Unintended Consequences of Prescription Drug Monitoring Programs Público
Wetzel, Martha (Spring 2018)
Published
Abstract
High rates of opioid overdose deaths have prompted states to implement prescription drug monitoring programs (PDMPs) to reduce opioid prescribing, but critics suggest that these policies are increasing pain for certain patients. Research shows that PDMPs can decrease opioid prescribing and overdoses, but there is no published research on the policies’ potential effects on pain and disability. Given that pain has high human and economic costs via increased disability, it is important to explore this potential tradeoff. This study uses National Health Interview Survey (NHIS) data from 2006 – 2015 to assess the effect of PDMPs on bedridden days and days of missed work. A generalized difference-in-difference approach is used to evaluate the impact of two variants of PDMPs: those with optional participation and those with mandatory participation. The results show that among adults who had a surgery or injury, mandatory PDMP programs are associated with an additional 2.4 bedridden days and 3.5 days missed days of work on average per person per year. A dose-response effect is observed for the two variants of PDMP programs, with the optional programs showing a smaller effect than the mandatory programs. No increase in the probability of receiving physical therapy, a potential substitute for opioid therapy, was observed. This study provides evidence of newly identified unintended consequences of PDMP policy, demonstrating that PDMPs appear to affect the functional capacity of individuals who have undergone surgery or experienced an injury. As a result, states and payers may wish to implement complementary policies designed to encourage judicial use of opioids and increase the use of non-opioid pain treatment modalities.
Table of Contents
Chapter 1: Introduction 1
Chapter 2: Review of the Literature 3
Background 3
Current Empirical Literature 4
Theory and Conceptual Framework 5
Testable Hypothesis 9
Chapter 3: Methods 11
Data Sources and Construct Measurement 11
Sample 16
Data Analysis 17
Chapter 4: Results 19
Sensitivity Analyses 22
Chapter 5: Discussion 25
Summary 25
Conclusions 26
Strengths and Limitations 27
Implications 28
References 30
Appendix A: Policy Dates A-1
Appendix B: Regression Output B-1
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