Managing Outpatient Service with Strategic Walk-ins
Management Science (forthcoming)
77 Pages Posted: 27 Apr 2020 Last revised: 7 Jul 2022
Date Written: July 5, 2022
Abstract
Outpatient care providers usually allow patients to access service via scheduling appointments or direct walk-in. Patients choose strategically between these two access channels (and otherwise balking) based on the trade-off of appointment delay and in-clinic waiting. How to manage outpatient care with such dual access channels, taking into account patient strategic choice behavior, is a challenge faced by providers. We study three operational levers to address this management challenge: service capacity allocation between these two channels, appointment delay information revelation via the choice and design of online scheduling systems, and a walk-in triage system which restricts the use of walk-in hours only for acute care. By studying a stylized queueing model, we find that neither a real-time online scheduling system (which offers instant access to appointment delay information at time of booking) nor an asynchronous online system (which does not directly provide delay information) can be universally more efficient. Although real-time systems appear more popular in practice, asynchronous systems sometimes can result in higher operational efficiency. Under the provider’s optimal capacity allocation, which scheduling system is more efficient hinges on two key factors: patient demand-provider capacity relationship and patient willingness to wait. For the walk-in triage system, we find that it may or may not be beneficial to adopt; the provider’s own cost tradeoff between lost demand and overtime work is the key determinant. Our research highlights that there is no one-size-fits-all model for outpatient care management and the best use of operational levers critically depends on the practice environment.
Keywords: customer strategic behavior, appointment scheduling, walk-ins, queueing models
JEL Classification: C44, C61, M10, I10
Suggested Citation: Suggested Citation