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Purpose: To develop a complete and consistent prescription drug monitoring program (PDMP) data set for use by drug safety researchers in evaluating patterns of high-risk use and potential abuse of scheduled drugs., Methods: Using publically available data references from the US Food and Drug Administration and the Centers for Disease Control and Prevention, we developed a strategic methodology to assign drug categories based on pharmaceutical class for the majority of prescriptions in the PDMP data set. We augmented data elements required to calculate morphine milligram equivalents and assigned duration of action (short-acting or long acting) properties for a majority of opioids in the data set., Results: About 10% of prescriptions in the PDMP data set did not have a vendor-assigned drug category, and 20% of opioid prescriptions were missing data needed to calculate risk metrics. Using inclusive methods, 19 133 167 (>99.9%) of prescriptions in the PDMP data set were assigned a drug category. For the opioid category, augmenting data elements resulted in 10 760 669 (99.8%) having required values to calculate morphine milligram equivalents and evaluate duration of action properties., Conclusions: Drug safety researchers who require a complete and consistent PDMP data set can use the methods described here to ensure that prescriptions of interest are assigned consistent drug categories and complete opioid risk variable values. Copyright © 2016 John Wiley & Sons, Ltd., Competing Interests: and Conflicts of Interest: None of the authors have conflicts of interest to declare., (Copyright © 2016 John Wiley & Sons, Ltd.)

Objectives: Prescription drug monitoring programs (PDMPs) are state-based data collection systems recording controlled substance medications. Currently, 49 states have PDMPs. There are discrepancies in reporting patterns, infrastructure, and oversight between programs. We characterized aspects of each state's PDMP., Methods: A web search of each state's PDMP was conducted, and a list of all PDMP administrators was obtained. From August 1 to November 31, 2014, a link to a web-based survey was sent to each PDMP administrator. Closed-ended questions included type of access, mandatory-use programs, data sharing, proactive contact with patients or health care providers, details of pharmacy reporting, and protocols for identifying "high-risk" patients. Descriptive statistics were used for analysis., Results: We received a 100% response rate (49/49). Ninety-six percent (47/49) have a physician-accessible PDMP. Most, 68% (32/49), do not have an enrollment mandate for physicians. Prior to prescribing controlled medications, 16% (8/49) require prescribers to access their state's PDMP. More than half of states (53%, 26/49) reported patient prescriptions over the past two or more years. Most, 57% (28/59), reported a lag time of 1 week or longer for patients to appear in a PDMP database after prescription filling. A majority of states (65% 32/49) share data with at least one other state. Protocols exist to identify high-risk patients for prescription drug misuse in 55% (27/49) of states., Conclusion: Characteristics of PDMPs are heterogeneous throughout the country. Standardizing data capture, availability, and reporting would improve their usefulness for providers. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Background: Prescription drug abuse is a serious health concern and is considered a nationwide epidemic. Patients often fail or refuse to disclose the use of controlled substances, leaving prescribers and pharmacies unaware of the potential for harmful drug interactions and risk of overdose. Psychiatric patients are especially vulnerable to controlled substance misuse., Objectives: To determine hazardous patterns of prescription drug use among psychiatric outpatients and to raise awareness about the importance of reviewing information provided by prescription drug monitoring programs (PDMPs)., Methods: The medical records of 150 patients attending the Adult Outpatient Psychiatric Clinic at the Los Angeles County+University of Southern California (LAC+USC) Medical Center from July 2012 through May 2013 were reviewed. Patient activity reports were generated from California's PDMP. Nondisclosure of controlled substance use was identified by a discrepancy between patient reporting of prescriptions according to the medical records and PDMP reports. A "pattern suggestive of prescription drug abuse" was defined as having one or more of the following: within-class prescriptions from multiple providers and/or within-class early refills or within-class overlapping prescriptions picked up within 10 days of each other., Results: Of the 150 patients, 113 were found in California's PDMP database. Of these 113 patients, 81 had obtained 111 prescriptions for controlled substances in the past 12 months. Of these 111 prescriptions, 52 (47%) were not disclosed to the primary psychiatrist, of which 14 (27%) revealed patterns consistent with prescription drug abuse., Conclusions: Reviewing PDMP databases before prescribing controlled substances should be considered a standard prescribing practice to prevent abuse, diversion, and adverse medical outcomes.

