Clinician impression versus prescription drug monitoring program criteria in the assessment of drug-seeking behavior in the emergency department

Efficacy of interventions targeted at physician prescribers of opioids for chronic non-cancer pain: an overview of systematic reviews

BACKGROUND

To combat the opioid crisis, interventions targeting the opioid prescribing behaviour of physicians involved in the management of patients with chronic non-cancer pain (CNCP) have been introduced in clinical settings. An integrative synthesis of systematic review evidence is required to better understand the effects of these interventions. Our objective was to synthesize the systematic review evidence on the effect of interventions targeting the behaviours of physician opioid prescribers for CNCP among adults on patient and population health and prescriber behaviour.

METHODS

We searched MEDLINE, Embase, and PsycInfo via Ovid; the Cochrane Database of Systematic Reviews; and Epistemonikos. We included systematic reviews that evaluate any type of intervention aimed at impacting opioid prescriber behaviour for adult CNCP in an outpatient setting.

RESULTS

We identified three full texts for our review that contained 68 unique primary studies. The main interventions we evaluated were structured prescriber education (one review) and prescription drug monitoring programmes (PDMPs) (two reviews). Due to the paucity of data available, we could not determine with certainty that education interventions improved outcomes in deprescribing. There is some evidence that PDMPs decrease the number of adverse opioid-related events, increase communication among healthcare workers and patients, modify healthcare practitioners' approach towards their opioid prescribed patients, and offer more chances for education and counselling.

CONCLUSIONS

Our overview explores the possibility of PDMPs as an opioid deprescribing intervention and highlights the need for more high-quality primary research on this topic.

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.

Leveraging the Prescription Drug Monitoring Program to Curb Opioid Prescribing in Arkansas

Effective means of accurately identifying problematic opioid prescribing are needed. Using an iterative approach with the Arkansas State Medical Board Pain Subcommittee, we modified existing opioid prescriber criteria to create seven metrics to be deployed in Arkansas. These included metrics of dose and days' supply, concomitant use of opioid and benzodiazepines, solid dosage units, and numbers of opioid patients and certain opioid prescriptions. Two of these metrics (average MME daily dose per prescription and total oxycodone 30 mg or hydromorphone prescriptions) were weighted by 2, creating a maximum score of 9 of which each prescriber could receive. Twenty prescribers with a score of 7 or greater were identified and referred to the Arkansas State Medical Board Pain Subcommittee for review and subsequent investigation if deemed necessary. Of those 20 prescribers, four were previously investigated and under disciplinary action, and three were under current investigation for misconduct related to prescribing practices. Five prescribers had new investigations opened due to the findings from the metrics, and disciplinary action was taken. Therefore, 12 of the 20 prescribers referred to the Arkansas State Medical Board were deemed worthy of investigation and disciplinary action. The Arkansas opioid prescriber metrics are able to accurately identify prescribers with potentially problematic opioid prescribing.

Flipping the script: The effects of opioid prescription monitoring on specialty-specific provider behavior

Mandatory access Prescription Drug Monitoring Programs (MA-PDMPs) aim to curb the epidemic at a common point of initiation of use, the prescription. However, there is recent concern about whether opioid policies have been too restrictive and reduced appropriate access to patients with the most need for opioid pharmaceuticals. We assess MA-PDMP's effect on specialty-specific opioid prescribing behavior of Medicare providers. Our findings suggest that requiring providers to query a PDMP differentially affects opioid prescribing across provider specialties. We find a three to four percent decrease in prescribing for Primary Care and Internal Medicine providers. This result is driven by healthcare providers at the lower end of the prescribing distribution. There is also suggestive evidence of an increase in opioid use disorder treatment drugs prescribed by these same providers. We also find no evidence for the hypothesis that MA-PDMPs restrict prescribing by providers who treat patients with potentially high levels of pain, few drug substitutes, or urgency for pain treatment (e.g., Oncology/Palliative care). This result is not dependent on whether a state provides exemptions for these providers. Our results indicate that MA-PDMPs may help close provider-patient informational gaps while retaining a provider's ability to supply these drugs to patients with a need for opioids.

Using wearable technology to detect prescription opioid self-administration

ABSTRACT

Appropriate monitoring of opioid use in patients with pain conditions is paramount, yet it remains a very challenging task. The current work examined the use of a wearable sensor to detect self-administration of opioids after dental surgery using machine learning. Participants were recruited from an oral and maxillofacial surgery clinic. Participants were 46 adult patients (26 female) receiving opioids after dental surgery. Participants wore Empatica E4 sensors during the period they self-administered opioids. The E4 collected physiological parameters including accelerometer x-, y-, and z-axes, heart rate, and electrodermal activity. Four machine learning models provided validation accuracies greater than 80%, but the bagged-tree model provided the highest combination of validation accuracy (83.7%) and area under the receiver operating characteristic curve (0.92). The trained model had a validation sensitivity of 82%, a specificity of 85%, a positive predictive value of 85%, and a negative predictive value of 83%. A subsequent test of the trained model on withheld data had a sensitivity of 81%, a specificity of 88%, a positive predictive value of 87%, and a negative predictive value of 82%. Results from training and testing model of machine learning indicated that opioid self-administration could be identified with reasonable accuracy, leading to considerable possibilities of the use of wearable technology to advance prevention and treatment.

How prescription drug monitoring programs influence clinical decision-making: A mixed methods systematic review and meta-analysis

BACKGROUND

Opioid prescribing, for chronic non-cancer pain, has increased substantially in the past two decades and is associated with significant harms. Various public health approaches have been adopted to address these harms including the implementation of prescription drug monitoring programs (PDMPs). This systematic review aims to identify how PDMP use influences healthcare providers' clinical decision-making.

METHODS

Six databases were searched for literature up until April 2021. Empirical studies were included, with no restrictions placed on year, location, language or study design. Thematic analysis of the identified articles was conducted and where possible, meta-analyses were conducted using a random effect model in Stata.

