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.

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

INTRODUCTION: 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). METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

Discrepancies Between the Electronic Medical Record and Website Access to the Prescription Drug Monitoring Program.

The US opioid crisis has affected many patients across the age spectrum. Yet little has been reported on the effects of this crisis on cancer patients. Prescription drug monitoring programs have emerged as potential tools to mitigate risks of opioid prescribing, but they are not without limitations. We present a case of missing opioid prescriptions on EMR integrated PDMP versus the web based PDMP. A full review of PDMP integration is needed to identify gaps as these pose a significant patient safety issue.

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.

Association between prescription drug monitoring programs use mandates and prescription stimulants received by Medicaid enrollees.

INTRODUCTION: Prescription drug monitoring program (PDMP) use mandates are an important policy tool to curb nonmedical opioid use. However, data are scarce about their efficacy on other commonly used prescription drugs such as stimulants. METHODS: We used 2010-2020 state-level secondary data from Medicaid State Drug Utilisation Data and quasi-experimental difference-in-differences research design to estimate the association between PDMP use mandates and population-adjusted stimulants (amphetamines and methylphenidate) prescribing outcomes: (i) number of prescriptions filled; and (ii) total amount reimbursed in US dollars. To account for heterogeneity in mandates across US states, two policy variables were considered: limited and expansive. Limited PDMP use mandates require prescribers or dispensers to check the PDMP only when prescribing/dispensing opioids or benzodiazepines, while expansive PDMP use mandates are non-specific to opioids/benzodiazepines and require prescribers or dispensers to check the PDMP when prescribing/dispensing targeted controlled substances in Drug Enforcement Agency Schedule II-V. The sample included 49 US states and the District of Columbia. Nevada was excluded since it implemented the PDMP mandate before the period of analysis. RESULTS: The state-wide implementation of the PDMP use mandate, either limited or expansive, was not associated with the number of prescriptions filled or the total amount reimbursed in US dollars for stimulants among Medicaid enrollees. DISCUSSION AND CONCLUSION: There was no evidence for the associations between PDMP use mandates and stimulant prescribing among Medicaid enrollees. Future works are encouraged to replicate the study in other populations and with longer post-period analysis when the impact of the mandates might be more successfully materialised.

Changes in opioid agonist treatment initiation among people prescribed opioids for pain following voluntary and mandatory prescription drug monitoring program implementation: A time series analysis.

INTRODUCTION: Prescription drug monitoring programs (PDMP) are increasingly used to identify people prescribed high-dose opioids. However, little is known about whether PDMPs impact opioid agonist treatment (OAT) uptake, the gold standard for opioid use disorder. This study examined the impact of PDMP implementation on OAT initiation among people prescribed opioids, in Victoria, Australia. METHODS: De-identified electronic records from all 464 Victorian general practices included in the POLAR database were used. OAT initiation was defined as a new OAT prescription between 1 April 2017 and 31 December 2020, with no OAT prescriptions in the year prior. Interrupted time series analyses were used to compare outcomes before (April 2017 to March 2019) and after (April 2019 to December 2020) PDMP implementation. Binary logistic regression was used to examine differences in patients' characteristics associated with OAT initiation prior to and after PDMP implementation. RESULTS: In total, 1610 people initiated OAT, 946 before and 664 after PDMP implementation. No significant immediate (step) or longer-term (slope) changes in the rates of OAT initiation were identified following PDMP implementation, after adjusting for seasonality. A high opioid dose (>100 mg oral morphine equivalent) in the 6-months prior to OAT initiation was the only significant characteristic associated with reduced odds of OAT initiation post-PDMP implementation (odds ratio 0.29; 0.23-0.37). DISCUSSION AND CONCLUSIONS: PDMP implementation did not have a significant impact on OAT initiation among people prescribed opioids. Findings suggest additional clinical initiatives that support OAT initiation are required to ensure PDMPs meet their intended target of reducing opioid-related harms.

Barriers and facilitators related to healthcare practitioner use of real time prescription monitoring tools in Australia.

Introduction: Real time prescription monitoring tools have been implemented in Australia to address the growing concerns of drug misuse, drug-related mortality and morbidity. The objective of this pilot study is to investigate the barriers and facilitators related to healthcare practitioner use of real time prescription monitoring tools. Methods: An online survey was distributed to Australian prescribers and pharmacists who use a real time prescription monitoring tool. Data analysis included descriptive statistics, chi-square tests and multivariate logistic regression analyses. Results: A total of 102 questionnaires were analyzed. Practitioners mainly agreed that the tool was easy to use (n = 64; 66.7%) and access (n = 56; 57.7%), and the data was easy to interpret (n = 77; 79.4%). Over half agreed that they wanted training to guide clinical actions (n = 52; 55.9%) and clinical guidelines or guidance on what to do with the RTPM findings (n = 51; 54.8%). Prescribers were more likely to report difficulties with workplace access to a computer or the internet (n = 7; 21.2%) compared with pharmacists (n = 6; 9.2%; p = 0.037). Practitioners working in community settings (n = 59; 57.9%; p = 0.022) and those with 1-10 years practice experience (n = 45; 44.2%; p = 0.036) were more likely to want training to guide clinical actions in response to RTPM information. Conclusion: This is the first known study to investigate the barriers and facilitators related to practitioner use of RTPM tools in Australia. The results from this study can inform further research to gain an understanding of healthcare practitioners use of RTPM tools, and how to minimize barriers and optimize use for the essential delivery of quality healthcare.

Introduction of QScript real-time prescription monitoring system was associated with a fall in pregabalin poisoning presentations to a clinical toxicology unit.

