Association of state-level prescription drug monitoring program implementation with opioid prescribing transitions in primary care in Australia.

AIMS: This study aimed to evaluate whether voluntary and mandatory prescription drug monitoring program (PDMP) use in Victoria, Australia, had an impact on prescribing behaviour, focusing on individual patients' prescribed opioid doses and transition to prescribing of nonmonitored medications. METHODS: This was a retrospective cross-sectional study using routinely collected primary healthcare data. A 90-day moving average prescribed opioid dose in oral morphine equivalents was used to estimate opioid dosage. A Markov transition matrix was used to describe how patients prescribed medications transitioned between opioid dose groups and other nonopioid treatment options during 3 transition periods: transition between 2 control periods prior to PDMP implementation (T1 to T2); during the voluntary PDMP implementation (T2 to T3); and during mandatory PDMP implementation (T3 to T4). RESULTS: Among patients prescribed opioids in our study, we noted an increased probability of transitioning to not being prescribed opioids during the mandatory PDMP period (T3 to T4). This increase was attributed mainly to the ceasing of low-dose opioid prescribing. Membership in an opioid dose group remained relatively stable for most patients who were prescribed high opioid doses. For those who were only prescribed nonmonitored medications initially, the probability of being prescribed opioids increased during the mandatory PDMP when compared to other transition periods. CONCLUSION: The introduction of PDMP mandates appeared to have an impact on the prescribing for patients who were prescribed low-dose opioids, while its impact on individuals prescribed higher opioid doses was comparatively limited.

Implementation of Electronic Health Record Integration and Clinical Decision Support to Improve Emergency Department Prescription Drug Monitoring Program Use.

STUDY OBJECTIVE(S): To evaluate the implementation of 3 electronic health record (EHR)-based interventions to increase prescription drug monitoring program (PDMP) use in the emergency department (ED): EHR-PDMP integration, addition of a PDMP risk score, and addition of EHR-based clinical decision support alert to review the PDMP when prescribing an opioid. METHODS: Three intervention stages were implemented using a prospective stepped-wedge design at 5 university-affiliated EDs split into 3 practice groups. The PDMP use and prescribing rates during the 3 stages were compared with baseline before EHR integration and a sustainability stage where the clinical decision support alert was removed, but EHR integration and risk score remained. Generalized linear mixed model with logit link function and a random intercept for clinicians was analyzed. RESULTS: The ED provider PDMP review before opioid prescribing was low in all stages. The highest review rate occurred during interruptive clinical decision support alerts, 23.8% (interquartile range 10.6 to 37.5). Overall, opioid prescribing declined, and PDMP review was not associated with a decrease in opioid prescribing. PDMP review was associated with a reduction in the probability of prescribing an opioid as the number of prior opioid prescriptions increased (odds ratio: 0.92 [95% confidence interval: 0.91 to 0.94] for every additional prescription). CONCLUSION: The EHR-PDMP integration did not increase PDMP use in the ED, but a PDMP risk score and a clinical decision support alert were associated with modest increases in the probability of PDMP review. When the PDMP is reviewed, ED clinicians are less likely to prescribe opioids to patients with a high number of prior opioid prescriptions.

Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program.

BACKGROUND: To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential. OBJECTIVES: To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high-risk opioid use and outlier behaviors. RESEARCH DESIGN: We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3-digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program. MEASURES: We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program. RESULTS: Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program. CONCLUSIONS: PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage.

Changes in opioid prescribing and prescription drug monitoring program utilization following electronic health record integration-Massachusetts, 2018.

OBJECTIVE: In this study, we explored key prescription drug monitoring program-related outcomes among clinicians from a broad cohort of Massachusetts healthcare facilities following prescription drug monitoring program (PDMP) and electronic health record (EHR) data integration. METHODS: Outcomes included seven-day rolling averages of opioids prescribed, morphine milligram equivalents (MMEs) prescribed, and PDMP queries. We employed a longitudinal study design to analyze PDMP data over a 15-month study period which allowed for six and a half months of pre- and post-integration observations surrounding a two-month integration period. We used longitudinal mixed effects models to examine the effect of EHR integration on each of the key outcomes. RESULTS: Following EHR integration, PDMP queries increased both through the web-based portal and in total (0.037, [95% CI = 0.017, 0.057] and 0.056, [95% CI = 0.035, 0.077]). Both measures of clinician opioid prescribing declined throughout the study period; however, no significant effect following EHR integration was observed. These results were consistent when our analysis was applied to a subset consisting only of continuous PDMP users. CONCLUSIONS: Our results support EHR integration contributing to PDMP utilization by clinicians but do not support changes in opioid prescribing behavior.