RESULTS

Forty-one articles related to 39 studies were included. All studies were conducted in the United States, published between 2005 and 2021 and most (n = 28) related to one state-level PDMP. PDMP utilisation influenced healthcare providers' clinical decision-making across seven broad themes: (i) the supply of controlled substances, (ii) refusal to prescribe or treat, (iii) risk mitigation strategies, (iv) communication, (v) education and counselling, (vi) referrals and care coordination and (vii) stigma.

CONCLUSIONS

PDMP use influenced healthcare providers' clinical decision-making, resulting in both intended and unintended outcomes for patients. PDMPs are a public health initiative designed to reduce harms associated with increased opioid prescribing, yet their use is associated with multiple unintended outcomes. Targeted research is needed to understand the impact of healthcare providers' clinical decision-making after PDMP utilisation, and the clinical outcomes for patients identified through these tools.

Retrospective Analysis of Adult Patients Presenting to the Acute Care Setting Requesting Prescriptions

Introduction

Patient visits to the emergency department (ED) or urgent care centre (UCC) for the sole purpose of requesting prescriptions are challenging for the patient, the physician, and the department. The primary objective of this study was to determine the characteristics of these patients, the nature of their requests, and the response to these requests. Our secondary objective was to determine the proportion of these medication requests that had street value.

Methods

This was a retrospective, electronic chart review of all adult patients requesting a prescription from a two-site ED and/or an UCC in a medium-sized Canadian city between April 1, 2014–June 30, 2017. Recorded outcomes included patient demographic data and access to a family doctor, medication requested, whether or not a prescription was given, and ED length of stay. Medication street value was determined using a local police service listing.

Results

A total of 2,265 prescriptions were requested by 1,495 patients. The patient median [interquartile range] age was 43 [32–54] years. A family doctor was documented by 55.4% (939/1,694) of patients. The two most commonly requested categories of medications were opioid analgesics 21.2% (481/2,265) and benzodiazepine anxiolytics 11.7% (266/2,265). Of patients requesting medication, 50.5% (755/1,495) requested medications without street value including some with potential to cause serious adverse health effects if discontinued. The requested prescription was received by 19.9% (298/1,495) of patients; 15.3% (173/1,134) returned for further prescription requests. The 90th percentile length of stay was 3.2 and 5.6 hours at the UCC and ED, respectively.

Conclusion

Patients who presented to the ED or UCC sought medications with and without street value in almost equal measure. A more robust understanding of these patients and their requests illustrates why a ‘one-size-fits-all’ response to these requests is inappropriate and signals some fault lines within our local healthcare system.

Positive Toxicology Results Are Not Associated with Emergency Physicians' Opioid Prescribing Behavior

Introduction

Given the general lack of literature on opioid and naloxone prescribing guidelines for patients with substance use disorder, we aimed to explore how a physician’s behavior and prescribing habits are altered by knowledge of the patient’s concomitant use of psychotropic compounds as evident on urine and serum toxicology screens.

Methods

We conducted a retrospective chart review study at a tertiary, academic, Level I trauma center between November 2017–October 2018 that included 358 patients who were discharged from the emergency department (ED) with a diagnosis of fracture, dislocation, or amputation and received an opioid prescription upon discharge. We extracted urine and serum toxicology results, number and amount of prescription opioids upon discharge, and the presence of a naloxone script.

Results

The study population was divided into five subgroups that included the following: negative urine and serum toxicology screen; depressants; stimulants; mixed; and no toxicology screens. When comparing the 103 patients in which toxicology screens were obtained to the 255 patients without toxicology screens, we found no statistically significant differences in the total prescribed morphine milligram equivalent (75.0 and 75.0, respectively) or in the number of pills prescribed (15.0 and 13.5, respectively). Notably, none of the 103 patients who had toxicology screens were prescribed naloxone upon discharge.

Conclusion

Our study found no association between positive urine toxicology results for psychotropically active substances and the rates of opioid prescribing within a single-center, academic ED. Notably, none of the 103 patients who had toxicology screens were prescribed naloxone upon discharge. More research on the associations between illicit drug use, opioids, and naloxone prescriptions is necessary to help establish guidelines for high-risk patients.

Emergency physician risk assessment practices prior to prescribing opioids

BACKGROUND

Safer opioid prescribing remains a crucial issue for emergency physicians. Policy statements and guidelines recommend deliberate risk assessment for likelihood of current or future opioid use disorder prior to prescribing opioids. However, the practice patterns of emergency physicians remain underreported.

METHODS

We surveyed emergency physicians across Canada about their local opioid prescribing policies, their practice patterns of risk assessment prior to prescribing opioids, and which clinical risk factors they find most important.

RESULTS

The response rate was 20.4% (n = 312/1532). 59.8% of respondents report usually or always assessing for risk. Physicians rely on gestalt (80.3%), targeted histories based on risk factors in the literature (55.6%) or their experience (57.6%), and reviewing medical (83.1%) and medication records (75.6%). Contacting primary prescribers is uncommon (16.3%). A minority routinely use opioid prescribing risk assessment tools (6.4%), have local opioid prescribing policies (27%), or make use of electronic medical record functions to assist risk stratifying (2.4%).

CONCLUSION

Many Canadian emergency physicians make risk assessments based on gestalt rather than identifying literature-based risk factors. This conflicts with guidelines calling for routine comprehensive assessment. Further efforts should be directed towards education in optimizing risk assessment; and towards system-level initiatives such as clear local prescribing policies, electronic-systems functionality, and developing assessment tools for use in the ED.

Drug Misuse in the Veterinary Setting: an Under-recognized Avenue

PURPOSE OF REVIEW

Prescription drug misuse is a public health concern. Governments are attempting to restrict the incidence of medication diversion by establishing laws to curb drug access from human healthcare providers. Veterinarians, who also prescribe controlled substances and see hundreds of millions of patients annually in the USA, are often overlooked as a source of prescription drug misuse.

