Prescription Drug Monitoring Program Data Research Articles

Predictors of postoperative opioid use in ventral and incisional hernia repair.

One in two ventral and incisional hernia repair (VIHR) patients have preoperative opioid prescription within a year before procedure. The study's aim was to investigate risk factors of increased postoperative prescription filling in patients with or without preoperative opioid prescription. VIHR cases from 2013 to 2017 were reviewed. State prescription drug monitoring program data were linked to patient records. The primary endpoint was cumulative opioid dose dispensed through post-discharge day 45. Morphine milligram equivalent (MME) was used for uniform comparison. 205 patients were included in the study (average age 53.5years; 50.7% female). Over 35% met criteria for preoperative opioid use. Preoperative opioid tolerance, superficial wound infection, current smoking status, and any dispensed opioids within 45days of admission were independent predictors for increased postoperative opioid utilization (p < 0.001). Preoperative opioid use during 45-day pre-admission correlated strongly with postoperative prescription filling in VIHR patients, and several independent risk factors were identified.

Effect of integration of prescription drug monitoring program data in the electronic health record on queries by primary care providers.

Objective: To evaluate the impact of PDMP integration in the EHR on provider query rates within twelve primary care clinics in one academic medical center. Methods: Using linked data from the EHR and state PDMP program, we evaluated changes in PDMP query rates using a stepped-wedge observational design where integration was implemented in three waves (four clinics per wave) over a five-month period (May, July, September 2019). Multivariable negative binomial general estimating equations (GEE) models assessed changes in PDMP query rates, overall and across several provider and clinic-level subgroups. Results: Among 206 providers in PDMP integrated clinics, the average number of queries per provider per month increased significantly from 1.43 (95% CI 1.07 - 1.91) pre-integration to 3.94 (95% CI 2.96 - 5.24) post-integration, a 2.74-fold increase (95% CI 2.11 to 3.59; p < .0001). Those in the lowest quartile of PDMP use pre-integration increased 36.8-fold (95% CI 16.91 - 79.95) after integration, significantly more than other pre-integration PDMP use quartiles. Conclusions: Integration of the PDMP in the EHR significantly increased the use of the PDMP overall and across all studied subgroups. PDMP use increased to a greater degree among providers with lower PDMP use pre-integration.

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

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. 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. 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. Our results support EHR integration contributing to PDMP utilization by clinicians but do not support changes in opioid prescribing behavior.

Real-World Dispensing of Buprenorphine in California during Prepandemic and Pandemic Periods.

The opioid overdose crisis in the United States has become a significant national emergency. Buprenorphine, a primary medication for individuals coping with opioid use disorder (OUD), presents promising pharmacokinetic properties for use in primary care settings, and is often delivered as a take-home therapy. The COVID-19 pandemic exacerbated the scarcity of access to buprenorphine, leading to dire consequences for those with OUD. Most existing studies, primarily focused on the immediate aftermath of the COVID-19 outbreak, highlight the challenges in accessing medications for opioid use disorder (MOUDs), particularly buprenorphine. However, these studies only cover a relatively short timeframe. To bridge this research gap, in our study, we utilized 33 months of California's prescription drug monitoring program (PDMP) data to provide insights into real-world buprenorphine dispensing trends since the onset of the pandemic from 2018 to 2021, focusing on outcomes such as patient counts, prescription volumes, prescriber involvement, days' supply, and dosage. Statistical analysis employed interrupted time series analysis to measure changes in trends before and during the pandemic. We found no significant impact on patient counts or prescription volumes during the pandemic, although it impeded the upward trajectory of prescriber numbers that was evident prior to the onset of the pandemic. An immediate increase in days' supply per prescription was observed post-pandemic. Our findings differ in comparison to previous data regarding the raw monthly count of patients and prescriptions. The analysis encompassed uninsured patients, offering a comprehensive perspective on buprenorphine prescribing in California. Our study's insights contribute to understanding the impact of COVID-19 on buprenorphine access, emphasizing the need for policy adjustments.

Prescription drug monitoring program use by opioid prescribers: a cross-sectional study.

Clinician use of prescription drug monitoring programs (PDMPs) has been linked to better patient outcomes, but state requirements to use PDMPs are unevenly enforced. We assessed PDMP use in Minnesota, which requires opioid prescribers to hold accounts and, in most cases, search the PDMP before prescribing, but where enforcement authority is limited. Using 2023 PDMP data, we found that 4 in 10 opioid prescribers did not search and 2 in 10 did not hold an account. PDMP use was strongly associated with prescribing volume, but even among the top decile of opioid prescribers, 8% never searched the PDMP. Thirty-two percent of opioid fills came from clinicians who did not search the PDMP. Failures to use the PDMP may be driven by a lack of information about state requirements, beliefs that these requirements are not enforced, and the costs of accessing the PDMP relative to the benefits. These results highlight the potential for policy makers to promote safer and better-informed prescribing of opioids and other drugs by addressing the forces that have limited PDMP use so far.

