Prescription Monitoring Program Data Research Articles

Leveraging prescription monitoring program data to evaluate the implementation of buprenorphine telehealth flexibilities: An interrupted time series analysis in Texas

BackgroundIn March 2020, policy changes by the Substance Abuse and Mental Health Services Administration and the Drug Enforcement Administration aimed to maintain access to office-based opioid treatment services by easing telehealth buprenorphine prescribing restrictions. However, the effectiveness of these changes remains largely unmeasured. The objective of this study was to measure the effectiveness of COVID-19-related telehealth flexibilities in an all-payer cohort from the Texas Prescription Monitoring Program. MethodsUsing Texas Prescription Monitoring Program data, we identified oral buprenorphine and buprenorphine/naloxone prescriptions dispensed in Texas between September 1, 2019, and September 26, 2020. Weekly counts of prescriptions, prescribing physicians, and dispensing pharmacies were analyzed. An autoregressive integrated moving average (ARIMA) model estimated changes in prescription volume between pre-implementation (September 1, 2019 - February 15, 2020) and post-implementation (April 12, 2020 - September 26, 2020) periods. ResultsPre-flexibility, an average of 8898 (SD: 342) buprenorphine prescriptions were dispensed to 7829 (SD: 326) patients weekly. This declined to 8360 (SD: 247) prescriptions and 7661 (SD: 229) patients post-flexibility. Adjusted for seasonality, this represented a statistically significant average decline of −257.27 (95% CI: −426.06, −88.49) patients and −647.01 (95% CI: −856.67, −437.36) prescriptions per week. DiscussionOur results suggest a modest decline in buprenorphine dispensing volume early in the COVID-19 pandemic. While difficult to assess its significance, it can be assumed that telehealth flexibilities mitigated a potentially larger decline. Future research should explore system and individual-level barriers to telehealth utilization.

Changes in Prescribed Opioid Dosages Among Patients Receiving Medical Cannabis for Chronic Pain, New York State, 2017-2019

Patients with chronic pain often receive long-term opioid therapy (LOT), which places them at risk of opioid use disorder and overdose. This presents the need for alternative or companion treatments; however, few studies on the association of medical cannabis (MC) with reducing opioid dosages exist. To assess changes in opioid dosages among patients receiving MC for longer duration compared with shorter duration. This cohort study of New York State Prescription Monitoring Program data from 2017 to 2019 included patients receiving MC for chronic pain while also receiving opioid treatment. Of these, patients receiving LOT prior to receiving MC were selected. Individuals were studied for 8 months after starting MC. Data were analyzed from November 2021 to February 2022. Selected patients were divided into 2 groups based on the duration of receiving MC: the nonexposure group received MC for 30 days or fewer, and the exposure group received MC for more than 30 days. The main outcome was opioid dosage, measured by mean daily morphine milligram equivalent (MME). Analyses were conducted for 3 strata by opioid dosage prior to receiving MC: MME less than 50, MME of 50 to less than 90, and MME of 90 or greater. A total of 8165 patients were included, with 4041 (median [IQR] age, 57 [47-65] years; 2376 [58.8%] female) in the exposure group and 4124 (median [IQR] age, 54 (44-62) years; 2370 [57.5%] female) in the nonexposure group. Median (IQR) baseline MMEs for the exposure vs nonexposure groups were 30.0 (20.0-40.0) vs 30.0 (20.0-40.0) in the lowest stratum, 60.0 (60.0-70.0) vs 60.0 (60.0-90.0) in the middle stratum, and 150.0 (100.0-216.2) vs 135.0 (100.0-218.0) in the highest stratum. During follow-up, significantly greater reductions in opioid dosage were observed among the exposure group. A dose-response association of patients' opioid dosage at baseline was observed with the differences in the monthly MME reductions between exposure and nonexposure groups, with a difference of -1.52 (95% CI, -1.67 to -1.37) MME for the lowest stratum, -3.24 (95% CI, -3.61 to -2.87) MME for the middle stratum, and -9.33 (95% CI, -9.89 to -8.77) MME for the highest stratum. The daily MME for the last month of the follow-up period among patients receiving longer MC was reduced by 48% in the lowest stratum, 47% in the middle stratum, and 51% in the highest stratum compared with the baseline dosages. Among individuals in the nonexposure group, daily MME was reduced by only 4% in the lowest stratum, 9% in the middle stratum, and 14% in the highest stratum. In this cohort study of patients receiving LOT, receiving MC for a longer duration was associated with reductions in opioid dosages, which may lower their risk of opioid-related morbidity and mortality.