Prescription drug monitoring programs and prescription pain medication misuse among U.S. high school students-2019.

BACKGROUND: Prescription drug monitoring programs (PDMPs) are state-level databases that track and inform prescribing practices to reduce prescription drug diversion and misuse. To our knowledge, only three studies have examined the impact of PDMPs on opioid-related outcomes among adolescents, and none have focused on prescription pain medication misuse among adolescents. METHODS: This study leveraged data from the 2019 National Youth Risk Behavior Survey (YRBS) to explore the associations between five categories of PDMP dimensions and the prevalence of self-reported prescription pain medication misuse. Demographic factors' associations with self-reported prescription pain medication misuse were also examined. RESULTS: In 2019, none of the PDMP dimensions were associated with self-reported prescription pain medication misuse among U.S. high school students, adjusting for gender, grade, race/ethnicity, and sexual orientation. CONCLUSIONS: None of the five PDMP dimensions were associated with lower prescription pain medication misuse, however further research is needed, especially as new YRBS data become available.

National Estimates and Physician-Reported Impacts of Prescription Drug Monitoring Program Use.

BACKGROUND: Despite widespread adoption of state prescription drug monitoring programs (PDMPs), it is unclear how often PDMPs are accessed through an electronic health record system (EHR-PDMP integration), or whether efforts to make PDMPs easier to access and use have improved their utility. OBJECTIVE: To produce national-level estimates on the use of PDMPs among office-based physicians and benefits associated with their use. DESIGN: We use nationally representative survey data to produce descriptive statistics on PDMP use and associated benefits among office-based physicians in the USA. PARTICIPANTS: 1398 office-based physicians who prescribe controlled substances. MAIN MEASURES: We examined physician-reported ease and frequency of PDMP use, and how EHR-PDMP integration affects frequency and ease of use. Multivariate models were used to assess whether characteristics of PDMP use were related to physician-reported benefits such as reduced prescribing of controlled substances and perceived improvements in clinical decision-making. KEY RESULTS: In 2019, two-thirds of office-based physicians in the USA reported frequent use of their state PDMP and over three-quarters reported they were easy to use. Both frequency and ease of use were positively correlated with PDMP integration status. Respondents who frequently checked their state's PDMP were 8.7 percentage points (95% CI -.4 to 17.8) more likely to report perceived benefits and reported 2.2 (95% CI 1.54 to 2.83) more benefits. Respondents who indicated their PDMP was easy to use were 12.7 percentage points (95% CI .040 to .214) more likely to report perceived benefits and reported 0.94 (95% CI 0.26 to 1.61) more benefits. CONCLUSIONS: Our findings suggest efforts to make PDMPs easier to access and use aided physicians in making informed clinical decisions that may not be captured by reduced prescribing alone. Efforts to further increase frequency and ease of use-including advancing a standards-based approach to PDMP and EHR data interoperability-may further increase the benefit of PDMPs.

Association of Prescription Drug Monitoring Programs With Opioid Prescribing and Overdose in Adolescents and Young Adults.

STUDY OBJECTIVE: Prescription opioid use is associated with substance-related adverse outcomes among adolescents and young adults through a pathway of prescribing, diversion and misuse, and addiction and overdose. Assessing the effect of current prescription drug monitoring programs (PDMPs) on opioid prescribing and overdoses will further inform strategies to reduce opioid-related harms. METHODS: We performed interrupted time series analyses to measure the association between state-level implementation of PDMPs with annual opioid prescribing and opioid-related overdoses in adolescents (13 to 18 years) and young adults (19 to 25 years) between 2008 and 2019. We focused on PDMPs that included mandatory reviews by providers. Data were obtained from a commercial insurance company. RESULTS: Among 9,344,504 adolescents and young adults, 1,405,382 (15.0%) had a dispensed opioid prescription, and 6,262 (0.1%) received treatment for an opioid-related overdose. Mandated PDMP review was associated with a 4.2% (95% CI, 1.9% to 6.4%) reduction in annual opioid dispensations among adolescents and a 7.8% (95% CI, 4.7% to 10.9%) annual reduction among young adults. For opioid-related overdoses, mandated PDMP review was associated with a 16.1% (95% CI, 3.8 to 26.7) and 15.9% (95% CI, 7.6 to 23.4) reduction in annual opioid overdoses for adolescents and young adults, respectively. CONCLUSION: PDMPs were associated with sustained reductions in opioid prescribing and overdoses in adolescents and young adults. Although these findings support the value of mandated PDMPs as part of ongoing strategies to reduce opioid overdoses, further studies with prospective study designs are needed to characterize the effect of these programs fully.