RECENT FINDINGS

Evidence suggests that drug misuse occurs in the veterinary setting, and veterinarians acknowledge this as a common problem. Although analgesics are alleged to be the most common drug class diverted, a recent cross-sectional study suggests veterinarian opioid prescribing rate continues to increase. Prescription misuse in veterinarian settings is likely underestimated and needs to be better investigated. Human healthcare providers must familiarize themselves with this potential channel to prescription drugs and specifically question patients on veterinary drug misuse.

Prevalence and Predictors of Driving after Prescription Opioid Use in an Adult ED Sample

Introduction

Prescription opioid use and driving is a public health concern given the risks associated with drugged driving, but the issue remains under-studied. We examined the prevalence and correlates of driving after taking prescription opioids (DAPO) among adults seeking emergency department (ED) treatment.

Methods

Participants (aged 25–60) seeking ED care at a Level I trauma center completed a computerized survey. Validated instruments measured prescription opioid use, driving behaviors, and risky driving. Patients who reported past three-month prescription opioid use and drove at least twice weekly were administered an extended study survey measuring DAPO, depression, pain, and substance use.

Results

Among participants completing the screening survey (n = 756; mean age = 42.8 [standard deviation {SD} =10.4]), 37.8% reported past three-month prescription opioid use (30.8% of whom used daily), and 14.7% reported past three-month DAPO. Of screened participants, 22.5% (n = 170) were eligible for the extended study survey. Unadjusted analyses demonstrated that participants reporting DAPO were more likely to use opioids daily (51.1% vs 15.9%) and had higher rates of opioid misuse (mean Current Opioid Misuse Measure score 3.4 [SD = 3.8] vs 1.1 [SD = 2.1]) chronic pain (80.7% vs 42.7%), and driving after marijuana or alcohol use (mean intoxicated driving score 2.1 [SD = 1.3] vs 0.3 [SD = 0.8]) compared to patients not reporting DAPO (all p<0.001). Adjusting for age, gender, employment, and insurance in a logistic regression model, participants reporting DAPO were more likely to report a chronic pain diagnosis (odds ratio [OR] = 3.77, 95% confidence interval [CI], 1.55–9.17), daily opioid use (OR = 3.81, 95% CI, 1.64–8.85), and higher levels of intoxicated driving (OR = 1.62, 95% CI, 1.07–2.45). Alcohol and marijuana use, depression, and opioid misuse were not associated with DAPO in adjusted analyses.

Conclusion

Nearly one in six adult patients seeking ED care reported DAPO. The ED may be an important site for interventions addressing opioid-related drugged driving.

Change in opioid policies in New England emergency departments, 2014 vs 2018

OBJECTIVE

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.

METHODS

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).

RESULTS

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 to <10 % of patients at risk. Most EDs (74 %) reported prescribing/dispensing buprenorphine to <10 % of patients with OUD. Comparing 2018 to 2014, the greatest difference in policy use was in prescribing/dispensing naloxone (+55 %, p < 0.001).

CONCLUSION

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.

How Are Real-time Opioid Prescribing Cognitions by Emergency Providers Influenced by Reviewing the State Prescription Drug Monitoring Program?

OBJECTIVE

To understand how real-time opioid prescribing cognitions by emergency medicine (EM) providers are influenced by review of the state prescription drug monitoring program (PDMP).

METHODS

We collected prospective data from a convenience sample of 103 patient encounters for pain from 23 unique EM providers. After seeing the patient, before and immediately after reviewing the PDMP, EM providers answered how much they thought "the patient need[ed] an opioid to help manage their pain?", how concerned they were "about drug abuse and/or diversion?", and whether they planned to prescribe an opioid (yes/no). If they changed their decision to prescribe after querying the PDMP, they were asked to provide comments. We categorized encounters by opioid prescribing plan before/after PDMP review (e.g., O+/O- means plan changed from "yes" to "no") and examined changes in cognitions across categories.

RESULTS

Ninety-two of 103 (89.3%) encounters resulted in no change in opioid prescribing plan (61/92 [66.3%] O+/O+; 31/92 [33.7%] O-/O-). For the four O+/O- encounters, perceived patient opioid need decreased 75% of the time and concern for opioid abuse and/or diversion increased 75% of time. For the seven O-/O+ encounters, providers reported increased perceived patient opioid need 28.6% of the time and decreased concern for opioid abuse and/or diversion 14.3% of time.

CONCLUSIONS

PDMP data rarely alter plans to prescribe an opioid among emergency providers. When changes in opioid prescribing plan were made, this was reflected by changes in cognitions. Findings support the need for a properly powered study to identify how specific PDMP findings alter prescribing cognitions.

Physician Responses to Enhanced Prescription Drug Monitoring Program Profiles

OBJECTIVE

Many states have begun implementing enhancements to PDMP patient profiles such as summaries or graphics to highlight issues of concern and enhance comprehension. The purpose of this study was to examine how physicians respond to sample enhanced PDMP profiles based on patient vignettes.

DESIGN

Brief semistructured interviews with physicians.

SETTING

Three national medical conferences for targeted specialties.

SUBJECTS

Ninety-three physicians practicing in primary care, emergency medicine, or pain management.

METHODS

We presented participants with one of three patient vignettes with corresponding standard and enhanced PDMP profiles and conducted brief interviews.

RESULTS

Findings indicated that enhanced profiles could increase ease of comprehension, reduce time burden, and aid in communicating with patients about opioid risks. Physicians also expressed concern about liability for prescribing when the enhanced profile indicates risk and cautioned against any implication that risk warnings should override clinical judgment based on the patient's complete medical history or presenting condition. Physicians emphasized the need for transparency of measures and evidence of validation of risk scores. We found little indication that enhanced profiles would change opioid prescribing decisions, though decisions varied by physician.

CONCLUSIONS

Our study underscores the importance of involving prescribers in developing and testing PDMP profile enhancements, as well as providing guidance in the interpretation and clinical use of enhanced profiles. Reduced time burden is an important benefit to consider as the number of states mandating PDMP use increases.

