Essays on Healthcare Operations Restricted; Files Only

Liu, Jiayi (Spring 2022)

Permanent URL: https://etd.library.emory.edu/concern/etds/1j92g857j?locale=en
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Abstract

This dissertation contains three essays on healthcare operations. In the first essay, I quantify the impacts of online platforms on drug abuse. I use the phased rollout of Craigslist, a major online platform, as an experimental setup. Applying a difference-in-differences approach on a national panel data set for all counties in the United States from 1997 to 2008, I find strong evidence of increased drug abuse after Craigslist’s entry. The impacts are larger among women, whites, Asians, and the more educated---those traditionally considered at lower risk for drug misuse. Furthermore, the unintended consequences of Craigslist are more likely to accrue in larger, wealthier areas with initially low levels of drug abuse. These findings raise the possibility that the marked growth in the U.S. drug abuse may have partially stemmed from the wider availability of illicit drugs online at the very beginning of its evolution. In the second essay, I apply text-based nudges to reduce patient no-shows. I run a field experiment in a local hospital where I change the framing of the reminder messages by highlighting the potential long wait time for the next available appointment. I find patient no-shows reduce by 28.6%; the resulting improvement in capacity utilization and patient throughput can lead to a 5.2% increase in clinic revenue. I further uncover the mechanisms behind this effect through a laboratory experiment. These findings demonstrate that through appropriately framed messages, queue operators can tap into the behavioral biases of individuals in order to engender a desired queuing response such as a reduction in queue abandonment. In the third essay, I study how patients change their behavior in response to the kidney allocation rules. I exploit a national kidney allocation policy that assigns priority based on an age cutoff. Using a sharp regression-discontinuity design, I find that allocation priority in deceased-donor organs substantially crowds out living donors. In addition, prioritized patients are less likely to accept an offered organ of a given quality, which may impact the organ wastage. These findings have implications on kidney allocation policy making.

Table of Contents

1 Drug Abuse and the Internet: Evidence from Craigslist 1

1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Theoretical Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

1.5 Robustness Checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1.6 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Appendices 17

2 Nudging Patient Choice by Messaging 22

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.2 Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2.3 Hypothesis Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

2.4 Waits Framing Effect: A Field Experiment . . . . . . . . . . . . . . . . . . . . . . . . 34

2.5 Unpacking Waits Framing Nudge: A Laboratory Experiment . . . . . . . . . . . . . 41

2.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Appendices 51

3 Behavioral Responses to Kidney Allocation Priority: A Regression Discontinuity

Analysis 54

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

3.3 Institutional Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

3.4 Data and Descriptive Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

3.5 Empirical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

3.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

4 Tables 76

5 Figures 101

References 121

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