Opioid Prescriptions to Urban and Rural Patients by Oral-maxillofacial Surgeons: A Review of Massachusetts Prescription Monitoring Program Data 2011-2021

Massachusetts has implemented many policies and initiatives in the last decade to combat the opioid epidemic, which remains a major public health crisis. Oral and maxillofacial surgeons are frequent prescribers of narcotic analgesics to manage postoperative pain. To this end, it remains unclear if analgesic management patterns differ for urban versus rural oral and maxillofacial surgeons, given potential differences in access to and delivery of care. While recent studies have found minimal urban-rural difference in opioid prescriptions to the Medicare population, this has yet to be explored among the general population.

Buprenorphine utilization among all Washington State residents' based upon prescription monitoring program data - Characteristics associated with two measures of retention and patterns of care over time

BackgroundOpioid use disorder is a serious health condition for which buprenorphine is proven effective, yet providers substantially underutilize buprenorphine. We present two approaches to measuring treatment duration, factors associated with retention, and patterns of care. MethodsThe study determined incident buprenorphine prescribing for all Washingtonians utilizing prescription monitoring program data from 2012 to 2019. The study calculated episode of care and cumulative time in care. Generalized linear models estimated associations among the length of the first episode of care and cumulative time in care with sex, age, and rurality. Cox proportional hazards models estimated the time to discontinuing buprenorphine for the first four episodes of care and time to discontinuing the last episode of care. ResultsMean and median duration of the first episode were 320 and 84 days, respectively, and for cumulative time in care 308 and 195 days. A minority of peoples' first episodes exceeded 180 days (37%). Being female and older were significantly associated with longer first episodes and cumulative time in care. Survival analyses indicated that the proportion of those still in care at 6, 12, and 24 months into their first episode of care declined for those with more than one episode of care; conversely the study found much smaller differences in retention for the last episode of care, indicating that many people were eventually able to be retained in care for longer periods of time. ConclusionEpisodes of care and cumulative time on buprenorphine were both short compared to minimum quality recommendations of 180 days. Median cumulative time in care was double that of the first episode, highlighting that many people engage in subsequent episodes of substantial length. Episode of care and cumulative care analyses should inform states, payers, health care systems and providers in measuring and setting treatment duration goals.

Health Care Provider Utilization of Prescription Monitoring Programs: A Systematic Review and Meta-Analysis.

ObjectiveTo synthesize the literature on the proportion of health care providers who access and use prescription monitoring program data in their practice, as well as associated barriers to the use of such data.DesignWe performed a systematic review using a standard systematic review method with meta-analysis and qualitative meta-summary. We included full-published peer-reviewed reports of study data, as well as theses and dissertations.MethodsWe identified relevant quantitative and qualitative studies. We synthesized outcomes related to prescription monitoring program data use (i.e., ever used, frequency of use). We pooled the proportion of health care providers who had ever used prescription monitoring program data by using random effects models, and we used meta-summary methodology to identify prescription monitoring program use barriers.ResultsFifty-three studies were included in our review, all from the United States. Of these, 46 reported on prescription monitoring program use and 32 reported on barriers. The pooled proportion of health care providers who had ever used prescription monitoring program data was 0.57 (95% confidence interval: 0.48–0.66). Common barriers to prescription monitoring program data use included time constraints and administrative burdens, low perceived value of prescription monitoring program data, and problems with prescription monitoring program system usability.ConclusionsOur study found that health care providers underutilize prescription monitoring program data and that many barriers exist to prescription monitoring program data use.