Predictors of Overdose Death Among High-Risk Emergency Department Patients With Substance-Related Encounters: A Data Linkage Cohort Study

STUDY OBJECTIVE

Persons with substance use disorders frequently utilize emergency department (ED) services, creating an opportunity for intervention and referral to addiction treatment and harm-reduction services. However, EDs may not have the appropriate tools to distinguish which patients are at greatest risk for negative outcomes. We link hospital ED and medical examiner mortality databases in one state to identify individual-level risk factors associated with overdose death among ED patients with substance-related encounters.

METHODS

This retrospective cohort study linked Maryland statewide ED hospital claims records for adults with nonfatal overdose or substance use disorder encounters in 2014 to 2015 with medical examiner mortality records in 2015 to 2016. Logistic regression was used to identify factors in hospital records associated with risk of opioid overdose death. Predicted probabilities for overdose death were calculated for hypothetical patients with different combinations of overdose and substance use diagnostic histories.

RESULTS

A total of 139,252 patients had substance-related ED encounters in 2014 to 2015. Of these patients, 963 later experienced an opioid overdose death, indicating a case fatality rate of 69.2 per 10,000 patients, 6 times higher than that of patients who used the ED for any cause. Factors most strongly associated with death included having both an opioid and another substance use disorder (adjusted odds ratio 2.88; 95% confidence interval 2.04 to 4.07), having greater than or equal to 3 previous nonfatal overdoses (adjusted odds ratio 2.89; 95% confidence interval 1.54 to 5.43), and having a previous nonfatal overdose involving heroin (adjusted odds ratio 2.24; 95% confidence interval 1.64 to 3.05).

CONCLUSION

These results highlight important differences in overdose risk among patients receiving care in EDs for substance-related conditions. The findings demonstrate the potential utility of incorporating routine data from patient records to assess risk of future negative outcomes and identify primary targets for initiation and linkage to lifesaving care.

Adolescent and Parent Knowledge, Attitudes, and Perceptions of Harm of Household Controlled Medications

Introduction: Adolescents learn knowledge, attitudes, and behaviors from their parents, yet little is known about how these attributes are associated with management of household controlled prescription medications. We aimed to assess adolescent and parent: 1) knowledge and attitudes regarding household controlled medications, including previous healthcare counseling; 2) perceptions of harm of medication misuse and diversion; and 3) potential associations of these attributes with household management. Methods: This was a cross-sectional study with paired data using brief, online, confidential surveys of adolescents and parents via an adolescent medicine clinic associated with a large academic center. Eligible adolescents were aged 12-18 years old with at least one controlled prescription medication in the home. Data collection and analysis occured in 2017-2018. Results: Of the 243 adolescent-parent dyads, many adolescents and parents had: low knowledge (15%; 6%), risky attitudes (31%; 32%), received healthcare counseling on safe management of controlled medications (30%; 96%), and low perceived harm of adolescent diversion (39%; 49%). Parents practicing unsafe household management were 2.4 (95% CI = 1.3, 4.3) times as likely to have risky attitudes. Adolescents with families practicing unsafe medication management were 3.7 (95% CI = 1.1, 10.4) times as likely to have low perceptions of harm from diversion. Conclusions: Many adolescents and parents have low knowledge, risky attitudes, and low perceptions of harm of adolescent diversion, some of which are associated with unsafe household medication management. Providers should aim to utilize interventions to improve these attributes for adolescents and parents to enhance safe household medication management.

Opioid prescribing rates from the emergency department: Down but not out

INTRODUCTION

To examine opioid prescribing rates following emergency department (ED) discharge stratified by patient's clinical and demographic characteristics over an 11-year period.

MATERIAL AND METHODS

We used 3.9 million ED visits from commercially insured enrollees and 15.2 million ED visits from Medicaid enrollees aged 12 to 64 over 2005-2016 from the IBM® MarketScan® Research Databases. We calculated rates of opioid prescribing at discharge from the ED and the average number of pills per opioid prescription filled.

RESULTS

Approximately 15-20% of ED visits resulted in opioid prescriptions filled. Rates increased from 2005 into late 2009 and 2010 and then declined steadily through 2016. Prescribing rates were similar for commercially insured and Medicaid enrollees. Being aged 25-54 years was associated with the highest rates of opioid prescriptions being filled. Hydrocodone was the most commonly prescribed opioid, but rates for hydrocodone prescription filling also fell the most. Rates for oxycodone were stable, and rates for tramadol increased. The average number of pills dispensed from prescriptions filled remained steady over the study period at 18-20.

DISCUSSION

Opioid prescribing rates from the ED have declined steadily since 2010 in reversal of earlier trends; however, about 15% of ED patients still received opioid prescriptions in 2016 amidst a national opioid crisis.

CONCLUSIONS

Efforts to reduce opioid prescribing could consider focusing on the pain types, age groups, and regions with high prescription rates identified in this study.

Conversion to Persistent or High-Risk Opioid Use After a New Prescription From the Emergency Department: Evidence From Washington Medicaid Beneficiaries

STUDY OBJECTIVE

We describe the overall risk and factors associated with transitioning to persistent opioid or high-risk use after an initial emergency department (ED) opioid prescription.

METHODS

A retrospective cohort study of Washington Medicaid beneficiaries was performed with linked Medicaid and prescription drug monitoring program files. We identified adults who had no record of opioid prescriptions in the previous 12 months, and who filled a new opioid prescription within 1 day of an ED discharge in 2014. We assessed the risk of persistent opioid use or high-risk prescription fills within 12 months after the index visit. Logistic regression was used to assess the association between pertinent variables and conversion to persistent or high-risk use.

RESULTS

Among 202,807 index ED visits, 23,381 resulted in a new opioid prescription. Of these, 13.7% led to persistent or high-risk opioid prescription fills within 12 months compared with 3.2% for patients who received no opioids at the index visit. Factors associated with increased likelihood of persistent opioid or high-risk prescription fills included a history of skeletal or connective-tissue disorder; neck, back, or dental pain; and a history of prescribed benzodiazepines. The highest conversion rates (37.3%) were observed among visits in which greater than or equal to 350 morphine milligram equivalents were prescribed. Conversion rates remained greater than 10% even among visits resulting in lower-dose opioid prescriptions.

