Evaluating appointment postponement in scheduling patients at a diagnostic clinic

Abstract

Diagnostic clinics are among healthcare facilities that suffer from long waiting times which can worsen medical outcomes and increase patient no‐shows. Reducing waiting times without significant capital investments is a challenging task. We tackle this challenge by proposing a new appointment scheduling policy that does not require significant investments for diagnostic clinics. The clinic in our study serves outpatients, inpatients, and emergency patients. Emergency patients must be seen on arrival, and inpatients must be given next day appointments. Outpatients, however, can be given later appointments. The proposed policy takes advantage of this by allowing the postponement of the acceptance of appointment requests from outpatients. The appointment scheduling process is modeled as a two‐stage stochastic programming problem where a portion of the clinic capacity is allocated to inpatients and emergency patients in the first stage. In the second stage, outpatients are scheduled based on their priority classes. After a detailed analysis of the solutions obtained from the two‐stage stochastic model, we develop a simple, non‐anticipative policy for patient scheduling. We evaluate the performance of this proposed, easy‐to‐implement policy in a simulation study which shows significant improvements in outpatient indirect waiting times.

How does the hospital make a safe and stable elective surgery plan during COVID-19 pandemic?

“…Although elective surgery is not as urgent as emergency surgery, it does not mean that it can be postponed indefinitely, because postponement may lead to deterioration of the patient's condition and emotional dissatisfaction. Therefore, waiting time is an important optimization goal ( Kiani et al 2022 ). In addition, given that there are differences in the diseases, it is necessary to prioritize the planning of high-priority patients ( Min and Yih 2010a ).…”

Optimization of a hybrid multi-item fabricating-shipping integrated system considering scrap, adjustable-rate, and postponement

“…Finally, the researchers conducted theoretical and computational analyses to explore the postponement strategies and deterioration rate's influence on optimal policies. Other studies (Kisperska-Moron and Swierczek, 2011;Altug, 2016;Chiu et al, 2021Chiu et al, , 2022aLin et al, 2022;Kiani et al, 2022;Hinkka et al, 2023;Soto-Ferrari et al, 2023) investigated various postponement strategies' impact on operations, management, and controlling of multi-item fabrication in manufacturers and supply chains.…”