Reformulation of oxycodone 80 mg to prevent misuse: A cohort study assessing the impact of a supply-side intervention

BackgroundIn August 2010, extended-release OxyContin® products, including oxycodone 80 mg, were reformulated and released as abuse-deterrent medications. This paper describes changes in individual prescription filling patterns that followed the reformulation of oxycodone 80 mg. MethodsUsing New York State prescription monitoring program data, we conducted a retrospective analysis of a cohort of New York City residents who had filled at least three consecutive prescriptions for oxycodone 80 mg immediately prior to the reformulation. We classified cohort members into one of three groups (continuers, switchers, and discontinuers) based on prescription filling patterns post-reformulation. Descriptive analyses were conducted to identify prevalence of filling patterns. Differences in median morphine milligram equivalents (MME) pre- and post-reformulation were compared using the Wilcoxon signed-rank sum test. Analyses were completed in 2018. ResultsA cohort of 4,098 New York City residents filled continuous prescriptions for oxycodone 80 mg immediately prior to reformulation. Post-reformulation, 14% of the cohort discontinued filling opioid analgesic prescriptions; 46% continued to fill prescriptions for oxycodone 80 mg; and 40% switched to a different opioid analgesic, most commonly oxycodone 30 mg. Post-reformulation, the median MME dose decreased significantly among all three groups: 45 mg among continuers, 150 mg among switchers, and 360 mg among discontinuers. ConclusionPost-reformulation, more than half the cohort changed their filling patterns. Following reformulation, median MME dose decreased significantly among the cohort. We hypothesize that the dramatic decrease in MME dose prompted many to transition to heroin in order to avoid severe withdrawal.

Association between opioid analgesic therapy and initiation of buprenorphine management: An analysis of prescription drug monitoring program data.

BackgroundIn the US, medication assisted treatment, particularly with office-based buprenorphine, has been an important component of opioid dependence treatment among patients with iatrogenic addiction to opioid analgesics. The predictors of initiating buprenorphine for addiction among opioid analgesic patients have not been well-described.MethodsWe conducted a time-to-event analysis using data from the North Carolina (NC) Prescription Drug Monitoring Program (PDMP). Our outcome of interest was time-to-initiation of sublingual buprenorphine. Our study population was a prospective cohort of all state residents receiving a full-agonist opioid analgesic between 2011 and 2015. Predictors of initiation of sublingual buprenorphine examined included: age, gender, cumulative pharmacies and prescribers utilized, cumulative opioid intensity (defined as cumulative opioid exposure divided by duration of opioid exposure), and benzodiazepine dispensing.FindingsOf 4.3 million patients receiving opioid analgesics in NC between 2011 and 2015 (accumulated 8.30 million person-years of follow-up), and a total of 28,904 patients initiated buprenorphine formulations intended for addiction treatment (overall rate 3.48 per 1,000 person-years). In adjusted multivariate models, the utilization of 3 or more pharmacies (HR: 2.93; 95% CI: 2.82, 3.05) or 6 or more controlled substance prescribers (HR: 12.09; 95% CI: 10.76, 13.57) was associated with buprenorphine initiation. A dose-response relationship was observed for cumulative opioid intensity (HR in highest decile relative to lowest decile: 5.05; 95% CI: 4.70, 5.42). Benzodiazepine dispensing was negatively associated with buprenorphine initiation (HR: 0.63; 95% CI: 0.61, 0.65).ConclusionsOpioid analgesic patients utilizing multiple prescribers or pharmacies are more likely to initiate sublingual buprenorphine. This finding suggests that patients with multiple healthcare interactions are more likely to be treated for high-risk opioid use, or may be more likely to be identified and treated for addiction. Future research should utilize prescription monitoring program data linked to electronic health records to include diagnosis information in analytic models.

Tracking Opioid Prescribing Metrics in Washington State (2012-2017): Differences by County-Level Urban-Rural and Economic Distress Classifications.