Systematic Identification and Categorization of Opioid Prescribing and Dispensing Policies in 16 States and Washington, DC.

OBJECTIVES: State policies can impact opioid prescribing or dispensing. Some state opioid policies have been widely examined in empirical studies, including prescription drug monitoring programs and pain clinic licensure requirements. Other relevant policies might exist that have received limited attention. Our objective was to identify and categorize a wide range of state policies that could affect opioid prescribing/dispensing. METHODS: We used stratified random sampling to select 16 states and Washington, DC, for our sample. We collected state regulations and statutes effective during 2020 from each jurisdiction, using search terms related to opioids, pain management, and prescribing/dispensing. We then conducted qualitative template analysis of the data to identify and categorize policy categories. RESULTS: We identified three dimensions of opioid prescribing/dispensing laws: the prescribing/dispensing rule, its applicability, and its disciplinary consequences. Policy categories of prescribing/dispensing rules included clinic licensure, staff credentials, evaluating the appropriateness of opioids, limiting the initiation of opioids, preventing the diversion or misuse of opioids, and enhancing patient safety. Policy categories related to applicability of the law included the pain type, substance type, practitioner, setting, payer, and prescribing situation. The disciplinary consequences dimension included specific consequences and inspection processes. DISCUSSION: Policy categories within each dimension of opioid prescribing/dispensing laws could become a foundation for creating variables to support empirical analyses of policy effects, improving operationalization of policies in empirical studies, and helping to disentangle the effects of multiple state laws enacted at similar times to address the opioid crisis. Several of the policy categories we identified have been underexplored in previous empirical studies.

Prescription drug monitoring programs use mandates and prescription stimulant and depressant quantities.

BACKGROUND: While the mandate to check patients' prescription history in Prescription Drug Monitoring Program (PDMP) database before prescribing/dispensing controlled drugs has been shown to be an important tool to curb opioid abuse, less is known about whether the mandate can reduce the misuse of other commonly abused prescription drugs. We examined whether PDMP use mandates were associated with changes in prescription stimulant and depressant quantities. METHODS: Using data from Automated Reports and Consolidate Ordering System (ARCOS), we employed difference-in-differences design to estimate the association between PDMP use mandates and prescription stimulant and depressant quantities in 50 U.S. states and the District of Columbia from 2006 to 2020. Limited PDMP use mandate was specific only to opioids or benzodiazepines. Expansive PDMP use mandate was non-specific to opioid or benzodiazepine and required prescribers/dispensers to check PDMP when prescribing/dispensing targeted controlled substances in Schedule II-V. The main outcomes were population-adjusted prescription stimulant (amphetamine, methylphenidate, lisdexamfetamine) and depressant (amobarbital, butalbital, pentobarbital, secobarbital) quantities in grams. RESULTS: There was no evidence that limited PDMP use mandate was associated with a reduction in the prescription stimulant and depressant quantities. However, expansive PDMP use mandate that was non-specific to opioid or benzodiazepine and required prescribers/dispensers to check PDMP when prescribing/dispensing targeted controlled substances in Schedule II-V was associated with 6.2% (95% CI: -10.06%, -2.08%) decline in prescription amphetamine quantity. CONCLUSION: Expansive PDMP use mandate was associated with a decline in prescription amphetamine quantity. Limited PDMP use mandate did not appear to change prescription stimulant and depressant quantities.

The prescription drug monitoring program in a multifactorial approach to the opioid crisis: PDMP data, Pennsylvania, 2016-2020.

