Advanced visualizations to interpret prescription drug monitoring program information.
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ABSTRACT:
SUBMITTER: Weiner SG
PROVIDER: S-EPMC6737934 | biostudies-literature | 2019 Aug
REPOSITORIES: biostudies-literature
Publications
Advanced visualizations to interpret prescription drug monitoring program information.
Weiner Scott G SG Sherritt Karen M KM Tseng Zoe Z Tripathi Jaya J
Drug and alcohol dependence 20190625
<h4>Objectives</h4>Prescription drug monitoring programs (PDMPs) are state-based databases that contain information about controlled substance prescriptions dispensed by pharmacies. Many states now mandate PDMP use by prescribers, despite unclear effectiveness. We hypothesize that it is possible to improve the interpretability, and hence effectiveness, of PDMPs by enhancing them.<h4>Methods</h4>This was a real-time simulation of an enhanced PDMP. Fifty practicing physicians (25 primary care, 25 ...[more]
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Project description:ObjectiveThe Arkansas Prescription Monitoring Program (AR PMP) was implemented in 2013 to combat prescription drug abuse. All enrollees were invited to participate in a user survey available in February 2014, to identify makeup of users, utilization of the program, and changes made to health care practices after implementation of the program.MethodsOf the 3,694 individual enrollees invited to participate, 1,541(41.7%) completed the survey. Data collected were analyzed to identify changes in health care practices by program frequency of use and user profession.ResultsMedical doctors, advanced practice nurses, and pharmacists are the professions who use the program most frequently. Daily AR PMP users are considerably more likely than infrequent users to be prompted to access the program by the involvement of a controlled substance (CS) prescription or by office/facility policy requirements. Increased frequency of use of the AR PMP results in positive impacts on CS prescribing and dispensing practices.ConclusionCompelling more users of the AR PMP to be prompted to access the program by the involvement of a CS prescription or by requirements per office/facility policy may increase frequency of use of the program and thereby changes in health care practices to combat prescription drug abuse.
| S-EPMC4502438 | biostudies-literature
Project description:ObjectiveThe US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain management clinics. We aimed to provide practical design recommendations to improve PDMP workflow integration, as well as controlled substance history retrieval, interpretation, and decision support.MethodsWe conducted 16 in-depth semi-structured interviews with practicing emergency and pain physicians regarding their procedures, problems, and proposed solutions surrounding their use of CURES, California's PDMP. We investigated design problems in CURES by combining users' feedback with our usability inspection, drawing upon an extensive body of design literature. Then, we generated alternatives using design methods.ResultsWe found CURES's design did not accommodate the unique information needs of different medical domains. Further, clinicians had trouble accessing CURES and retrieving patients' controlled substance histories, mainly due to usability problems that could be addressed with little technical adjustment. Additionally, CURES rendered patient histories in large, cluttered tables, devoid of overview or context, making interpretation difficult and precarious. Lastly, our interviewees had rarely noticed or used advanced features, such as decision support.Discussion and conclusionUsability barriers inhibited adoption and effective use. We provide practical recommendations for improving opioid control by way of improving PDMP design, based on interviewees' suggestions and research-based design principles. Our findings have implications for other disciplines, including surgery and primary care.
| S-EPMC6951861 | biostudies-literature
Project description:INTRODUCTION:The purpose of this study is to extend prior research on barriers to use of a prescription drug monitoring program by examining psychosocial correlates of intended use among physicians and pharmacists. METHODS:Overall, 1,904 California physicians and pharmacists responded to a statewide survey (24.1% response rate) from August 2016 to January 2017. Participants completed an online survey examining attitudes toward prescription drug misuse and abuse, prescribing practices, prescription drug monitoring program design and ease of use, professional obligations, and normative beliefs regarding prescription drug monitoring program use. Data were analyzed in 2017. RESULTS:Perceived prescription drug monitoring program usefulness and normative beliefs fully mediated the relationship between concern about prescription drug abuse and intentions to use the prescription drug monitoring program. Clinicians' sense of professional and moral obligation to use the prescription drug monitoring program was unrelated to intention to use the prescription drug monitoring program despite a positive relationship with concern about misuse and abuse. Compared with physicians, pharmacists reported greater concern about prescription drug misuse, greater professional and moral obligation to use prescription drug monitoring program, and greater rating of prescription drug monitoring program usefulness. CONCLUSIONS:Interventions that target normative beliefs surrounding prescription drug monitoring program use and how to use prescription drug monitoring programs effectively are likely to be more effective than those that target professional obligations or moralize to the medical community.