Opioid and benzodiazepine utilization patterns in metropolitan and rural Texas.

Although many drugs are implicated in the crisis, opioids and concomitant sedatives are associated with increased overdose risk in both rural and urban communities. Individuals in rural areas are up to 5-fold more likely to experience adverse outcomes related to opioids. The primary objective of this study was to evaluate concomitant use of opioid and benzodiazepine prescriptions in Texas, compare metropolitan and rural differences, and use these data to inform clinicians and to help develop harm reduction strategies. Prescribing data were extracted from the Texas Prescription Drug Monitoring Program (PDMP) public use data file, the statewide monitoring program administered by the Texas State Board of Pharmacy. An overlapping drug combination prescription day was defined as any day in which a patient had at least one of the overlapping drug types-eg, opioid + benzodiazepine, opioid + benzodiazepine + carisoprodol. In Texas, 47.4 percent of the counties with the highest number of overlapping days (per patient) bordered other states. Providers who practice in rural areas prescribe opioid and benzodiazepine medications with 8.2 more overlapping days per quarter. Taking both opioid and benzodiazepine prescriptions is associated with increased overdose risk. Opioid prescription data provide a distinct view into the opioid epidemic that allows all states and counties to view the trends of opioid utilization. There are only a few studies using PDMP data to compare urban and rural trends. Rural patients had more benzodiazepine and opioid days overlap than urban patients. The prevalence is higher among older adults and providers who practice in rural areas (average 8.2 more days per quarter). Our findings in Texas indicate a trend downward in overlap for both rural and urban areas over the last year of measurement. However, rural areas are still significantly higher.

Buprenorphine Dose and Time to Discontinuation Among Patients With Opioid Use Disorder in the Era of Fentanyl.

Buprenorphine treatment for opioid use disorder (OUD) has more than doubled since 2009. However, current US Food and Drug Administration buprenorphine dosing guidelines are based on studies among people using heroin, prior to the emergence of fentanyl in the illicit drug supply. To estimate the association between buprenorphine dose and time to treatment discontinuation during a period of widespread fentanyl availability. This retrospective cohort study used statewide Rhode Island Prescription Drug Monitoring Program data. Participants were Rhode Island residents initiating buprenorphine treatment for OUD between October 1, 2016, and September 30, 2020. Data analysis was performed from December 9, 2022, to August 10, 2023. Daily dose of buprenorphine (16 mg and 24 mg) defined starting on the day of initiation based on total quantity and days' supply dispensed. Patients were censored on any dose change. Buprenorphine treatment discontinuation in the 180 days following initiation, defined as a gap in treatment of more than 27 days based on prescription fill dates and days' supply. Kaplan-Meier and Cox regression survival analyses were conducted to estimate the association between buprenorphine dose and time to treatment discontinuation, controlling for potential informative censoring and measured potential confounders. Among 6499 patients initiating buprenorphine treatment for OUD, most were aged 25 to 44 years (57%; n = 3682), were male (61%; n = 3950), and had private (47%; n = 3025) or Medicaid (33%; n = 2153) insurance. More than half of patients were prescribed a daily dose of interest at initiation (16 mg: 50%; n = 3264; 24 mg: 10%; n = 668). In Kaplan-Meier analyses, 58% of patients discontinued buprenorphine treatment within 180 days (16 mg: 59% vs 24 mg: 53%; log-rank test P = .005). In Cox regression analyses, patients prescribed a dose of 16 mg had a greater risk of treatment discontinuation than those prescribed 24 mg (adjusted hazard ratio, 1.20; 95% CI, 1.06-1.37). In this cohort study of patients initiating buprenorphine treatment from 2016 to 2020, patients prescribed a 24 mg dose of buprenorphine remained in treatment longer than those prescribed 16 mg. The value of higher buprenorphine doses than currently recommended needs to be considered for improving retention in treatment.