BACKGROUND: Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state prescription drug monitoring programs (PDMPs), aim to reduce opioid morbidity and mortality through enhanced tracking and reporting of prescription data. The primary objective of our study was to describe the opioid prescribing trends in the state of Pennsylvania (PA) as recorded by the PA PDMP following legislative changes in reporting guidelines, and discuss the PDMP's role in a multifactorial approach to opioid harm reduction. METHODS: State-level opioid prescription data summaries recorded by the PA PDMP for each calendar quarter from August 2016 through March 2020 were collected from the PA Department of Health. Data for oxycodone, hydrocodone, and morphine were analyzed by quarter for total prescription numbers and refills. Prescription lengths, pill quantities, and average morphine milliequivalents (MMEs) were analyzed by quarter for all 14 opioid prescription variants recorded by the PA PDMP. Linear regression was conducted for each group of variables to identify significant differences in prescribing trends. RESULTS: For total prescriptions dispensed, the number of oxycodone, hydrocodone, and morphine prescriptions decreased by 34.4, 44.6, and 22.3% respectively (p < 0.0001). Refills fluctuated less consistently with general peaks in Q3 of 2017 and Q3 of 2018 (p = 0.2878). The rate of prescribing for all opioid prescription lengths decreased, ranging in frequency from 22 to 30 days (47.5% of prescriptions) to 31+ days of opioids (0.8% of prescriptions) (p < 0.0001). Similarly, decreased prescribing was observed for all prescription amounts, ranging in frequency from 22 to 60 pills (36.6% of prescriptions) to 60-90 pills (14.2% of prescriptions) (p < 0.0001). Overall, the average MME per opioid prescription decreased by 18.9%. CONCLUSIONS: Per the PA PDMP database, opioid prescribing has decreased significantly in PA from 2016 to 2020. The PDMP database is an important tool for tracking opioid prescribing trends in PA, and PDMPs structured similarly in other states may enhance our ability to understand and influence the trajectory of the U.S. opioid crisis. Further research is needed to determine optimal PDMP policies and practices nationwide.

Effects of State Opioid Prescribing Laws on Use of Opioid and Other Pain Treatments Among Commercially Insured U.S. Adults.

BACKGROUND: There is concern that state laws to curb opioid prescribing may adversely affect patients with chronic noncancer pain, but the laws' effects are unclear because of challenges in disentangling multiple laws implemented around the same time. OBJECTIVE: To study the association between state opioid prescribing cap laws, pill mill laws, and mandatory prescription drug monitoring program query or enrollment laws and trends in opioid and guideline-concordant nonopioid pain treatment among commercially insured adults, including a subgroup with chronic noncancer pain conditions. DESIGN: Thirteen treatment states that implemented a single law of interest in a 4-year period and unique groups of control states for each treatment state were identified. Augmented synthetic control analyses were used to estimate the association between each state law and outcomes. SETTING: United States, 2008 to 2019. PATIENTS: 7 694 514 commercially insured adults aged 18 years or older, including 1 976 355 diagnosed with arthritis, low back pain, headache, fibromyalgia, and/or neuropathic pain. MEASUREMENTS: Proportion of patients receiving any opioid prescription or guideline-concordant nonopioid pain treatment per month, and mean days' supply and morphine milligram equivalents (MME) of prescribed opioids per day, per patient, per month. RESULTS: Laws were associated with small-in-magnitude and non-statistically significant changes in outcomes, although CIs around some estimates were wide. For adults overall and those with chronic noncancer pain, the 13 state laws were each associated with a change of less than 1 percentage point in the proportion of patients receiving any opioid prescription and a change of less than 2 percentage points in the proportion receiving any guideline-concordant nonopioid treatment, per month. The laws were associated with a change of less than 1 in days' supply of opioid prescriptions and a change of less than 4 in average monthly MME per day per patient prescribed opioids. LIMITATIONS: Results may not be generalizable to non-commercially insured populations and were imprecise for some estimates. Use of claims data precluded assessment of the clinical appropriateness of pain treatments. CONCLUSION: This study did not identify changes in opioid prescribing or nonopioid pain treatment attributable to state laws. PRIMARY FUNDING SOURCE: National Institute on Drug Abuse.

Perspectives of opioid prescribers in overdose hotspots and coldspots, Massachusetts, 2019.

