patients (Cayirli et al, 2006(Cayirli et al, , 2008(Cayirli et al, , 2012Kim and Giachetti, 2006;LaGanga and Lawrence, 2008). Cayirli et al (2006Cayirli et al ( , 2008 investigate the performance of appointment scheduling rules (ASRs) in outpatient clinics in terms of patient waiting time and provider idle time and overtime.…”

“…In primary-care clinics with many walkin patients and high no-show rates or high late-cancellation rates, policies such as overbooking (i.e., scheduling more appointments than provider capacity in each clinic session) and accepting walkin patients are often adopted to improve provider utilization and clinic accessibility. In the literature, many studies propose quantitative models to analyze or optimize overbooking policies (Kopach et al, 2007;Lawrence, 2007, 2012;Muthuraman and Lawley, 2008;Kros et al, 2009;Zeng et al, 2010;Ratcliffe et al, 2012), and also several studies investigate the appointment scheduling systems in the clinics accepting walk-in patients (Cayirli et al, 2006(Cayirli et al, , 2008(Cayirli et al, , 2012Kim and Giachetti, 2006;LaGanga and Lawrence, 2008). In the literature studies considering walk-in patients, it is assumed that a clinic accepts all walk-in patients, and that the cost structure for walk-in patients is same as that for patients with appointments scheduled.…”

Healthcare operations management: a structured literature review

“…No-show adversely affects productivity and overall cost. Cayirli et al (2012) suggested a dome rule for fixing appointment times while taking care of different interruptions generally experienced in day to day operations of healthcare organisations. LaGanga and Lawrence (2012) came up with an appointment system which could overbook appointment schedules in a way that revenue generated from serving extra patients could balance the negative effects of increased patient waiting time and physician overtime costs.…”