| S-EPMC6151268 | biostudies-literature
Project description:Prescription Drug Monitoring Programs (PDMP) are statewide databases that collect data on prescription of controlled substances. New York State mandates prescribers to consult the PDMP registry before prescribing a controlled substance such as opioid analgesics. The effect of mandatory PDMP on opioid drug prescriptions by dentists is not known. This study investigates the impact of mandatory PDMP on frequency and quantity of opioid prescriptions by dentists in a dental urgent care center. Based on the sample size estimate, we collected patient records of a 3-month period before and two consecutive 3-month periods after the mandatory PDMP implementation and analyzed the data on number of visits, treatment types and drug prescriptions using Chi-square tests. For patients who were prescribed pain medications, 452 (30.6%), 190 (14.1%), and 140 (9.6%) received opioid analgesics in the three study periods respectively, signifying a statistically significant reduction in the number of opioid prescriptions after implementation of the mandatory PDMP (p<0.05). Total numbers of prescribed opioid pills in a 3-month period decreased from 5096 to 1120, signifying a 78% reduction in absolute quantity. Prescriptions for non-opioid analgesics acetaminophen increased during the same periods (p<0.05). We conclude that the mandatory PDMP significantly affected the prescription pattern for pain medications by dentists. Such change in prescription pattern represents a shift towards the evidence-based prescription practices for acute postoperative pain.
| S-EPMC4537135 | biostudies-other
Project description:BACKGROUND:Although prescription drug monitoring programs (PDMPs) have been widely implemented to potentially reduce abuse of prescription opioids, there is limited data on variations in PDMP use by prescriber specialty. Such knowledge may guide targeted interventions to improve PDMP use. METHODS:Using data from Washington state Medicaid program, we performed a retrospective cohort study of opioid prescribers and their PDMP queries between Nov 1, 2013 and Oct 31, 2014. PDMP registration was mandatory for emergency physicians, but not for other providers. The unit of analysis was the prescriber. The primary outcome was any prescriber queries of the PDMP. We used multivariate regression models to identify variations in PDMP queries by prescriber specialty, as well as to explore explanatory pathways for observed variations. RESULTS:We studied 17,390 providers who prescribed opioids, including 8718 (50%) who were not registered with PDMP, 4767 (27%) who were registered but had no recorded use of the PDMP, and 3905 (23%) PDMP users (queries/user: median 18, IQR 5-64). Compared to general medicine physicians, PDMP use was higher for emergency physicians (OR 1.4, 95%CI: 1.2-1.7), and lower for surgical specialists (OR 0.1, 95%CI: 0.08-0.1), obstetrician-gynecologists (OR 0.2, 95%CI: 0.1-0.2) and dentists (OR 0.4, 95%CI: 0.4-0.5). Higher use by emergency physicians appeared to be mediated by higher registration rates, rather than by provider level predilection to use the PDMP. CONCLUSIONS:A minority of opioid prescribers to Medicaid beneficiaries used the PDMP. We identified variations in PDMP use by prescriber specialty. Interventions to increase PDMP queries should target both PDMP registration and PDMP use after registration, as well as specialties with current low use rates.
| S-EPMC6453570 | biostudies-literature
Project description:IntroductionPrescription Drug Monitoring Program data can provide insights into a patient's likelihood of an opioid overdose, yet clinicians and public health officials lack indicators to identify individuals at highest risk accurately. A predictive model was developed and validated using Prescription Drug Monitoring Program prescription histories to identify those at risk for fatal overdose because of any opioid or illicit opioids.MethodsFrom December 2018 to July 2019, a retrospective cohort analysis was performed on Maryland residents aged 18-80 years with a filled opioid prescription (n=565,175) from January to June 2016. Fatal opioid overdoses were identified from the Office of the Chief Medical Examiner and were linked at the person-level with Prescription Drug Monitoring Program data. Split-half technique was used to develop and validate a multivariate logistic regression with a 6-month lookback period and assessed model calibration and discrimination.ResultsPredictors of any opioid-related fatal overdose included male sex, age 65-80 years, Medicaid, Medicare, 1 or more long-acting opioid fills, 1 or more buprenorphine fills, 2 to 3 and 4 or more short-acting schedule II opioid fills, opioid days' supply ≥91 days, average morphine milligram equivalent daily dose, 2 or more benzodiazepine fills, and 1 or more muscle relaxant fills. Model discrimination for the validation cohort was good (area under the curve: any, 0.81; illicit, 0.77).ConclusionsA model for predicting fatal opioid overdoses was developed using Prescription Drug Monitoring Program data. Given the recent national epidemic of deaths involving heroin and fentanyl, it is noteworthy that the model performed equally well in identifying those at risk for overdose deaths from both illicit and prescription opioids.