BACKGROUND: Prescription opioids (POs) have had a devastating effect on people and public health systems in the U.S. Due to the urgency and complexity of the opioid crisis, there is a need to expand qualitative research on the medical community's perspectives on opioid prescribing practices and the role that prescription drug monitoring programs (PDMPs) have played in mitigating this crisis. METHODS: We conducted qualitative interviews with clinicians (n = 23) across specialties and a range of overdose hotspot and coldspot locations in Massachusetts during 2019. We aimed to capture their perspectives on the opioid crisis, changes in clinical practice, and experiences with opioid prescribing and PDMPs. RESULTS: Respondents consistently recognized the role clinicians played in the opioid crisis and reported reductions in their opioid prescribing, which were motivated by the crisis itself. The limitations of opioids in pain management were frequently discussed. While clinicians appreciated having greater awareness of their opioid prescribing and increased access to patient prescription histories, they also expressed concerns about surveillance of their prescribing and other unintended consequences. We observed that clinicians in opioid prescribing hotspots had more detailed and specific reflections on their experiences with the Massachusetts PDMP, MassPAT. CONCLUSION: Clinician perceptions of the severity of the opioid crisis in Massachusetts and thoughts on their role as prescribers were consistent across specialty, prescribing level, and practice location. Many clinicians in our sample cited use of the PDMP as an influence on their prescribing. Those practicing in opioid overdose hotspots had the most nuanced reflections about the system.

Benzodiazepine Dose Intensity among Patients Concurrently Prescribed Buprenorphine in Rhode Island.

Background: The concomitant use of buprenorphine and benzodiazepines has been linked to patient fatalities, with greater risk occurring with higher doses of benzodiazepines. We assessed benzodiazepine dose intensity among patients who were concurrently prescribed buprenorphine, as compared with patients prescribed benzodiazepines who were not receiving buprenorphine. Methods: We conducted a cross-sectional analysis of adult patients who received at least a 30-day supply of benzodiazepines during 2018, using data from the Rhode Island (RI) Prescription Drug Monitoring Program. Mean daily diazepam milligram equivalents (DME) were calculated overall and according to patient sex, age group, payment type, and RI county. Multivariable logistic regression analyses were conducted to assess the odds of higher-dose benzodiazepine utilization among patients with concurrent use of buprenorphine, as compared with patients not prescribed buprenorphine, adjusting for patient demographics. Results: Compared to patients prescribed benzodiazepines who were not receiving buprenorphine, those with concurrent buprenorphine utilization had a significantly higher mean DME/day (19.22, 95% CI: 18.70-19.74; vs 10.94, 95% CI: 10.93-10.95; p < 0.001). Patients who were prescribed benzodiazepines with concurrent utilization of buprenorphine also had a comparatively higher odds of a DME/day ≥15 (aOR: 2.86, 95% CI: 2.63-3.10), ≥20 DME/day (aOR: 2.98, 95% CI: 2.75-3.24), and ≥25 DME/day (aOR: 2.99, 95% CI: 2.65-3.18). Conclusion: Compared to patients prescribed benzodiazepines for at least 30 days who were not receiving buprenorphine, patients concurrently utilizing benzodiazepines and buprenorphine had more than twice the odds of higher dose benzodiazepine utilization. Future studies are needed to assess the relationship between benzodiazepine dose intensity, overdose outcomes, and treatment retention among patients receiving buprenorphine.

Evaluating the temporal association between the recency of prescribed controlled substance acquisition and fatal and non-fatal opioid overdose.

BACKGROUND: Previous studies have explored psychosocial effects as possible triggers of opioid overdose (OOD). However, little is known about the temporal association between OOD and prescribed controlled substance (CS) acquisition. OBJECTIVE: The objective of this study was to evaluate the temporal relationship between OOD and acquiring prescribed CSs prior to OOD. METHODS: This study is an exploratory descriptive analysis using Arkansas Prescription Drug Monitoring Program (AR-PDMP) data linked to death certificate and statewide inpatient discharge records. All persons with ≥1 AR-PDMP prescription fill(s) between 1 January 2014 and 31 December 2017 were included (n = 1,946,686). For persons that experienced OOD and had ≥1 PDMP record(s), the difference in days between OOD and the most recent AR-PDMP prescription filled prior to an OOD was recorded. To account for censoring, a sensitivity analysis was conducted restricting the study group to "New AR-PDMP Entrants" that had at least a 180-day gap between consecutive AR-PDMP fill dates. RESULTS: 28,998,307 AR-PDMP records were analyzed for 1,946,686 individuals. 7195 persons experienced 9223 OODs and 414 (4.49%) of those were fatal. Of these, 6236 experienced ≥1 OOD and acquired prescribed CSs prior to or on the day of the first OOD. Of those that experienced ≥1 OOD(s), 2201 (30.59%) had an AR-PDMP record in the 0- to 5-day period prior to their overdose and 497 (6.91%) had an AR-PDMP record the day prior to their overdose. Among New AR-PDMP Entrants that experienced ≥1 OOD(s), 408 (27.38%) had an AR-PDMP record in the 0- to 5-day period prior to their overdose. CONCLUSION: Though the vast majority of persons accessing CSs in Arkansas did not experience an OOD, a sizable proportion of persons that experience an OOD(s) obtained prescribed CSs immediately prior.

