Assessment of Postoperative Opioid Prescriptions Before and After Implementation of a Mandatory Prescription Drug Monitoring Program.
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ABSTRACT:
SUBMITTER: Shenoy R
PROVIDER: S-EPMC8725834 | biostudies-literature | 2021 Oct
REPOSITORIES: biostudies-literature
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Assessment of Postoperative Opioid Prescriptions Before and After Implementation of a Mandatory Prescription Drug Monitoring Program.
Shenoy Rivfka R Wagner Zachary Z Kirkegaard Allison A Romanelli Robert J RJ Mudiganti Satish S Mariano Louis L Martinez Meghan M Zanocco Kyle K Watkins Katherine E KE
JAMA health forum 20211001 10
<h4>Importance</h4>Legislation mandating consultation with a prescription drug monitoring program (PDMP) was implemented in California on October 2, 2018. This mandate requires PDMP consultation before prescribing a controlled substance and integrates electronic health record (EHR)-based alerts; prescribers are exempt from the mandate if they prescribe no more than a 5-day postoperative opioid supply. Although previous studies have examined the consequences of mandated PDMP consultation, few hav ...[more]
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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:BackgroundIn 2016, California updated its prescription drug monitoring program (PDMP), adding two key features: automated proactive reports to prescribers and mandatory registration for prescribers and pharmacists. The effects of these changes on prescribing patterns have not yet been examined. We aimed to evaluate the joint effect of these two PDMP features on county-level prescribing practices in California.MethodsUsing county-level quarterly data from 2012 to 2017, we estimated the absolute change associated with the implementation of these two PDMP features in seven prescribing indicators in California versus a control group comprising counties in Florida and Washington: opioid prescription rate per 1000 residents; patients' mean daily opioid dosage in milligrams of morphine equivalents[MME]; prescribers' mean daily MME prescribed; prescribers' mean number of opioid prescriptions per day; percentage of patients getting >90 MME/day; percentage of days with overlapping prescriptions for opioids and benzodiazepines; multiple opioid provider episodes per 100,000 residents.ResultsProactive reports and mandatory registration were associated with a 7.7 MME decrease in patients' mean daily opioid dose (95 %CI: -11.4, -2.9); a 1.8 decrease in the percentage of patients prescribed high-dose opioids (95 %CI: -2.3, -0.9); and a 6.3 MME decrease in prescribers' mean daily dose prescribed (95 %CI: -10.0, -1.3).ConclusionsCalifornia's implementation of these two PDMP features was associated with decreases in the total quantity of opioid MMEs prescribed, and indicators of patients prescribed high-dose opioids compared to states that had PDMP's without these features. Rates of opioid prescribing and other high-risk prescribing patterns remained unchanged.
| S-EPMC7750250 | biostudies-literature
Project description:BackgroundPrescription drug monitoring programs (PDMPs) exist in 49 states to guide opioid prescribing. In 40 states, clinicians must check the PDMP prior to prescribing an opioid. Data on mandated PDMP checks show mixed results on opioid prescribing.ObjectivesThis study sought to examine the impact of the Massachusetts mandatory PDMP check on opioid prescribing for discharges from an urban tertiary emergency department (ED).MethodsThis was a retrospective cohort study of discharges from one ED from 7/1/2010-10/15/2018. The primary outcome was the monthly percentage of patients discharged from the ED with an opioid prescription. The intervention was Massachusetts mandating a PDMP check for all opioid prescriptions. Prescribing was compared pre- and post-mandate. Interrupted time series (ITS) analysis accounted for known declining trends in opioid prescribing.ResultsOf 273,512 ED discharges, 35,050 (12.8%) received opioid prescriptions. Mean monthly opioid prescribing decreased post-intervention from 15.1% (SD ± 3.5%) to 5.1% (SD ± 0.9%; p < 0.001). ITS showed equal pre and post-intervention slopes (-0.002, p = 0.819). A small immediate decrease occurred in prescribing around the mandated check: a 3-month level effect decrease of 0.018 (p = 0.039), 6-month level effect 0.019 (p = 0.023), and a 12-month level effect of 0.020 (p = 0.019). The 24-month level effect was not decreased.ConclusionPrior to the mandated PDMP check, ED opioid prescribing was declining. The mandate did not change the rate of decline but was associated with a non-sustained drop in opioid prescribing immediately following enactment.