Drugs involved in Kentucky drug poisoning deaths and relation with antecedent controlled substance prescription dispensing

BackgroundThe shift from prescription to illicit drugs involved in drug poisoning deaths raises questions about the current utility of prescription drug monitoring program (PDMP) data to inform drug poisoning (overdose) prevention efforts. In this study, we describe relations between specific drugs involved in Kentucky drug poisoning deaths and antecedent controlled substance (CS) dispensing.MethodsThe study used linked death certificates and PDMP data for 2,248 Kentucky resident drug poisoning deaths in 2021. Death certificate literal text analysis identified drugs mentioned with involvement (DMI) in drug poisoning deaths. We characterized the concordance between each DMI and the CS dispensing history for this drug at varying timepoints since 2008.ResultsOverall, 25.5% of all decedents had dispensed CS in the month before fatal drug poisoning. Over 80% of decedents were dispensed opioid(s) since 2008; the percentage was similar regardless of opioid involvement in the poisoning death. One-third of decedents had dispensed buprenorphine for treatment of opioid use disorder since 2008, but only 6.1% had dispensed buprenorphine in the month preceding death. Fentanyl/fentanyl analogs were DMI in 1,568 (69.8%) deaths, yet only 3% had received a fentanyl prescription since 2008. The highest concordance in the month preceding death was observed for clonazepam (43.6%).ConclusionOverall, concordance between CS dispensing history and the drugs involved in poisoning deaths was low, suggesting a need to reevaluate the complex relationships between prescription medication exposure and overdose death and to expand harm reduction interventions both within and outside the healthcare system to reduce drug poisoning mortality.

Impact of Statewide Statute Limiting Days’ Supply to Opioid-Naive Patients

To address the ongoing opioid crisis, states use policy enactment to restrict prescribing by licensed healthcare providers and mandate the use of Prescription Drug Monitoring Programs. There have been mixed results regarding the effectiveness of such state policies. The purpose of this study is to evaluate the impact of Colorado Senate Bill 18-022, which limits opioid prescriptions to ≤7-day supply among patients without an opioid prescription in the previous year (i.e., are opioid naive). This is a retrospective interrupted time-series analysis of opioid prescribing to evaluate the weekly percentage of opioid prescriptions consistent with statutory limits for ≤7-day supply among opioid-naive patients before and after enactment using Prescription Drug Monitoring Programs data from May 21, 2017 to May 25, 2019. Statistical analysis was performed in 2021-2022. The weekly percentage of opioid prescriptions ≤7-day supply increased by an average of 0.12% per week (p<0.0001) from 79.7% to 87.4% in the week before enactment. The week after enactment, the average increased by 0.2% (p=0.67). The year after enactment, the average weekly percentage change was 0.07% per week, a 0.05% decrease (p=0.01). Statutory limits on days' supply among opioid-naive patients had little impact on opioid prescribing in Colorado. Legislating limits on opioid prescribing should be evaluated using Prescription Drug Monitoring Program data and considered for deimplementation when not impactful.

Health-care practitioner use of prescription drug monitoring programs in clinical practice in Australia: A qualitative study.

Prescription drug monitoring programs (PDMP) are electronic databases used by prescribers and pharmacists to monitor the use of high-risk prescription medications subject to extramedical use. This study aimed to explore how Australian pharmacists and prescribers are using PDMPs in practice and to gain an understanding of barriers to tool use, as well as practitioner recommendations to increase tool usability and uptake. Semi-structured interviews were conducted with pharmacists and prescribers who use a PDMP (n = 21). The interviews were audio-recorded, transcribed and thematically analysed. The four themes that emerged were: (i) PDMP notifications combined with practitioner clinical judgement guide PDMP usability; (ii) practitioners use PDMPs to facilitate patient and practitioner communication; (iii) workflow systems integration impacts tool usability; and (iv) optimising PDMP information and data access including practitioner-tool engagement to improve tool uptake and usability. Practitioners appreciate the value of PDMP information support for clinical decisions and patient communication. However, they also acknowledge the challenges to tool use and recommend improvements including enhanced workflow, systems integration, optimisation of tool information and national data sharing. Practitioners provide an important perspective on PDMP use in clinical practice. The findings can be drawn on by PDMP administrators to improve tool usefulness. Consequently, this may lead to an increase in practitioner PDMP use and optimise the delivery of quality patient care.

Supporting Evidence-Based Care Through Informatics Innovation to Address the Overdose Epidemic.

Supporting Evidence-Based Care Through Informatics Innovation to Address the Overdose Epidemic.

