Are Prescription Drug Monitoring Programs Effective? An Analysis of the Impact of Prescription Drug Monitoring Programs (PDMPs) Operational Variation on Prescription Opioid Misuse and Abuse
Loading...
Links to Files
Permanent Link
Author/Creator
Author/Creator ORCID
Date
2020-01-01
Type of Work
Department
School of Public Policy
Program
Public Policy
Citation of Original Publication
Rights
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan through a local library, pending author/copyright holder's permission.
This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
Subjects
Abstract
ABSTRACT Title of dissertations: Are Prescription Drug Monitoring Programs (PDMPs) Effective? An Analysis of the Impact of Prescription Drug Monitoring Programs (PDMPs) Operational Variation on Prescription Opioid Misuse and Abuse Kathy Guggino-Easterling, Doctor of Philosophy, 2021 dissertations directed by: Nancy A. Miller. Ph.D., Professor, Public Policy BackgroundAccording to the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics (NCHS), the third leading cause of accidental death in the U.S. in 2018 was narcotic overdoses. According to Healthcare Cost and Utilization Project (HCUP) data, the rate of opioid-related inpatient stays per 100,000 population in 2017 was 299.7, compared to 189.2 in 2010. The prescription drug abuse epidemic is intricate and multi-faceted. State prescription monitoring programs (PMPs) or prescription drug monitoring programs (PDMPs) have been described as a potentially impactful clinical tool to prevent prescription drug abuse. However, it is important to account for operational variations when studying the effectiveness of PDMPs in order to determine which programs are most successful, to determine best practices, to inform policy decisions and to justify PDMP funding.
Objective
The goal of this research was to determine the extent to which variation in state PDMP operational characteristics affects PDMP effectiveness in decreasing opioid abuse, as measured by state level opioid inpatient discharges. This study also examined whether PDMPs have the unintended consequence of increasing heroin use. Methods
I conducted a state-level analysis with state-level data acquired from publicly available sources, using a cross-sectional time series model with adjustments for state and year fixed effects. Data were analyzed for 23 states with available HCUPnet opioid inpatient discharge data for the period 2001 through 2014. I examined four PDMP characteristics: proactive PDMP, frequency of data reporting requirements, mandatory query and mandatory enrollment. To deal with potential endogeneity, I explored possible instrumental variables. Although the three I tested were weak instruments across most of my analyses, I was able to use an instrumental variable related to the Affordable Care Act state marketplace exchanges to test whether state implementation of a PDMP was endogenous (See Appendix II). Using the Hausman test for endogeneity, I determined that presence of a PDMP was not endogenous (See Appendix III).
Main Findings
Overall, the results do not support the hypothesis that having an operational PDMP, measured simply by the presence of a PDMP, would decrease opioid related discharges. However, statistically significant results were found for states with a more frequent data reporting interval, mandatory enrollment, and, although marginally significant, mandatory query. Both a mandatory enrollment and mandatory query requirement were associated with a reduction in opioid inpatient discharges, while less frequent reporting was associated with an increase in opioid discharges over the study period. Although reduced inpatient discharges could result from fewer admissions, greater inpatient mortality, or both, research finds inpatient mortality for opioid misuse declined between 2001 and 2012 (Douglas et al., 2017), suggesting the discharge reduction is associated with fewer admissions for opioid misuse. Another variable which had a consistent statistically significant effect was a state Naloxone access law; these laws were associated with a decrease of between .029 and .037 inpatient opioid discharges per 1,000 state population over the study time period. I found limited spillover effects of PDMP operational characteristics on poisoning by heroin inpatient discharges. Heroin poisoning frequently happens when a person overdoses on heroin unintentionally. Conclusions/implicationsBased on these findings, more states should explore the implementation of a more frequent data reporting interval, and mandatory enrollment and query requirements. This will promote greater utilization of PDMP systems as a clinical decision support tool. In addition, more states may want to consider adopting naloxone overdose prevention laws. State policymakers should invest funds for research by partners, such as local universities, for ongoing PDMP evaluations to build evidence which can guide policy implementation. In addition, major recent federal opioid laws that include federal funding for PDMPs will be very helpful in advancing PDMPS and increasing PDMP use by providers, Medicaid providers and managed care entities.
?