Waiting Online versus In-Person: An Empirical Study on Outpatient Clinic Service Incompletion

Management Science and Information Systems Seminar（2024-03）

Title: Waiting Online versus In-Person: An Empirical Study on Outpatient Clinic Service Incompletion

Speaker:  Jimmy Qin, Columbia University

Time: Friday, March 1, 10:00-11:30 a.m., Beijing Time

Location: Room 216, Guanghua Building 2

Abstract

The adoption of online services, such as telemedicine, has increased rapidly over the last few years. To better manage online services and effectively integrate them with in-person services, we need to better understand customer behaviors under the two service modalities. Utilizing data from two large internal medicine outpatient clinics, we take an empirical approach to study service incompletion for in-person and telemedicine appointments respectively. We focus on estimating the causal effect of physician availability on service incompletion. When physicians are unavailable, patients may be more likely to leave without being seen. We introduce a multivariate probit model with instrumental variables to handle estimation challenges due to endogeneity, sample selection, and measurement error. Our estimation results show that intra-day delay increases the telemedicine service incompletion rate by 7.40%, but it does not have a significant effect on the in-person service incompletion rate. This suggests that telemedicine patients may leave without being seen when delayed, while in-person patients are not sensitive to intra-day delay. We conduct counterfactual experiments to optimize the intra-day sequencing rule when having both telemedicine and in-person patients. Our analysis indicates that not correctly differentiating the types of incompletions due to intra-day delays from no-show can lead to highly suboptimal patient sequencing decisions.

Biography

Jimmy Qin is a Ph.D. candidate in the Decision, Risk, and Operations (DRO) division of Columbia University Graduate School of Business, where he is advised by Carri W. Chan, Jing Dong, and Paul Glasserman. He works closely with healthcare professionals to address emerging questions about improving healthcare delivery. He is particularly interested in the role of digital healthcare tools in increasing access to care, reducing costs, and reducing disparities. He develops and utilizes empirical models to have a deep understanding of key tradeoffs in the healthcare system, and use other operations research tools to provide structural insights and to identify prescriptive policies. His work has been recognized as the finalist for the INFORMS Health Application Society Student Paper Competition (2023) and for the INFORMS Service Science Best Student Paper Award (2023). Before coming to Columbia, he obtained his bachelor's and master's degrees from Fudan University and Stanford University respectively, both in statistics.