105. Outpatient Department Appointment Scheduling: A Semi-Open Queuing Network Model
Invited abstract in session TA-13: Appointment scheduling, stream OR in Healthcare (ORAHS).
Tuesday, 8:30-10:00Room: Clarendon SR 1.01
Authors (first author is the speaker)
| 1. | Mahua Banerjee
|
| Quantitative Methods and Operations Management, Indian Institute of Management Kozhikode | |
| 2. | Ashutosh Sarkar
|
| Quantitative Methods & Operations Management, Indian Institute of Management Kozhikode |
Abstract
Hospital Outpatient Departments (OPDs) traditionally provide advance appointments for doctor consultations, ensuring service predictability, reduced waiting times and increased resource utilization. However, they also accept walk-in patients to protect against cancellations and no-shows. In this context, OM researchers have extensively studied various policies for scheduling walk-in patients. The parameters used to design these policies are – patient arrival sequence, caseload, consultation time, and patient waiting time. This study considers the case of the OPD of a multi-specialty hospital that offers both advance appointments as well as walk-ins with a few additional characteristics such as patients with multiple consultations and patients with appointments arriving late. These pose a challenge for the OPD manager to determine the extent of buffer to be built between consecutive appointments and the way to schedule late arrivals and walk-in patients. In this study, the complexities of the above decision environment are modeled as a semi-open queuing network (SOQN) model. The model evaluates the effectiveness of several scheduling policies and determines the optimal buffer time between appointments. Subsequently the model simulates the collected test data from the hospital, and it is observed that the effectiveness of the scheduling policies is greatly influenced by factors such as, caseload, service time variability, and prioritization of different patient classes.
Keywords
- Health Care
- Queuing Systems
- Scheduling
Status: accepted
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