CONCLUSION

Medicaid recipients are at moderate risk for conversion to persistent or high-risk opioid use after a new ED prescription. Longer or higher-dose prescriptions are associated with increased risk for conversion; however, even visits that lead to guideline-concordant prescriptions bear some risk for long-term or high-risk use.

Association of the Use of a Mandatory Prescription Drug Monitoring Program With Prescribing Practices for Patients Undergoing Elective Surgery

Importance

Most states have adopted the routine use of a prescription drug monitoring program (PDMP) to curb overprescribing of opioids. The American College of Surgeons promotes the use of these programs as a "guiding principle to curb the opioid epidemic." However, there is a paucity of data on the effects of the use of these programs for surgical patient populations.

Objective

To determine the association of the mandatory use of a PDMP with the opioid prescribing practices for patients undergoing general surgery.

Design, Setting, and Participants

A prospective observational cohort study was conducted at an academic hospital in New Hampshire among 1057 patients undergoing representative elective general surgical procedures from July 1, 2016, to June 30, 2017.

Exposures

New state legislation mandated the use of a PDMP and opioid risk-assessment tool for all patients receiving an outpatient opioid prescription in New Hampshire beginning January 1, 2017. The electronic medical prescribing system was modified to facilitate and support compliance with the new requirements.

Main Outcomes and Measures

Change in opioid prescribing practices after January 1, 2017, and time to complete PDMP requirements.

Results

Among the 1057 patients (569 women [53.8%] and 488 men [46.2%]; mean [SD] age, 56.8 [15.4] years), the percentage of patients prescribed opioids after surgery did not decrease significantly (429 of 536 [80.0%] before the new requirements vs 401 of 521 [77.0%] after the requirements; P = .29). The mean number of opioid pills prescribed decreased from 30.8 to 24.0 (22.1%) in the 6 months prior to the mandatory PDMP requirement; the rate of decrease was actually less (from 22.8 to 21.9 pills [3.9%]) in the 6 months after the legislation. These new requirements did not identify any high-risk patients who subsequently were not prescribed opioids. The query and opioid abuse risk calculator together took a median time of 7 minutes (range, 2-17 minutes) to complete.

Conclusions and Relevance

A mandatory PDMP query requirement was not significantly associated with the overall rate of opioid prescribing or the mean number of pills prescribed for patients undergoing general surgical procedures. In no cases was a high-risk patient identified, leading to avoidance of an opioid prescription. A PDMP can be a useful adjunct in certain settings, but this study found that it did not have the intended effect in a population undergoing elective surgical procedures. Legislative efforts to mandate PDMP use should be targeted to populations in which benefit can be demonstrated.

Predicting opioid use disorder in patients with chronic pain who present to the emergency department

Background

Emergency department (ED) patients with chronic pain challenge providers to make quick and accurate assessments without an in-depth pain management consultation. Emergency physicians need reliable means to determine which patients may receive opioid therapy without exacerbating opioid use disorder (OUD).

Methods

Eighty-nine ED patients with a chief complaint of chronic pain were enrolled. Researchers administered questionnaires and reviewed medical and state prescription monitoring database information. Participants were classified as either OUD or non-OUD. Statistical analysis included a bivariate analysis comparing differences between groups and multivariate logistic regression evaluating ORs.

Results

The 45 participants categorised as OUD had a higher proportion of documented or reported psychiatric diagnoses (p=0.049), preference of opioid treatment (p=0.005), current oxycodone prescription (p=0.043), borrowed pain medicine (p=0.004) and non-authorised dose increase (p<0.001). The state prescription monitoring database revealed the OUD group to have an increased number of opioid prescriptions (p=0.005) and pills (p=0.010). Participants who borrowed pain medicine and engaged in non-authorised dose increase were 5.2 (p=0.025, 95% CI 1.24 to 21.9) and 6.1 times (p=0.001, 95% CI 1.55 to 24.1) more likely to have OUD, respectively.

Limitations

Major limitations of our study include a small sample size, self-reported measures and convenience sample which may introduce selection bias.

Conclusion

Patients with chronic pain with OUD have distinguishable characteristics. Emergency physicians should consider such evidence-based variables prior to opioid therapy to ameliorate the opioid crisis and limit implicit bias.

Techniques to Shorten a Screening Tool for Emergency Department Patients

Introduction

Screening of patients for opioid risk has been recommended prior to opioid prescribing. Opioids are prescribed frequently in the emergency department (ED) setting, but screening tools are often of significant length and therefore limited in their utility. We describe and evaluate three approaches to shortening a screening tool: creation of a short form; curtailment; and stochastic curtailment.

Methods

To demonstrate the various shortening techniques, this retrospective study used data from two studies of ED patients for whom the provider was considering providing an opioid prescription and who completed the Screener and Opioid Assessment for Patients with Pain-Revised, a 24-item assessment. High-risk criteria from patients’ prescription drug monitoring program data were used as an endpoint. Using real-data simulation, we determined the sensitivity, specificity, and test length of each shortening technique.

Results

We included data from 188 ED patients. The original screener had a test length of 24 questions, a sensitivity of 44% and a specificity of 76%. The 12-question short form had a sensitivity of 41% and specificity of 75%. Curtailment and stochastic curtailment reduced the question length (mean test length ranging from 8.1–19.7 questions) with no reduction in sensitivity or specificity.

Conclusion

In an ED population completing computer-based screening, the techniques of curtailment and stochastic curtailment markedly reduced the screening tool’s length but had no effect on test characteristics. These techniques can be applied to improve efficiency of screening patients in the busy ED environment without sacrificing sensitivity or specificity.

Identifying and classifying opioid-related overdoses: A validation study

PURPOSE

The study aims to develop and validate algorithms to identify and classify opioid overdoses using claims and other coded data, and clinical text extracted from electronic health records using natural language processing (NLP).

