Essays on Healthcare Providers and Regulatory Incentives Restricted; Files Only
Smith, Andrew (Spring 2024)
Abstract
Healthcare is not only one of the largest industries in the United States, but also one of the
most heavily regulated. In this dissertation, I evaluate how some of these regulatory schemes
influence the behavior of providers in this industry.
In the first chapter—joint work with my advisor, Sara Markowitz—I consider oversight
ratios and their effect on the supply of nurse practitioners (NPs). Many states require
that NPs practice under the supervision of a physician, and a subset of these states limit
the number of NPs that any one physician may supervise at a time. In the last two decades,
New York, Nevada, and Pennsylvania have repealed these oversight ratios. Using synthetic
control, we estimate the effect of repeal in each of these states. Surprisingly, we find that
repealing this peculiar regulation does not increase the number of NPs practicing in any of
these states.
Chapters two and three of this dissertation evaluate the effect on a physician of
being sued for medical malpractice. A rich literature indicates that doctors are very sensitive
to the possibility of being sued for medical malpractice, but it is not clear why. The existence
of malpractice insurance means that physicians rarely pay anything out of pocket when they
are sued, and malpractice insurance premiums are not particularly experience rated. Prior
research has postulated in passing that the thing doctors are afraid of is damage to their
reputations.
In Chapter 2, I test the reputational harm hypothesis by asking whether patients
and their referring physicians care about malpractice history when choosing a specialist.
Using a discrete choice model of demand for hip and knee replacement surgery in Florida,
I find that a surgeon who has been sued is less likely to be selected than one who has not.
While this effect is small, it appears to persist over time, and physicians who prevail in their
lawsuits by paying out zero or nominal damages are not much more likely to be selected
than physicians who pay out larger sums.
Chapter 3 builds on the findings of Chapter 2. In Chapter 2, I cannot distinguish
the roles of the patient and the referring physician in choosing a specialist. In Chapter
3, I analyze the effect of being sued for malpractice on a specialist’s referral relationships.
Using difference-in-differences and event studies, I estimate the effect of a first lawsuit on
the number of referral sources, the total volume of referrals, and the concentration of these
referral sources between referral sources. Across outcomes, I find small and statistically
insignificant effects.
Table of Contents
Nurse Practitioner Oversight Ratios and Labor Market Outcomes 1
1. Introduction 2
2. Oversight Ratios 6
3. Labor Market Outcomes 9
4. Methods 11
5. Results 13
5.1 New York 13
5.2 Nevada 17
5.3 Pennsylvania 19
6. Conclusion 21
References 23
Appendix 48
Does Your Reputation Precede You? The Role of Malpractice History in the
Demand for Specialist Physicians 63
1. Introduction 64
2. Background on Medical Malpractice 67
3. Data 72
3.1 Florida Professional Liability Claims Reports 72
3.2 Florida Hospital Inpatient File 73
3.3 Other Data 74
4. Sample Construction and Summary Statistics 75
4.1 Patient Safety Indicators 75
4.2 Sample Construction 77
4.3 Choice Set Construction 79
5. Methods 81
6. Results 86
6.1 Primary Results 86
6.2 Time-Restricted Models 87
6.2.1 Choice of Lookback Period Length 87
6.2.2 Time-Restricted Results 88
6.3 Willingness to Travel 88
6.4 Alternative Reputational Mechanisms 89
7. Conclusion 89
References 91
What’s a Little Malpractice Between Friends? How Malpractice Affects Referral
Relationships Between Physicians 115
1. Introduction 116
2. Background and Data 118
2.1 Background 118
2.2 Data 121
2.2.1 Physician Shared Patient Patterns Data 121
2.2.2 Florida Professional Liability Claims Reports (PLCR) 121
2.2.3 Other Sources 122
2.2.4 Sample Construction 123
2.2.5 Descriptive Statistics 124
3. Empirical Strategy 124
3.1 Conditional Parallel Trends 126
3.2 Random Treatment Timing 127
4. Results 128
5. Conclusion 129
References 130
About this Dissertation
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