Barriers to Increasing Prescription Drug Monitoring Program Use: A Multidisciplinary Perspective.

Prescription drug monitoring programs are implemented through individual state policies and are one solution to curb the opioid crisis. The objectives of this study are to: (1) describe the multidisciplinary experiences using this program in practice; (2) identify limitations of the program and the desired features for improvement; and (3) characterize expectations for improved access when prescription drug monitoring programs are embedded in the electronic health record. A qualitative descriptive study design used semistructured interviews of 15 multidisciplinary healthcare providers. Textual data were analyzed using content analysis. Results showed the prescription drug monitoring program was helpful to decision-making processes related to opioid prescribing and referral to treatment; there were barriers limiting healthcare providers' use of the prescription drug monitoring program; preferences were delineated for integrating prescription drug monitoring program into electronic health record; and recommendations were provided to improve the program and increase use. In conclusion, the prescription drug monitoring program was viewed as useful in making strides to reduce the impact of inappropriate opioid prescribing in our country. By engaging a multidisciplinary group of healthcare providers, solutions were offered to improve the interface and function of the prescription drug monitoring program to assist in increasing use.

Enhancing and Leveraging the West Virginia's Prescription Drug Monitoring Program (PDMP) for Public Health Surveillance and Clinical Decision Making: A Case Study.

West Virginia has struggled with an overdose epidemic for many years and continues to have the highest overdose death rate in the nation. However, through successful collaboration between the West Virginia Board of Pharmacy and the West Virginia Department of Health via its Violence and Injury Prevention Program, West Virginia has improved data quality, enhanced program development and implementation, and developed strategies to address the overdose epidemic. This multiagency collaboration plays an important role in addressing the overdose epidemic and promotes lasting interagency relationships. One strategy is overcoming barriers to maximizing and utilizing the Prescription Drug Monitoring Program, or PDMP. This strategy allows for a better understanding of a patient's prescription history and ensures safer prescribing practices. In addition, this strategic partnership facilitates the use of PDMP data for epidemiologic studies and public health surveillance, which results in sustainable analyses and dissemination of actionable data that are now driving public health action in West Virginia.

Prescription Drug Monitoring and Child Maltreatment in the United States, 2004-2018.

OBJECTIVE: To test whether a policy approach aimed at decreasing prescription drug misuse, specifically, state monitoring of controlled substance prescriptions-prescription drug monitoring programs (PDMPs)-were associated with changes in Child Protective Services-reported maltreatment prevalence. STUDY DESIGN: Using a difference-in-differences design and maltreatment data (2004-2018) from 50 states and the District of Columbia, we compared the prevalence of total maltreatment incidents and total victims, in states with and without PDMPs, before and after implementation. Exploratory analyses further examined models disaggregated by maltreatment type (neglect, physical abuse, sexual abuse, psychological abuse) and among different racial/ethnic groups. Quasi-Poisson models included state-level covariates, state- and year-fixed effects, and cluster-robust standard errors. RESULTS: Difference-in-differences models identified greater relative reductions in PDMP states relative to controls (total prevalence ratio, 0.87; 95% CI, 0.80, 0.940; victimization prevalence ratio, 0.92; 95% CI, 0.85-0.98) over the observation period. Decreases seemed to be driven by changes in neglect (prevalence ratio, 0.87; 95% CI, 0.80-0.93) and physical abuse (prevalence ratio, 0.78; 95% CI, 0.71-0.87) incidents, and may have been especially salient for American Indian/Alaskan Native children (prevalence ratio, 0.78; 95% CI, 0.65-0.94). CONCLUSIONS: We found evidence supporting an association between prescription drug monitoring and reduced maltreatment prevalence at the state level. Policies aimed at restricting the prescribing and dispensing of controlled substances may have indirect implications for child welfare.