Detecting Anomalous Networks of Opioid Prescribers and Dispensers in Prescription Drug Data

The opioid overdose epidemic represents a serious public health crisis, with fatality rates rising considerably over the past several years. To help address the abuse of prescription opioids, state governments collect data on dispensed prescriptions, yet the use of these data is typically limited to manual searches. In this paper, we propose a novel graph-based framework for detecting anomalous opioid prescribing patterns in state Prescription Drug Monitoring Program (PDMP) data, which could aid governments in deterring opioid diversion and abuse. Specifically, we seek to identify connected networks of opioid prescribers and dispensers who engage in high-risk and possibly illicit activity. We develop and apply a novel extension of the Non-Parametric Heterogeneous Graph Scan (NPHGS) to two years of de-identified PDMP data from the state of Kansas, and find that NPHGS identifies subgraphs that are significantly more anomalous than those detected by other graph-based methods. NPHGS also reveals clusters of potentially illicit activity, which may strengthen state law enforcement and regulatory capabilities. Our paper is the first to demonstrate how prescription data can systematically identify anomalous opioid prescribers and dispensers, as well as illustrating the efficacy of a network-based approach. Additionally, our technical extensions to NPHGS offer both improved flexibility and graph density reduction, enabling the framework to be replicated across jurisdictions and extended to other problem domains.

High-risk Prescribing Following Surgery Among Payer Types for Patients on Chronic Opioids.

Among those on chronic opioids, to determine whether patients with Medicaid coverage have higher rates of high-risk opioid prescribing following surgery compared with patients on private insurance. Following surgery, patients on chronic opioids experience gaps in transitions of care back to their usual opioid prescriber, but differences by payer type are not well understood. This study aimed to analyze how new high-risk opioid prescribing following surgery compares between Medicaid and private insurance. In this retrospective cohort study through the Michigan Surgical Quality Collaborative, perioperative data from 70 hospitals across Michigan were linked to prescription drug monitoring program data. Patients with either Medicaid or private insurance were compared. The outcome of interest was new high-risk prescribing, defined as a new occurrence of: overlapping opioids or benzodiazepines, multiple prescribers, high daily doses, or long-acting opioids. Data were analyzed using multivariable regressions and a Cox regression model for return to usual prescriber. Among 1435 patients, 23.6% (95% CI: 20.3%-26.8%) with Medicaid and 22.7% (95% CI: 19.8%-25.6%) with private insurance experienced new, postoperative high-risk prescribing. New multiple prescribers was the greatest contributing factor for both payer types. Medicaid insurance was not associated with higher odds of high-risk prescribing (odds ratio: 1.067, 95% CI: 0.813-1.402). Among patients on chronic opioids, new high-risk prescribing following surgery was high across payer types. This highlights the need for future policies to curb high-risk prescribing patterns, particularly in vulnerable populations that are at risk of greater morbidity and mortality.

Ethics of Prescription Drug Monitoring Programs

Ethics of Prescription Drug Monitoring Programs

Impact of unsolicited reporting notifications on providers’ prescribing behavior: An experimental study on Maryland PDMP data

BackgroundUnsolicited Reporting Notifications(URNs) have been a component of Maryland’s Prescription Drug Monitoring Program (PDMP) since 2016. We evaluated the effect of URNs on providers’ prescription behaviors. MethodsThis is a quasi-experimental study of providers who were issued at least one URN from January 2018 to April 2021. Providers for whom URNs were not successfully delivered were designated as a comparison group. The outcome variables were average daily opioid and benzodiazepine prescriptions, average morphine milligram equivalents per patient, and proportion of overlapping opioid and benzodiazepine, either with or without muscle relaxant prescriptions. Changes were compared before versus after the issuance of a URN among the intervention and comparison groups using “Generalized Estimation Equation” and “Generalized Linear” Models. We also conducted stratified analyses by types of URN, including notifications for multiple provider episodes (MPE), overdose fatality (ODF), and dangerous drug combinations (DDC). ResultsThe average daily number of opioids prescriptions (3.3% decrease in the intervention group vs 22.7% increase in the comparison group, P<0.001), co-prescription of opioids and benzodiazepines either with muscle relaxants (68.0% decrease vs. 36.1% decrease, P<0.001), or without muscle relaxants (6.0% decrease vs. 16.3% increase, P<0.001), significantly reduced after the first URN regardless of the type of URN. Stratified analysis by types of URNs showed that ODF and DDC URNs had a significant effect on most of the outcomes of interest. ConclusionThe findings suggest that unsolicited reporting, especially particular types of URNs including ODF and DDC, is associated with subsequent changes in unsafe prescribing behaviors.