Since the late 1990s, the number of opioid analgesic overdose deaths has quadrupled in the United States of America (from 4 030 deaths in 1999 to 16 651 in 2010). The objectives of this article are to provide an overview of the problem of prescription drug overdose in the United States and to discuss actions that could help reduce the problem, with particular attention to the characteristics of prescription drug monitoring programs (PDMPs). These programs consist of state-level databases that monitor controlled substances. The information compiled in the databases is at the disposal of authorized persons (e.g., physicians, pharmacists, and other health-care providers) and may be used only for professional purposes. Suppliers can use such information to prevent interaction with other drugs or therapeutic duplication, or to identify drug-search behavior. Law enforcement agencies can use these programs to identify improper drug prescription or dispensing patterns, or drug diversion.

Nonmedical use of prescription medications--particularly controlled substances--has risen dramatically in recent decades, resulting in alarming increases in overdose-related health care utilization, costs, and mortality. The Centers for Disease Control and Prevention estimate that 80% of abused and misused controlled substances originate as legal prescriptions. As such, policymakers and payers have the opportunity to combat nonmedical use by regulating controlled substance accessibility within legal prescribing and dispensing processes. One common policy strategy is found in Medicaid controlled substance lock-in programs. Lock-in programs identify Medicaid beneficiaries exhibiting high-risk controlled substance seeking behavior and "lock in" these patients to, typically, a single prescriber and pharmacy from which they may obtain Medicaid-covered controlled substance prescriptions. Lock-in restrictions are intended to improve care coordination between providers, reduce nonmedical use behaviors, and limit Medicaid costs stemming from nonmedical use and diversion. Peer-reviewed and gray literature have been examined to assess the current prevalence and design of Medicaid lock-in programs, as well as the current evidence base for informing appropriate program design and understanding program effectiveness. Forty-six state Medicaid agencies currently operate lock-in programs. Program design varies widely between states in terms of defining high-risk controlled substance use, the scope of actual lock-in restrictions, and length of program enrollment. Additionally, there is a remarkable dearth of peer-reviewed literature evaluating the design and effectiveness of Medicaid lock-in programs. Nearly all outcomes evidence stemmed from publicly accessible internal Medicaid program evaluations, which largely investigated cost savings to the state. Lock-in programs are highly prevalent and poised to play a meaningful role in curbing the prescription drug abuse epidemic. However, achieving these ends requires a concerted effort from the academic and policy communities to rigorously evaluate the effect of lock-in programs on patient outcomes, determine optimal program design, and explore opportunities to enhance lock-in program impact through coordination with parallel controlled substance policy efforts, namely prescription drug-monitoring programs.

Background: Prescription drug abuse has prompted considerable concern. We evaluated a retrospective drug utilization review program to reduce controlled substance use among individuals with high-risk utilization., Methods: We analyzed pharmacy claims from a large pharmaceutical benefits manager. For each eligible member, we calculated a controlled substance score based on the number and type of claims, prescribers and pharmacies, and utilization patterns over three months. Two state health plans sent controlled substance letters to prescribers of members meeting or exceeding a plan- and pre-specified controlled substance score. Two different state health plans did not send such letters. We used a difference-in-difference design and generalized estimating equations to quantify the impact of the program on the mean difference in reduction of the controlled substance score over six months., Results: Eligible members in the intervention and comparison states had similar baseline mean controlled substance scores (19.0 vs. 18.6, p = 0.36). Adjusting for individuals' age, sex and pharmacy risk group score, reductions in the mean controlled substance score were greater in the intervention than comparison cohort (5.67 vs. 4.31, p = 0.01), corresponding with a 34.0% reduction in the intervention cohort compared to a 25.5% reduction in the comparison cohort. Changes were driven primarily by reductions in the number of controlled substance claims filled (30.5% vs. 23.1%, p = 0.01), as well as by a non-statistically significant trend towards reductions in the number of prescribers and pharmacies used (26.9% vs. 20.1%, p = 0.07)., Conclusions: Retrospective drug utilization review programs may reduce controlled substance scores and claims among individuals with patterns suggesting high-risk utilization., (Copyright © 2013 John Wiley & Sons, Ltd.)

This article provides an overview on prescription drug abuse and highlights a number of related legislative bills introduced during the 112th Congress in response to this growing epidemic. Prescription drug abuse has emerged as the nation's fastest growing drug problem. Although prescription drugs have been used effectively and appropriately for decades, deaths from prescription pain medicine in particular have reached epidemic proportions. Bills related to prescription drug abuse introduced during the 112th Congress focus on strengthening provider and consumer education, tracking and monitoring prescription drug abuse, improving data collection on drug overdose fatalities, combating fraud and abuse in Medicare and Medicaid programs, reclassifying drugs to make them more difficult to prescribe and obtain, and enforcing stricter penalties for individuals who operate scam pain clinics and sell pain pills illegitimately. This article underscores the importance of a multifaceted approach to combating prescription drug abuse and concludes with implications for nursing., (Copyright © 2013. Published by Mosby, Inc.)