| S-EPMC8206309 | biostudies-literature
Project description:BackgroundOut-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.ObjectiveTo estimate the frequency and characteristics of prescription fills for opioids that are likely paid out-of-pocket by individuals in the Oregon Medicaid program.Research designCross-sectional analysis using Oregon Medicaid administrative claims and PDMP data (2012 to 2013).SubjectsContinuously enrolled nondually eligible Medicaid beneficiaries who could be linked to the PDMP with two opioid fills covered by Oregon Medicaid.MeasuresPatient 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.ResultsA total of 33 592 Medicaid beneficiaries filled a total of 555 103 opioid prescriptions. Of these opioid fills, 74 953 (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).ConclusionsPrescription opioid fills that were likely paid out-of-pocket were common and associated with several known indicators of high-risk opioid use.
| S-EPMC9926937 | biostudies-literature
Project description:IntroductionPrescription 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.MethodsDe-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.ResultsIn 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 conclusionsPDMP 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.
| S-EPMC10947011 | biostudies-literature
Project description:OBJECTIVES:To estimate the effect of California's prescription drug monitoring program's (PDMP) registration mandate on use of the PDMP. METHODS:We evaluated the effect of California's mandatory PDMP registration law by fitting time series models on the percentage of clinicians registered for California's PDMP and the percentage of clinicians who were active PDMP users (users who created ??1 patient prescription reports in a given month) from 2010 through 2017. We also compared PDMP use among early PDMP adopters (clinicians who registered >?8 months before the mandatory registration deadline) versus late adopters (clinicians who registered ??8 months before the deadline). RESULTS:Mandatory registration was associated with increases in active PDMP users: 53.5% increase for prescribers and 17.9% for pharmacists. Early adopters were 4 times more likely to be active PDMP users than were late adopters. CONCLUSIONS:Mandatory registration was associated with increases in PDMP registration and use, but most new registrants did not become active users. Public Health Implications. Mandatory PDMP registration increases PDMP use but does not result in widespread PDMP usage by all clinicians prescribing controlled substances.
| S-EPMC6236755 | biostudies-literature
Project description:BackgroundIn the past two decades, the U.S. saw an alarmingly increasing trend of benzodiazepine prescribing. Mandatory use of Prescription Drug Monitoring Programs (PDMPs) was suggested to have the potential to reduce opioid prescribing, but little is known about its impacts on benzodiazepines. This study examined whether PDMP data use mandates were associated with changes in benzodiazepine prescribing in the U.S. Methods: Aggregate state quarterly prescription drug records of benzodiazepines for Medicaid enrollees during 2010-2017 were obtained from the U.S. Medicaid State Drug Utilization Data. Three population-adjusted outcome variables were evaluated, including quantity, dosage, and Medicaid spending of benzodiazepine prescriptions per quarter per 100 Medicaid enrollees. The primary policy variable was the state-wide implementation of PDMP data use mandates for benzodiazepines. To account for between-state variations in mandates, an additional policy variable was considered to indicate strong mandates on PDMP data use, which required all prescribers to query a patient's PDMP records for first prescribing and subsequent prescribing at least every 12 months. Linear regressions with difference-in-difference approach were used to assess the associations between PDMP data use mandates and benzodiazepine prescribing, controlling for state-level time-varying policy and socioeconomic covariates. Results: The state-wide implementation of PDMP data use mandates for benzodiazepines was not associated with quantity, dosage, or Medicaid spending of benzodiazepine prescriptions. Strong mandates on PDMP data use were not associated with any benzodiazepine prescribing outcomes, either. Conclusions: There was no evidence for the associations between PDMP data use mandates for benzodiazepines and changes in benzodiazepine prescribing among Medicaid enrollees. Future research is warranted to replicate the study in other populations using individual patient records and continuously monitor the trends in benzodiazepine prescribing in association with PDMPs.
| S-EPMC7202951 | 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: Not available
| S-EPMC4465450 | biostudies-literature
Project description:Policies and practices have proliferated to optimize prescribers' use of their states' prescription drug monitoring programs, which are statewide databases of controlled substances dispensed at retail pharmacies. Our study assessed the effectiveness of three such policies: comprehensive legislative mandates to use the program, laws that allow prescribers to delegate its use to office staff, and state participation in interstate data sharing. Our analysis of information from a large commercial insurance database indicated that comprehensive use mandates implemented during 2011-15 were associated with a 6-9 percent reduction in opioid prescriptions with high risk for misuse and overdose. We also found delegate laws to be associated with reductions of a similar magnitude for selected outcomes. In general, the effects of all three policies strengthened over time, especially beginning in the second year after implementation. Our findings support comprehensive use mandates and delegate laws to optimize prescribers' use of drug monitoring programs, but the results will need updates in the context of evolving state opioid policies-including the increasing integration of drug monitoring data with electronic health records.
| S-EPMC6362993 | biostudies-literature