Mapping prescription drug monitoring program data to self-report measures of non-medical prescription opioid use in community pharmacy settings

BackgroundCommunity pharmacists are well-positioned to identify patients engaged in non-medical prescription opioid use (NMPOU) through Prescription Drug Monitoring Program (PDMP) databases. Integrating patient-reported outcomes with PDMP data may improve the interpretability of PDMP information to support clinical decision-making. ObjectiveThis study linked patient-reported clinical measures of substance use with PDMP data to examine relationships between average daily opioid dose in morphine milligram equivalents (MME) and visits to multiple pharmacies/prescribers with self-reported NMPOU. MethodsData from a cross-sectional health assessment given to patients aged ≥18 years filling opioid prescriptions were linked to PDMP records. NMPOU in the past three months was assessed on a continuous scale (range 0–39) using an adapted version of the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST). PDMP measures included average daily MME and number of distinct pharmacies/prescribers visited in the past 180 days. Univariable and multivariable zero-inflated negative binomial models estimated associations between PDMP measures and any NMPOU and severity of use. ResultsThe sample included 1421 participants. In multivariable models adjusted for sociodemographic, mental health, and physical health characteristics, any NMPOU was associated with higher average daily MME (adjusted OR = 1.22, 95% CI = 1.05–1.39) and number of distinct prescribers visited (adjusted OR = 1.15, 95% CI = 1.01–1.30). Higher average daily MME (adjusted mean ratio (MR) = 1.12, 95% CI = 1.08–1.15), number of distinct pharmacies visited (adjusted MR = 1.11, 95% CI = 1.04–1.18), and number of distinct prescribers visited (adjusted MR = 1.07, 95% CI = 1.02–1.11) were associated with increased NMPOU severity. ConclusionsWe observed significant, positive associations between average daily MME and visits to multiple pharmacies/prescribers with any NMPOU and severity of use. This study demonstrates self-report clinical measures of substance use can be cross-walked to PDMP data and translated into clinically interpretable information.

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

BackgroundPrescription 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.MethodsState-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.ResultsFor 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%.ConclusionsPer 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.

Development and validation of an overdose risk prediction tool using prescription drug monitoring program data

ObjectivesTo develop and validate a machine-learning algorithm to predict fatal overdose using Pennsylvania Prescription Drug Monitoring Program (PDMP) data. MethodsThe training/testing (n = 3020,748) and validation (n = 2237,701) cohorts included Pennsylvania residents with a prescription dispensing from February 2018-September 2021. Potential predictors (n = 222) were measured in the 6 months prior to a random index date. Using a gradient boosting machine, we developed a 20-variable model to predict risk of fatal drug overdose in the 6 months after the index date. ResultsBeneficiaries in the training (n = 1,812,448), testing (n = 1,208,300), and validation (n = 2,237,701) samples had similar age, with low rates of fatal overdose during 6-month follow up (0.12%, 0.12%, 0.04%, respectively). The validation c-statistic was 0.86 for predicting fatal overdose using 20 PDMP variables. When ranking individuals based on risk score, the prediction model more accurately identified fatal overdose at 6 months compared to using opioid dosage or opioid/benzodiazepine overlap, although the percentage of individuals in the highest risk percentile who died at 6 months was less than 1%. Conclusions and policy implicationsA gradient boosting machine algorithm predicting fatal overdose derived from twenty variables performed well in discriminating risk across testing and validation samples, improving on single factor risk measures like opioid dosage

Dental opioid prescription patterns in academic and community settings.

Reports of interventions to improve dental opioid prescribing have come primarily from academic settings, but most opioid prescriptions are written by community dentists. This analysis compares prescription characteristics between these two groups to inform interventions to improve dental opioid prescribing in community settings. State prescription drug monitoring program data from 2013 to 2020 were used to compare opioid prescriptions from dentists at academic institutions (PDAI) to prescriptions from dentists in non-academic settings (PDNS). Linear regression was used to assess daily morphine milligram equivalents (MME), total MME, and days' supply, adjusting for year, age, sex, and rurality. Prescriptions from dentists at the academic institution accounted for less than 2% of over 2.3 million dental opioid prescriptions analyzed. Over 80% of prescriptions in both groups were written for <50 MME per day and for ≤3 days' supply. On average, in the adjusted models, prescriptions from the academic institution were written for about 75 additional MME per prescription and nearly a full day longer duration. Compared to adults, adolescents were the only age group who received both higher daily doses and longer days' supply. Prescriptions from dentists at academic institutions accounted for small percentage of opioid prescriptions, but prescription characteristics were clinically comparable between groups. Interventional targets to reduce opioid prescribing in academic institutions could be applied to community settings.

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

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. The objective of this study was to evaluate the temporal relationship between OOD and acquiring prescribed CSs prior to OOD. 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. 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. 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.