METHODS

Primary data were derived from Kaiser Permanente Northwest (2008-2014), an integrated health care system (~n > 475 000 unique individuals per year). Data included International Classification of Diseases, Ninth Revision (ICD-9) codes for nonfatal diagnoses, International Classification of Diseases, Tenth Revision (ICD-10) codes for fatal events, clinical notes, and prescription medication records. We assessed sensitivity, specificity, positive predictive value, and negative predictive value for algorithms relative to medical chart review and conducted assessments of algorithm portability in Kaiser Permanente Washington, Tennessee State Medicaid, and Optum.

RESULTS

Code-based algorithm performance was excellent for opioid-related overdoses (sensitivity = 97.2%, specificity = 84.6%) and classification of heroin-involved overdoses (sensitivity = 91.8%, specificity = 99.0%). Performance was acceptable for code-based suicide/suicide attempt classifications (sensitivity = 70.7%, specificity = 90.5%); sensitivity improved with NLP (sensitivity = 78.7%, specificity = 91.0%). Performance was acceptable for the code-based substance abuse-involved classification (sensitivity = 75.3%, specificity = 79.5%); sensitivity improved with the NLP-enhanced algorithm (sensitivity = 80.5%, specificity = 76.3%). The opioid-related overdose algorithm performed well across portability assessment sites, with sensitivity greater than 96% and specificity greater than 84%. Cross-site sensitivity for heroin-involved overdose was greater than 87%, specificity greater than or equal to 99%.

CONCLUSIONS

Code-based algorithms developed to detect opioid-related overdoses and classify them according to heroin involvement perform well. Algorithms for classifying suicides/attempts and abuse-related opioid overdoses perform adequately for use for research, particularly given the complexity of classifying such overdoses. The NLP-enhanced algorithms for suicides/suicide attempts and abuse-related overdoses perform significantly better than code-based algorithms and are appropriate for use in settings that have data and capacity to use NLP.

The utility of a statewide prescription drug-monitoring database vs the Current Opioid Misuse Measure for identifying drug-aberrant behaviors in emergency department patients already on opioids

BACKGROUND

The most recent guidelines on prescribing opioids from the United States Centers for Disease Control recommend that clinicians not prescribe opioids as first-line therapy for chronic non-cancer pain. If an opioid prescription is considered for a patient already on opioids, prescribers are encouraged to check the statewide prescription drug monitoring database (PDMP). Some additional guidelines recommend screening tools such as the Current Opioid Misuse Measure (COMM) which may also help identify drug-aberrant behaviors.

OBJECTIVE

To compare the PDMP and the Current Opioid Misuse Measure (COMM), a commonly-recommended screening tool for patients on opioids, in detecting drug-aberrant behaviors in patients already taking opioids at the time of ED presentation.

METHODS

Patients on opioids were enrolled prospectively in a mixed urban-suburban ED seeing approximately 65,000 patients per year. The sensitivity, specificity, likelihood ratios, and diagnostic odds ratios of the PDMP and COMM were compared against objective criteria of drug-aberrant behaviors as documented in the electronic medical record (EMR) and medical examiner databases.

RESULTS

Compared to the COMM, the PDMP had similar sensitivity (36% vs 45%) and similar specificity (79% vs 55%), but better positive predictive value, better negative predictive value, and better diagnostic odds ratio. The combination of the PDMP and the COMM did not improve the detection of drug-aberrant behaviors.

CONCLUSIONS

The PDMP alone is a more useful as a screening instrument than either the COMM or the combination of the PDMP plus COMM in patients already taking opioids at time of ED presentation. However, the PDMP misses a majority of patients with documented drug-aberrant behaviors in the EMR, and should not be used in isolation to justify whether a particular opioid prescription is appropriate.

Screening Tools Validated in the Outpatient Pain Management Setting Poorly Predict Opioid Misuse in the Emergency Department: A Pilot Study

BACKGROUND

Currently, no universally accepted methods exist to assess drug-related aberrant behaviors in emergency department (ED) patients. There are several screening tools to identify opioid misuse in patients with chronic pain, however, the validity of these screening tools to assess for misuse within the ED remains unclear.

OBJECTIVES

This study investigated the effectiveness of three commonly used screening tools, previously validated in outpatient pain management settings, to assess risk of opioid misuse in ED patients.

METHODS

This was a prospective observational study of 154 participants (median age 50 years; 49.6% female) presenting to an academic ED for a chief complaint of pain ≥ 6 months or an opioid refill request. Participants completed the Opioid Risk Tool, the Screener and Opioid Assessment for Patients with Pain-Revised, and the Current Opioid Misuse Measure. Scores for each were compared with electronic medical record (EMR) data alone or a reference standard comprising EMR + statewide prescription drug monitoring program (PDMP) + medical examiner database.

RESULTS

Using the combined reference standard, 55.8% of participants displayed at least one aberrant behavior. Regardless of the reference standard, the test characteristics of these screening tools were modest at best, with likelihood ratios close to 1.

CONCLUSION

Three screening tools previously validated in outpatient pain management settings poorly categorized risk among ED patients with chronic noncancer pain or requests for opioid refills, and should not be used to assess drug-aberrant behaviors in the ED. Review of the EMR alone or together with the PDMP may be more useful methods to assess drug-aberrant behaviors in the ED setting.

Characteristics and Red Flag Correlates of Psychiatric Outpatients in a Mandated-Use Prescription Drug Monitoring Program State: A PBRN Card Study

Objectives

All 50 states have implemented a Prescription Drug Monitoring Program (PDMP) in efforts to control prescription drug abuse. Many now mandate PDMP checks before clinicians prescribe controlled substances. The aim of this study was to characterize the associations between patient characteristics, red flags found on PDMP reports, and prescriber behavior at community mental health agencies.

Methods

Prescribers at 9 practice sites, in five regional community mental health centers, were recruited by a practice-based research network (PBRN) to participate in a Card Study. Prescribers completed a PDMP attitudes survey, and cards were completed for patients who had PDMP reports checked. Data were analyzed using descriptive and inferential statistics.

