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.

State-level policies and receipt of CDC-informed opioid thresholds among commercially insured new chronic opioid users.

OBJECTIVES: To evaluate the association of state-level policies on receipt of opioid regimens informed by Centers for Disease Control and Prevention (CDC) morphine milligram equivalent (MME)/day recommendations. DESIGN: A retrospective cohort study of new chronic opioid users (NCOUs). SETTING: Commercially insured plans across the United States using IQVIA PharMetrics® Plus for Academics database with new chronic use between January 2014 and March 2015. PARTICIPANTS: NCOUs with ≥60-day coverage of opioids within a 90-day period with ≥30-day opioid-free period prior to the date of the first qualifying opioid prescription. INTERVENTIONS: State-level policies including Prescription Drug Monitoring Program (PDMP) robustness and cannabis policies involving the presence of medical dispensaries and state-wide decriminalization. MAIN OUTCOME MEASURES: NCOUs were placed in three-tiered risk-based average MME/day thresholds: low (>0 to <50), medium (≥50 to <90), and high (≥90). Multinomial logistic regression was used to estimate the association of state-level policies with the thresholds while adjusting for relevant patient-specific factors. RESULTS: NCOUs in states with medium or high PDMP robustness had lower odds of receiving medium (adjusted odds ratio [AOR] 0.74; 95 percent confidence interval [CI]: 0.62-0.69) and high (AOR 0.74; 95 percent CI: 0.59-0.92) thresholds. With respect to cannabis policies, NCOUs in states with medical cannabis dispensaries had lower odds of receiving high (AOR 0.75; 95 percent CI: 0.60-0.93) thresholds, while cannabis decriminalization had higher odds of receiving high (AOR 1.24; 95 percent CI: 1.04-1.49) thresholds. CONCLUSION: States with highly robust PDMPs and medical cannabis dispensaries had lower odds of receiving higher opioid thresholds, while cannabis decriminalization correlated with higher odds of receiving high opioid thresholds.

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.

Buprenorphine prescribing and treatment accessibility in response to regulation changes due to the COVID-19 public health emergency.

BACKGROUND: In 2021, over 80,000 fatal overdoses occurred in the United States. Since 2020, the federal government has enacted multiple regulatory changes around buprenorphine prescribing for opioid use disorder (OUD) to increase access to buprenorphine. This study aims to explore trends in buprenorphine treatment initiation pre- and post-public health emergency to evaluate changes in the context of X-waiver relaxations and telehealth allowances. METHODS: In a cross-sectional study, all RI residents who filled a buprenorphine prescription at a pharmacy in Rhode Island (RI), Massachusetts, and Connecticut between January 2017 and December 2023 were obtained from the RI Prescription Drug Monitoring Program (PDMP). The study excluded buprenorphine products not approved for OUD treatment from the analysis. Identified individuals had initiated buprenorphine for OUD during the study period if they did not have a prior prescription or if they had >30 days without buprenorphine exposure between their prescriptions. Spearman's rank correlation tests were used to identify significant associations between outcomes and regulation changes. RESULTS: The average number of patients dispensed buprenorphine did not significantly change over the study period, however the average number of initiates significantly decreased (ρ = -0.38255, p = .0003). The average number of providers prescribing CII-CV substances in RI has increased 3.4 % over the study period. The average percentage of prescribers in the PDMP prescribing buprenorphine for OUD doubled (ρ = 0.96075, p < .0001). CONCLUSION: Though efforts have been made to increase buprenorphine initiation, buprenorphine initiates remain well below pre-PHE levels. Efforts must continue to eliminate existing barriers to treatment and improve access to individuals seeking treatment.

Opioid Use in Pelvic Fractures: The Impact of Opioid Prescribing Laws in Pennsylvania.

Pennsylvania's Prescription Drug Monitoring Program (PDMP) was established in 2016, but its impact on opioid use for pelvic fractures is understudied. We compared opioid use in 277 pelvic fracture cases between two periods: 2015-2017 (T1) and 2018-2020 (T2). Outcomes included daily inpatient morphine milligram equivalents (MME), long-term opioid use (LOU) 60-90 days post-discharge, and intermediate-term opioid use (IOU) 30-60 days post-discharge. T1 and T2 had comparable baseline characteristics. T2 was associated with a decrease in average daily inpatient MME (58.6 vs 78.5, P = .02), particularly in younger patients. Regression analyses showed age and Injury Severity Score (ISS) were significant predictors for daily inpatient MME, while time period was not. Geriatric patients in T2 had significantly decreased IOU (30% vs 9%, P = .05). Pelvic fracture type and daily MME predicted IOU, while pelvic fracture type predicted LOU. This study suggests a modest impact of these laws, but further study is needed.

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.

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.

Comprehensive, evidence-based, consensus guidelines for prescription of opioids for chronic non-cancer pain from the American Society of Interventional Pain Physicians (ASIPP)

Opioid prescribing in the United States is decreasing, however, the opioid epidemic is continuing at an uncontrollable rate. Available data show a significant number of opioid deaths, primarily associated with illicit fentanyl use. It is interesting to also note that the data show no clear correlation between opioid prescribing (either number of prescriptions or morphine milligram equivalent [MME] per capita), opioid hospitalizations, and deaths. Furthermore, the data suggest that the 2016 guidelines from the Centers for Disease Control and Prevention (CDC) have resulted in notable problems including increased hospitalizations and mental health disorders due to the lack of appropriate opioid prescribing as well as inaptly rapid tapering or weaning processes. Consequently, when examined in light of other policies and complications caused by COVID-19, a fourth wave of the opioid epidemic has been emerging. In light of this, we herein seek to provide guidance for the prescription of opioids for the management of chronic non-cancer pain. These clinical practice guidelines are based upon a systematic review of both clinical and epidemiological evidence and have been developed by a panel of multidisciplinary experts assessing the quality of the evidence and the strength of recommendations and offer a clear explanation of logical relationships between various care options and health outcomes. The methods utilized included the development of objectives and key questions for the various facets of opioid prescribing practice. Also utilized were employment of trustworthy standards, and appropriate disclosures of conflicts of interest(s). The literature pertaining to opioid use, abuse, effectiveness, and adverse consequences was reviewed. The recommendations were developed after the appropriate review of text and questions by a panel of multidisciplinary subject matter experts, who tabulated comments, incorporated changes, and developed focal responses to questions posed

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.

Lineamientos técnicos y operativos para la aplicación de la vacuna contra la COVID-19 - Pfizer Bivalente Hondura / Technical and operational guidelines for the application of the vaccine against COVID-19 - Pfizer Bivalent Depth

El presente lineamiento de la Vacuna contra la COVID 19 Pfizer Bivalente deberá ser utilizado por los proveedores de servicios de vacunación en Establecimientos de Salud públicos de la SESAL y del Instituto Hondureño de Seguridad Social (IHSS), para la prevención de la COVID-19, inmediatamente de la aprobación de este documento normativo. Estos lineamientos estarán vigentes mientras las características de la vacuna y la población se mantengan en las condiciones presentes en este documento...(AU)

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.