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OBJECTIVES: 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. METHODS: This was a real-time simulation of an enhanced PDMP. Fifty practicing physicians (25 primary care, 25 emergency medicine) were randomized to see three cases with a standard profile or an enhanced profile that included graphical representation of prescriptions and identified risky prescribing patterns. After a two-month washout period, participants were placed in the opposite group. RESULTS: Physicians presented with the enhanced profile were more likely to correctly identify patients with multiple providers (97.0% vs. 85.8%, p=0.002), overlapping opioid and benzodiazepine prescriptions (94.7% vs. 87.5%, p=0.03), overlapping opioid prescriptions (89.5% vs. 70.8%, p

The U.S. opioid epidemic persists, yet it is unclear if opioid-related emergency department (ED) policies have changed. We investigated: 1) the prevalence of opioid use disorder (OUD) prevention and treatment policies in New England EDs in 2018, and 2) how these policies have changed since 2014.Using the National Emergency Department Inventory-USA, we identified and surveyed all New England EDs in 2015 and 2019 about opioid-related policies in 2014 and 2018, respectively. The surveys assessed OUD prevention policies (to use a screening tool, access the Prescription Drug Monitoring Program [PDMP], notify primary care providers, prescribe/dispense naloxone) and treatment policies (to refer to recovery resources, prescribe/dispense buprenorphine).Of 194 EDs open in 2018, 167 (86 %) completed the survey. Of 193 EDs open in 2018 and 2014, 147 (76 %) completed both surveys. In 2018, the most commonly-reported policy was accessing the PDMP (96 %); the least commonly-reported policy was prescribing/dispensing buprenorphine to at risk patients (37 %). EDs varied in prescribing/dispensing naloxone: 35 % of EDs offered naloxone to ≥80 % of patients at risk of opioid overdose versus 33 % of EDs to10 % of patients at risk. Most EDs (74 %) reported prescribing/dispensing buprenorphine to10 % of patients with OUD. Comparing 2018 to 2014, the greatest difference in policy use was in prescribing/dispensing naloxone (+55 %, p0.001).Implementation of opioid-related ED policies increased between 2014 and 2018. Continued effort is needed to understand the extent to which policy implementation translates to clinical care, and to best translate evidence-based policies into clinical practice.

Objectives This study aimed to: (a) determine the percentage of ED patients receiving prescriptions for opioid pain medications that meet the criteria for “high-risk for abuse potential” on the Screener and Opioid Assessment for Patients with Pain (SOAPP®-R), (b) determine the percentage of patients with high-risk behavior on the state prescription drug monitoring program (PDMP) database, (c) compare the SOAPP-R with data from the PDMP, and (d) determine psychometric properties of SOAPP-R for ED patients Methods Convenience sample of ED patients who were being considered for discharge with a prescription for an opioid pain medication. Subjects completed SOAPP-R on an electronic tablet and PDMP data was obtained. Scores on SOAPP-R ≥18 were defined as “at-risk”, and PDMP data showing both ≥4 opioid prescriptions and ≥4 providers in 12 months was considered the criterion standard for high-risk behavior. Results 82 patients (88.2%) provided consent. 32.9% (n = 27) were determined to be “at-risk” (score ≥18) by SOAPP-R. 15.9% (n = 13) subjects met PDMP criteria and 53.9% (n = 7) of those had SOAPP-R scores ≥18 (sensitivity 54%, specificity 71%, positive predictive value 26%, negative predictive value 89%). The association of an at-risk SOAPP-R score and PDMP high-risk criteria was an adjusted odds ratio of 1.39 (95% confidence interval 0.73–3.68). Conclusions In our population, about one-third of patients being considered for discharge with an opioid prescription scored “at-risk” on SOAPP-R and 15.9% met the PDMP high-risk criteria. The high negative predictive value of SOAPP-R indicates it may be a useful screening tool for the ED patient population.

BackgroundThe Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R) is a 24-item assessment designed to assist in the prediction of aberrant drug-related behavior (ADB) among patients with chronic pain. Recent work has created shorter versions of the SOAPP-R, including a static 12-item short form and two computer-based methods (curtailment and stochastic curtailment) that monitor assessments in progress. The purpose of this study was to cross-validate these shorter versions in two new populations.MethodsThis retrospective study used data from patients recruited from a hospital-based pain center (n = 84) and pain patients followed and treated at primary care centers (n = 110). Subjects had been administered the SOAPP-R and assessed for ADB. In real-data simulation, the sensitivity, specificity, and area under the curve (AUC) of each form were calculated, as was the mean test length using curtailment and stochastic curtailment.ResultsCurtailment reduced the number of items administered by 30% to 34% while maintaining sensitivity and specificity identical to those of the full-length SOAPP-R. Stochastic curtailment reduced the number of items administered by 45% to 63% while maintaining sensitivity and specificity within 0.03 of those of the full-length SOAPP-R. The AUC of the 12-item form was equal to that of the 24-item form in both populations.ConclusionsCurtailment, stochastic curtailment, and the 12-item short form have potential to enhance the efficiency of the SOAPP-R