Association of State-Imposed Restrictions on Gabapentin with Changes in Prescribing in Medicare.

BACKGROUND: Between August 2016 and July 2018, three states classified gabapentin as a Schedule V drug and nine states implemented prescription drug monitoring program (PDMP) regulation for gabapentin. It is highly unusual for states to take drug regulation into their own hands. The impact of these changes on gabapentin prescribing is unclear. OBJECTIVE: To determine the effect of state-imposed regulation on gabapentin prescribing for Medicare Part D enrollees from 2013 to 2018. DESIGN: Population-based difference-in-difference(DID) analysis study utilizing the Medicare Part D Prescriber Public Use File. PARTICIPANTS: All eligible Medicare Part D prescribers excluding those outside of the fifty states and the District of Columbia were included in our analysis. Prescriber data and key sociodemographic variables were organized by state and year. States with a gabapentin schedule change or PDMP regulation enacted before 2019 were included in the intervention group. For the Schedule V DID analysis, a control group of the ten highest opioid-prescribing states was used. INTERVENTIONS: States with gabapentin schedule changes or PDMP regulation before January 1, 2019, were included and compared to control states that did not implement these policies. MAIN MEASURES: Total days' supply of gabapentin per enrollee per year was the primary outcome variable. KEY RESULTS: The mean total days' supply of gabapentin per enrollee increased 41% from 19.71 to 27.81 total days' supply per enrollee per year between 2013 and 2018. After adjustment, Schedule V gabapentin regulation resulted in a reduction of 8.37 total days of gabapentin prescribed per enrollee (95% confidence interval of - 10.34 to - 6.39). In contrast, PDMP regulation resulted in a reduction of 1.01 total days of gabapentin prescribed per enrollee (95% confidence interval of - 1.74 to - 0.29). CONCLUSIONS: Classifying gabapentin as a Schedule V drug results in substantial reduction in total days prescribed whereas PDMP regulation results in modest reduction.

Cycles of Chronic Opioid Therapy Following Mandatory Prescription Drug Monitoring Program Legislation: A Retrospective Cohort Study.

BACKGROUND: Mandates for prescriber use of prescription drug monitoring programs (PDMPs), databases tracking controlled substance prescriptions, are associated with reduced opioid analgesic (OA) prescribing but may contribute to care discontinuity and chronic opioid therapy (COT) cycling, or multiple initiations and terminations. OBJECTIVE: To estimate risks of COT cycling in New York City (NYC) due to the New York State (NYS) PDMP mandate, compared to risks in neighboring New Jersey (NJ) counties. DESIGN: We estimated cycling risk using Prentice, Williams, and Peterson gap-time models adjusted for age, sex, OA dose, payment type, and county population density, using a life-table difference-in-differences design. Failure time was duration between cycles. In a subgroup analysis, we estimated risk among patients receiving high-dose prescriptions. Sensitivity analyses tested robustness to cycle volume considering only first cycles using Cox proportional hazard models. PARTICIPANTS: The cohort included 7604 patients dispensed 12,695 prescriptions. INTERVENTIONS: The exposure was the August 2013 enactment of the NYS PDMP prescriber use mandate. MAIN MEASURES: We used monthly, patient-level data on OA prescriptions dispensed in NYC and NJ between August 2011 and July 2015. We defined COT as three sequential months of prescriptions, permitting 1-month gaps. We defined recurrence as re-initiation of COT after at least 2 months without prescriptions. The exposure was enactment of the PDMP mandate in NYC; NJ was unexposed. KEY RESULTS: Enactment of the NYS PDMP mandate was associated with an adjusted hazard ratio (HR) for cycling of 1.01 (95% CI, 0.94-1.08) in NYC. For high-dose prescriptions, the risk was 1.16 (95% CI, 1.01-1.34). Sensitivity analyses estimated an overall risk of 1.01 (95% CI, 0.94-1.11) and high-dose risk of 1.09 (95% CI, 0.91-1.31). CONCLUSIONS: The PDMP mandate had no overall effect on COT cycling in NYC but increased cycling risk among patients receiving high-dose opioid prescriptions by 16%, highlighting care discontinuity.