Results

Thirty nine providers completed cards for n=249 unique patient encounters. Over 1/3 of all patients reported an addiction disorder (38%) or a diagnosis of chronic pain (34%). Twenty percent of PDMP reports were found to have red flags, most commonly multiple prescribers or multiple pharmacies. Red flags were associated with race (p<.0.05), presence of chronic pain (p<0.01), presence of an addiction diagnosis (p<0.05), use of opioids (p<0.001), and non-adherence with treatment (p<0.006). Among prescribers, red flags were associated with lower prescribing rates (p<0.01), and decisions to decrease dosage (p<0.002).

Conclusions

Red flags were commonly found on PDMP reports done in community mental health settings, and were associated with important patient characteristics and diagnostic factors. PBRN research methods can be leveraged to obtain real-time observational data about psychiatric prescribers' use of PDMP reports in clinical decision-making in different settings.

Subtle scales: An avenue for identification of prescription drug abuse

Prescription drug abuse and diversion behavior is sustained by overprescribing of abuse-liable substances. Individuals who intend to abuse or divert prescriptions can feign symptoms easily and effectively. Efforts to identify such faking behavior have been lacking because most drug abuse screening tools and self-reported symptom inventories are known to have poor sensitivities to faking. This paper makes the case for the potential of subtle scales in the identification of faking behavior. Subtlety in scale development is the degree to which the psychopathological meaning of an item can be determined in an a priori fashion. Scales containing subtle items, such as the Minnesota Multiphasic Personality Inventory and the Substance Abuse Subtle Screening Inventory, have traditionally shown only moderate sensitivity to faking due to the lack of a tailored and focused approach. This paper provides a guide for the development of a subtle scale that is tailored to a specific condition and using sound measurement theory, a theoretical framework, and knowledge derived from literature. The Accuracy of Knowledge framework proposed by Lanyon is presented along with its application to the development of a subtle scale. Further, specific recommendations have been provided for the various steps involved in the development of a subtle scale including item development, sample selection, item refinement, and scale scoring. Use of well-developed subtle scales can present opportunities to reduce overprescribing, over-diagnosis, and help in the early identification of abuse behavior for targeted interventions. We conclude by presenting opportunities, scope, and possible avenues for research within the cultural context of the United States.

Provider perceptions of system-level opioid prescribing and addiction treatment policies

Stakeholders have implemented a multitude of system-level policies to address the U.S. opioid overdose epidemic. Because opioid prescribing partly fueled the crisis and because prescribing of medications for opioid addiction treatment is a key prevention strategy, it is critical to understand prescriber perceptions of policies in these domains. This article reviews prescriber awareness and opinions of the following system-level policies: opioid prescribing guidelines, prescription drug monitoring programs (PDMPs), medications for addiction treatment, and naloxone distribution programs. Most providers are aware of these policies, especially PDMPs, albeit a smaller proportion actively participate in their implementation. Low engagement in certain system-level policies is concerning and deserves attention, given that prescribers play an integral role in achieving optimal impact and mitigating the crisis.

Predicting opioid dependence from electronic health records with machine learning

BACKGROUND

The opioid epidemic in the United States is averaging over 100 deaths per day due to overdose. The effectiveness of opioids as pain treatments, and the drug-seeking behavior of opioid addicts, leads physicians in the United States to issue over 200 million opioid prescriptions every year. To better understand the biomedical profile of opioid-dependent patients, we analyzed information from electronic health records (EHR) including lab tests, vital signs, medical procedures, prescriptions, and other data from millions of patients to predict opioid substance dependence.

RESULTS

We trained a machine learning model to classify patients by likelihood of having a diagnosis of substance dependence using EHR data from patients diagnosed with substance dependence, along with control patients with no history of substance-related conditions, matched by age, gender, and status of HIV, hepatitis C, and sickle cell disease. The top machine learning classifier using all features achieved a mean area under the receiver operating characteristic (AUROC) curve of ~ 92%, and analysis of the model uncovered associations between basic clinical factors and substance dependence. Additionally, diagnoses, prescriptions, and procedures prior to the diagnoses of substance dependence were analyzed to elucidate the clinical profile of substance-dependent patients, relative to controls.

CONCLUSIONS

The predictive model may hold utility for identifying patients at risk of developing dependence, risk of overdose, and opioid-seeking patients that report other symptoms in their visits to the emergency room.

Detecting aberrant opioid behavior in the emergency department: a prospective study using the screener and Opioid Assessment for Patients with Pain-Revised (SOAPP®-R), Current Opioid Misuse Measure (COMM)™, and provider gestalt

Emergency department (ED) providers have limited time to evaluate patients at risk for opioid misuse. A validated tool to assess the risk for aberrant opioid behavior may mitigate adverse sequelae associated with prescription opioid misuse. We sought to determine if SOAPP-R, COMM, and provider gestalt were able to identify patients at risk for prescription opioid misuse as determined by pharmacy records at 12 months. We conducted a prospective observational study of adult patients in a high volume US ED. Patients completed the SOAPP-R and COMM, and treating EM providers evaluated patients' opioid misuse risk. We performed variable-centered, person-centered, and hierarchical cluster analyses to determine whether provider gestalt, SOAPP-R, or COMM, or a combination, predicted higher misuse risk. The primary outcome was the number of opioid prescriptions at 12 months according to pharmacy records. For 169 patients (mean age 43 years, 51% female, 73% white), correlation analysis showed a strong relationship between SOAPP-R and COMM with predicting the number of opioid prescriptions dispensed at 12 months. Provider scores estimating opioid misuse were not related to SOAPP-R and only weakly associated with COMM. In our adjusted regression models, provider gestalt and SOAPP-R uniquely predicted opioid prescriptions at 6 and 12 months. Using designated cutoff scores, only SOAPP-R detected a difference in the number of opioid prescriptions. Cluster analysis revealed that provider gestalt, SOAPP-R, and COMM scores jointly predicted opioid prescriptions. Provider gestalt and self-report instruments uniquely predicted the number of opioid prescriptions in ED patients. A combination of gestalt and self-assessment scores can be used to identify at-risk patients who otherwise miss the cutoff scores for SOAPP-R and COMM.