| S-EPMC7996003 | biostudies-literature
Project description:ObjectiveClinical review of a prescription drug monitoring program (PDMP) is considered a valuable tool for opioid prescribing risk mitigation; however, PDMP use is often low, even in states with mandatory registration and use policies. The objective was to evaluate the impact of an academic detailing (AD) outreach intervention on PDMP use among primary care prescribers.MethodsAD intervention was delivered to primary care based controlled substance prescribers (N = 87) and their associated PDMP delegates (n = 42) by a clinical pharmacist as 1 component of a large-scale, statewide initiative to improve opioid prescribing safety. Prescriber PDMP use behavior was assessed by prescriber self-report and analysis of objective 2016-2018 PDMP data regarding the number of monthly report requests. We compared means between pre- and postintervention using a paired t test and plotted the monthly average reports over time to assess the trend of mean reports over time. Generalized linear mixed model with a negative binomial distribution was used to assess the difference in the trend and magnitude of the combined count of reports for the entire sample and prescriber subsets that were segmented on the basis of the adoption status of PDMP.ResultsThe monthly mean of reports by combined prescribers and delegates significantly increased after the AD intervention (mean 28.1 pre vs. 53.0 post; P < 0.001), with the increase in delegate reports (mean 17.1 pre vs. 60.0 post; P < 0.001) driving the overall increase. Reports were requested 40.4 times more often than in the preintervention period (P < 0.001). Patterns of pre- to postchanges in mean monthly report requests differed by baseline PDMP adoption status.ConclusionThe AD intervention was transformative in facilitating practice change to use delegates to run reports. Visits with both prescribers and delegates, including hands-on PDMP training and registration assistance, can be viewed as beneficial for practice facilitation.
| S-EPMC8273068 | biostudies-literature
Project description:STUDY OBJECTIVE:We assess whether an automated prescription drug monitoring program intervention in emergency department (ED) settings is associated with reductions in opioid prescribing and quantities. METHODS:We performed a retrospective cohort study of ED visits by Medicaid beneficiaries. We assessed the staggered implementation (pre-post) of automated prescription drug monitoring program queries at 86 EDs in Washington State from January 1, 2013, to September 30, 2015. The outcomes included any opioid prescribed within 1 day of the index ED visit and total dispensed morphine milligram equivalents. The exposure was the automated prescription drug monitoring program query intervention. We assessed program effects stratified by previous high-risk opioid use. We performed multiple sensitivity analyses, including restriction to pain-related visits, restriction to visits with a confirmed prescription drug monitoring program query, and assessment of 6 specific opioid high-risk indicators. RESULTS:The study included 1,187,237 qualifying ED visits (898,162 preintervention; 289,075 postintervention). Compared with the preintervention period, automated prescription drug monitoring program queries were not significantly associated with reductions in the proportion of visits with opioid prescribing (5.8 per 1,000 encounters; 95% confidence interval [CI] -0.11 to 11.8) or the amount of prescribed morphine milligram equivalents (difference 2.66; 95% CI -0.15 to 5.48). There was no evidence of selective reduction in patients with previous high-risk opioid use (1.2 per 1,000 encounters, 95% CI -9.5 to 12.0; morphine milligram equivalents 1.22, 95% CI -3.39 to 5.82). The lack of a selective reduction in high-risk patients was robust to all sensitivity analyses. CONCLUSION:An automated prescription drug monitoring program query intervention was not associated with reductions in ED opioid prescribing or quantities, even in patients with previous high-risk opioid use.
| S-EPMC5820164 | biostudies-literature
Project description:Comprehensive mandates for prescription drug monitoring programs (PDMPs) require state-licensed prescribers and dispensers both to register with and to use the programs in most clinical circumstances. Such mandates have the potential to improve providers' participation and reduce opioid-related adverse events. Using Medicaid prescription data and hospital utilization data across the US in the period 2011-16, we found that state implementation of comprehensive PDMP mandates was associated with a reduction in the opioid prescription rate from 161.47 to 147.07 per 1,000 enrollees per quarter, a reduction in the opioid-related inpatient stay rate from 97.50 to 93.34 per 100,000 enrollees per quarter, and a reduction in the opioid-related emergency department (ED) visit rate from 74.60 to 61.36 per 100,000 enrollees per quarter. Our estimated annual reductions of approximately 12,000 inpatient stays and 39,000 ED visits could save over $155 million in Medicaid spending, a fact that deserves policy attention when states attempt to strengthen and refine PDMPs to better tackle the opioid crisis.
| S-EPMC6824582 | biostudies-literature
Project description:IntroductionThe objective of this scoping review is to describe the extent and nature of research studies based on linked prescription drug monitoring program (PDMP) data; defined as PDMP data linked to other clinical, administrative or public health data sets. The population is prescribed and dispensed controlled substances. The concept is analysis of linked PDMP data to other clinical, administrative or public health data sets. The context is the USA.Methods and analysisThe scoping review will be conducted with guidance from the latest version of the JBI Manual for Evidence Synthesis, using the framework as outlined by Arksey and O'Malley. Search strategies will be peer-reviewed according to the Peer Review of Electronic Search Strategies (PRESS) guidelines. For transparency and reproducibility, we will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines in reporting results. Two reviewers will independently screen titles and abstracts, then independently review full text to select papers or studies for inclusion. When consensus cannot be reached with discussion, a third reviewer will resolve the conflicts. From our included studies, we will extract variables describing aspects of population, concept and context (USA).Ethics and disseminationEthical approval was not required for this review. This scoping review entails analysis of previously published, peer-reviewed research. We intend to publish findings in a peer-reviewed journal.
| S-EPMC9013995 | biostudies-literature