High-risk opioid prescribing is a critical driver of prescription opioid-related morbidity and mortality. This study explored opioid prescribing patterns across urban-rural and economic distress classifications. Secondarily, this study explored the urban-rural distribution of relevant health services, economic factors, and population characteristics. County-level opioid prescribing metrics were based on quarterly Washington State Prescription Monitoring Program data (2012-2017). Counties were classified using the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties, and Washington State unemployment-based distressed areas. County-level measures from Area Health Resources Files were used to describe the urban-rural continuum. Persistent economic distress was associated with higher-risk opioid prescribing. The large central metropolitan category had lower-risk opioid prescribing metrics than the other 5 urban-rural categories, which were similar to each other and not ordered by degree of rurality. High-risk prescribing declined over time, without notable trend divergence by either urban-rural or economic distress classifications. The most striking urban-rural differences in opioid prescribing metrics were between large central metropolitan and all other categories; thus, we recommend caution when collapsing urban-rural categories for analysis. Further research is needed regarding geographic and economic patterning of opioid prescribing practices, as well as the dissemination of guidelines and best practices across the urban-rural continuum. Finally, the multiple intertwined burdens faced by rural communities-higher-risk prescribing practices, higher opioid morbidity and mortality rates, and fewer resources for primary care, mental health care, alternative pain treatment, and opioid use disorder treatment-must be addressed as an urgent public health priority.

Opioid and Benzodiazepine Use Before Injury Among Workers in Washington State, 2012 to 2015.

To characterize pre-injury prescription opioid and benzodiazepine use and its relationship with post-injury use and missed work among workers. Three hundred thirteen thousand five hundred forty three Washington State Department of Labor and Industries workers' compensation injury claims from 2012 to 2015 were linked with State Prescription Monitoring Program data. Pre-injury prevalence of opioid and benzodiazepine use were compared between compensable and non-compensable claims, and between workers with and without post-injury prescriptions, using the Pearson's chi-squared test. The prevalence of opioid or benzodiazepine use in the 90 days before injury was 8.6% and 2.9%, respectively. Workers with pre-injury opioid or benzodiazepine use were more likely to have compensable claims and be on opioids or benzodiazepines, respectively, after injury. Cases with chronic opioid use pre-injury nearly universally receive opioids post-injury. Pre-injury opioid and benzodiazepine use may increase the risk of disability after work-related injury.

The prescription monitoring program data: What it can tell you

The prescription monitoring program data: What it can tell you

Using prescription monitoring program data to characterize out-of-pocket payments for opioid prescriptions in a state Medicaid program.

Out-of-pocket payment for prescription opioids is believed to be an indicator of abuse or diversion, but few studies describe its epidemiology. Prescription drug monitoring programs (PDMPs) collect controlled substance prescription fill data regardless of payment source and thus can be used to study this phenomenon. To estimate the frequency and characteristics of prescription fills for opioids that are likely paid out-of-pocket by individuals in the Oregon Medicaid program. Cross-sectional analysis using Oregon Medicaid administrative claims and PDMP data (2012 to 2013). Continuously enrolled nondually eligible Medicaid beneficiaries who could be linked to the PDMP with two opioid fills covered by Oregon Medicaid. Patient characteristics and fill characteristics for opioid fills that lacked a Medicaid pharmacy claim. Fill characteristics included opioid name, type, and association with indicators of high-risk opioid use. A total of 33592 Medicaid beneficiaries filled a total of 555103 opioid prescriptions. Of these opioid fills, 74953 (13.5%) could not be matched to a Medicaid claim. Hydromorphone (30%), fentanyl (18%), and methadone (15%) were the most likely to lack a matching claim. The 3 largest predictors for missing claims were opioid fills that overlapped with other opioids (adjusted odds ratio [aOR] 1.37; 95% confidence interval [CI], 1.34-1.4), long-acting opioids (aOR 1.52; 95% CI, 1.47-1.57), and fills at multiple pharmacies (aOR 1.45; 95% CI, 1.39-1.52). Prescription opioid fills that were likely paid out-of-pocket were common and associated with several known indicators of high-risk opioid use.