OBJECTIVE: To investigate the impact of QScript implementation on pregabalin-related poisoning presentations to the ED. METHODS: This is a retrospective review of pregabalin-related poisoning presentations to a tertiary Australian ED in the 4 years prior to, and 1 year following the introduction of QScript real-time prescription monitoring system. RESULTS: Pregabalin-related poisoning presentations fell by 28% from an average of 98 presentations annually over the 4 years prior to QScript implementation to 71 in 2022. The severity of poisonings was similar over the periods. CONCLUSIONS: The introduction of QScript was associated with a reduction in pregabalin-related poisoning presentations.

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.

Trends in Initiate Pediatric Opioid Prescriptions in Rhode Island: 2017-2021.

OBJECTIVE: To analyze recent trends in initiate pediatric opioid prescriptions dispensed in Rhode Island. METHODS: All Rhode Island residents aged 0-17 years with an initiate opioid prescription dispensed between January 1, 2017 and December 31, 2021 were obtained from the Rhode Island Prescription Drug Monitoring Program. Analyses were conducted to investigate trends related to patient demographics, prescription characteristics, diagnosis codes, and prescriber type. RESULTS: From 2017-2021, there was a decrease in the number of unique pediatric patients dispensed an initiate prescription, the number of initiate pediatric opioid prescriptions, and the initiate prescription dosage. Initiate opioid prescriptions were primarily related to dental-related diagnoses, and dentists and oral and maxillofacial (OMF) surgeons comprised the largest category of prescriber type. CONCLUSION: Initiate pediatric opioid prescriptions have decreased in Rhode Island in recent years. However, there remain opportunities to educate prescribers on reducing opioid exposure to vulnerable populations, including the use of alternate analgesics.

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

INTRODUCTION: 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. METHODS: Semi-structured interviews were conducted with pharmacists and prescribers who use a PDMP (n = 21). The interviews were audio-recorded, transcribed and thematically analysed. RESULTS: 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. DISCUSSION AND CONCLUSIONS: 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.

Prescription drug monitoring program (PDMP) utilization and outcomes within the West Palm Beach Veterans Affairs (VA) healthcare system.

OBJECTIVE: Prescription drug monitoring programs (PDMPs) can identify patients at risk of controlled substance (CS) polypharmacy and accidental poisoning. DESIGN: A retrospective pre-/post-intervention review of a random sample of provider notes with documentation of PDMP outcomes was completed before and after the enactment of a Florida law mandating PDMP queries. SETTING: West Palm Beach Veterans Affairs Health Care System, which provides inpatient and outpatient services. PARTICIPANTS: Reviewed a random sample of 10 percent of progress notes documenting PDMP outcomes between September and November 2017 and the same timeframe of 2018. INTERVENTIONS: Florida enacted a law in March 2018 requiring PDMP queries to be completed for all new and renewed CS prescriptions. MAIN OUTCOME MEASURED: The primary outcome was to compare PDMP utilization and prescribing decisions based on query results before and after the enactment of the law. RESULTS: The number of progress notes documenting PDMP queries increased by over 350 percent from 2017 to 2018. In 2017 and 2018, 30.6 percent (68/222) and 20.8 percent (164/790) of PDMP queries found non-Veterans Affairs (VA) CS prescriptions, respectively. Providers decided to avoid prescribing CS prescriptions in 23.5 percent (16/68) of patients with non-VA CS prescriptions found in 2017 and 11 percent (18/164) in 2018. Overlapping or unsafe combinations were identified in 10 percent (7/68) of queries with non-VA prescriptions found in 2017 and 14 percent (23/164) in 2018. CONCLUSIONS: Mandating PDMP queries resulted in an increase in the total number of queries, positive findings, and overlapping CS prescriptions. Outcomes of PDMP mandate impacted prescribing by discontinuation and avoidance of CS initiation in 10-15 percent of patients.

Prescription drug monitoring programs evaluation: A systematic review of reviews.

BACKGROUND: Prescription drug monitoring programs (PDMPs) are used to mitigate harms from high-risk medicines including misuse, prescription shopping, overdoses, and death. Previous systematic reviews report inconsistent findings. We undertook a systematic review of reviews to 1) describe and identify the methods and outcome measures used to evaluate PDMPs, 2) summarise existing evidence on outcomes and factors that influence PDMP success or benefit realisation. METHODS: MEDLINE, EMBASE, Scopus, Cochrane Database of Systematic Reviews, and PROSPERO were used to identify systematic reviews on PDMPs. Twelve papers met the inclusion criteria. Data extracted included review aim, study designs, settings, outcome measures, and key findings. Quality was assessed using AMSTAR 2 quality assessment tool. RESULTS: Review papers were categorised as outcome or process evaluation reviews. Process evaluation reviews described implementation processes, barriers and facilitators to PDMP use and/or implementation. Most (57%) papers described barriers which frequently included usability and data integration. Outcome evaluation papers reported impact of PDMPs on outcomes, which were opioid-focused, and findings were highly variable. Most reviews (67%) were rated as low quality, limiting the conclusions that can be drawn. CONCLUSIONS: Inconsistent methods and outcome measures were used to evaluate PDMPs. No economic evaluations of PDMPs were found. Standardising assessment and reporting of results may improve the quality and confidence in an evidence-base to inform future roll-out and evaluation of PDMPs. Targeting barriers such as system-related challenges and negative end-user perceptions could improve sustained uptake of PDMPs, and potentially facilitate benefits realisation, including mitigating harms of high-risk prescription medicines.

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.

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

BACKGROUND: Community 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. OBJECTIVE: This 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. METHODS: Data 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. RESULTS: The 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. CONCLUSIONS: We 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.