Using Health Information Exchange to Improve Use of Prescription Monitoring Data

ObjectiveDemonstrate that use of the Washington State health informationexchange (HIE) to facilitate access to prescription monitoringprogram (PMP) data enhances the effectiveness of a PMP. Theincreased accessibility will lead to improved patient care by givingproviders more complete and recent data on patients’ controlledsubstance prescriptions.IntroductionWashington State experienced a five-fold increase in deaths fromunintentional drug overdoses between 1998 and 2014. The PMPcollects data on controlled substances prescribed to patients andmakes the data available to healthcare providers, giving providersanother tool for patient care and safety. Optimal impact for theprogram depends on providers regularly accessing the information toreview patients’ dispensing history. We have found through providersurveys and work with stakeholders that the best way to increase useis to make data seamlessly accessible through electronic health recordsystems (EHRs). This approach does not require a separate login tothe PMP portal. This linkage works through the Health InformationExchange (HIE) to make PMP data available to providers via EHRs.The HIE facilitates electronic communication of patient informationamong organizations including hospitals and providers. In additionto the PMP, another resource to address the prescription drug abuseproblem is the Emergency Department Information Exchange(EDIE), a web-based technology that specifically connects emergencydepartments statewide to track patients who visit multiple EDs.We also developed a connection between EDIE and PMP datathrough the HIE.MethodsIncreased provider utilization of the PMP will be achieved byusing the HIE to create more seamless access to PMP data throughproviders’ EHRs and through the EDIE system. This will be done bycompleting the build out of a transaction using NCPCP 10.6, pilotingthe connection with healthcare systems and EHR vendors, and bycontinuing to promote and encourage the PMP to remain an MUoption through recent rule changes being proposed by CMS/ONC.The pilot with Epic was conducted in 2015 from April to October.Epic has released an update, available to Washington customers, thatincludes the connection between EHR and PMP. PMP data is alsoconnected to EDIE. That connection is now live in 80 of 93 acute carehospital emergency departments.ResultsTo date the transaction is in production with 80 emergencydepartments and achieving positive results. In 2015 the PMP receivedmore than 2 million queries from the EDIE system via the HIE,compared to 900,000 queries via the online PMP portal in the yearbefore the link through the HIE was available. We have also finisheda pilot with a major EHR vendor and are working to on-board theircustomers. We are also working directly with healthcare systems, andas of September 2016 there are 3 healthcare facilities in testing thatare expected to go live by the end of the year. Over 90 registrationsfor meaningful use of the PMP have been received, representing morethan 1000 clinics. Improved access to PMP data benefits providers byallowing them to check the history of transactions linked to their DEAnumbers, which can alert them to fraudulent prescriptions.ConclusionsIntegration of PMP data with other information systems will greatlyenhance the accessibility and impact of the data. Making a connectionto EDIE alone more than doubled the number of queries we receivedfrom providers in 2015. We anticipate even more inquiries onceadditional care settings are connected. We hope from this to see acontinued decline in unintentional poisonings due to prescriptiondrugs.

The law of unintended consequences: illicit for licit narcotic substitution.

The law of unintended consequences: illicit for licit narcotic substitution.

Prescribers and Pharmacists Requests for Prescription Monitoring Program (PMP) Data: Does PMP Structure Matter?

ABSTRACTPrescription monitoring programs (PMPs) have been purported to be an effective tool to combat prescription drug abuse. However, utilization rates of PMP data by health care providers (e.g., prescribers and pharmacists) is relatively low. The objectives of the study were to describe (1) PMP utilization (e.g., requested reports) by prescribers, pharmacists, and law enforcement for active state PMPs; (2) PMP utilization by health care providers with and without online access; (3) average annual operational costs for PMPs from 2008 to 2009; and (4) PMP requests based on PMP housing authority (law enforcement vs. non-law enforcement [e.g., board of pharmacy]). This was a cross-sectional study employing a Web-based survey. A 16-item questionnaire was e-mailed to the 33 operational state PMP administrators and responses were collected from January to March 2011. Descriptive statistics were used to describe PMP request rates and annual operating costs. The usable survey response rate was 45.5%. Among all authorized users, prescribers had higher mean (±SD) requests per 100,000 population (2198.2 ± 3218.0) compared with pharmacists’ requests (268.9 ± 261.2). Online accessibility resulted in higher request rates per 100,000 population (2996.4 ± 3021.5) compared with mail/fax access (14.6 ± 2.8). On average, PMP annual costs were $12,515 ± $14,911 per 100,000 population. In law enforcement–governed PMPs, health care provider utilization was lower compared with PMPs under health or pharmacy boards. Prescriber request rates were higher than pharmacists and online access for providers (e.g., prescribers and pharmacists) resulted in higher request rates per 100,000 population. More research is needed to determine other factors that may be associated with PMP utilization by prescribers and pharmacists.