Screening emergency department patients for opioid drug use: A qualitative systematic review

INTRODUCTION

The opioid drug epidemic is a major public health concern and an economic burden in the United States. The purpose of this systematic review is to assess the reliability and validity of screening instruments used in emergency medicine settings to detect opioid use in patients and to assess psychometric data for each screening instrument.

METHODS

PubMed/MEDLINE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Web of Science, Cumulative Index to Nursing and Allied Health Literature and ClinicalTrials.gov were searched for articles published up to May 2018. The extracted articles were independently screened for eligibility by two reviewers. We extracted 1555 articles for initial screening and 95 articles were assessed for full-text eligibility. Six articles were extracted from the full-text assessment.

RESULTS

Six instruments were identified from the final article list: Screener and Opioid Assessment for Patients with Pain - Revised; Drug Abuse Screening Test; Opioid Risk Tool; Current Opioid Misuse Measure; an Emergency Medicine Providers Clinician Assessment Questionnaire; and an Emergency Provider Impression Data Collection Form. Screening instrument characteristics, and reliability and validity data were extracted from the six studies. A meta-analysis was not conducted due to heterogeneity between the studies.

CONCLUSIONS

There is a lack of validity and reliability evidence in all six articles; and sensitivity, specificity and predictive values varied between the different instruments. These instruments cannot be validated for use in emergency medicine settings. There is no clear evidence to state which screening instruments are appropriate for use in detecting opioid use disorders in emergency medicine patients. There is a need for brief, reliable, valid and feasible opioid use screening instruments in the emergency medicine setting.

Past-year Prescription Drug Monitoring Program Opioid Prescriptions and Self-reported Opioid Use in an Emergency Department Population With Opioid Use Disorder

BACKGROUND

Despite increasing reliance on prescription drug monitoring programs (PDMPs) as a response to the opioid epidemic, the relationship between aberrant drug-related behaviors captured by the PDMP and opioid use disorder is incompletely understood. How PDMP data should guide emergency department (ED) assessment has not been studied.

OBJECTIVES

The objective was to evaluate a relationship between PDMP opioid prescription records and self-reported nonmedical opioid use of prescription opioids in a cohort of opioid-dependent ED patients enrolled in a treatment trial.

METHODS

PDMP opioid prescription records during 1 year prior to study enrollment on 329 adults meeting Diagnostic and Statistical Manual IV criteria for opioid dependence entering a randomized clinical trial in a large, urban ED were cross-tabulated with data on 30-day nonmedical prescription opioid use self-report. The association among these two types of data was assessed by the Goodman and Kruskal's gamma; a logistic regression was used to explore characteristics of participants who had PDMP record of opioid prescriptions.

RESULTS

During 1 year prior to study enrollment, 118 of 329 (36%) patients had at least one opioid prescription (range = 1-51) in our states' PDMP. Patients who reported ≥15 of 30 days of nonmedical prescription opioid use were more likely to have at least four PDMP opioid prescriptions (20/38; 53%) than patients reporting 1 to 14 days (14/38, 37%) or zero days of nonmedical prescription opioid use (4/38, 11%; p = 0.002). Female sex and having health insurance were significantly more represented in the PDMP (p < 0.05 for both).

CONCLUSION

PDMPs may be helpful in identifying patients with certain aberrant drug-related behavior, but are unable to detect many patients with opioid use disorder. The majority of ED patients with opioid use disorder were not captured by the PDMP, highlighting the importance of using additional methods such as screening and clinical history to identify opioid use disorders in ED patients and the limitations of PDMPs to detect opioid use disorders.

Clinicians' Use of Prescription Drug Monitoring Programs in Clinical Practice and Decision-Making

Objectives

Little is known about clinicians' use of prescription drug monitoring program (PDMP) profiles in decision-making. The objective of this qualitative study was to understand how clinicians use, interpret, and integrate PDMP profiles with other information in making clinical decisions.

Design

Qualitative interviews of clinician PDMP users.

Setting

Oregon registrants in the state's PDMP.

Subjects

Thirty-three clinicians practicing in primary care, emergency medicine, pain management, psychiatry, dentistry, and surgery.

Methods

We conducted semistructured telephone interviews with PDMP users. A multidisciplinary team used a grounded theory approach to identify patterns of PDMP use and how PDMP profiles influence clinical decisions.

Results

PDMP use varied from consistent monitoring to checking the PDMP only on suspicion of misuse, with inconsistent use reported particularly among short-term prescribers. Primary care clinicians reported less routine use with existing pain patients than with new patients. In response to worrisome PDMP profiles with new patients, participants reported declining to prescribe, except in the case of acute, verifiable conditions. Long-term prescribers reported sometimes continuing prescriptions for existing patients depending on perceived patient intent, honesty, and opioid misuse risk. Some long-term prescribers reported discharging patients from their practices due to worrisome PDMP profiles; others expressed strong ethical grounds for retaining patients but discontinuing controlled substances.

Conclusion

Greater consistency is needed in use of PDMP in monitoring existing patients and in conformity to guidelines against discharging patients from practice. Research is needed to determine optimal approaches to interpreting PDMP profiles in relation to clinical judgment, patient screeners, and other information.

Effect of Automated Prescription Drug Monitoring Program Queries on Emergency Department Opioid Prescribing

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.

Managing Concerning Behaviors in Patients Prescribed Opioids for Chronic Pain: A Delphi Study

BACKGROUND

Current guideline-recommended monitoring of patients prescribed long-term opioid therapy (LTOT) for chronic pain will likely result in increased identification of behaviors of concern for misuse and addiction, but there is a dearth of empiric evidence about how these behaviors should be managed.

OBJECTIVE

To establish expert consensus about treatment approaches for common and challenging concerning behaviors that arise among patients on LTOT.

DESIGN

We used a Delphi approach, which allows for generation of consensus.

PARTICIPANTS

Participants were clinical experts in chronic pain and opioid prescribing recruited from professional societies and other expert groups.

MAIN MEASURES

The Delphi process was conducted online, and consisted of an initial brainstorming round to identify common and challenging behaviors, a second round to identify management strategies for each behavior, and two rounds to establish consensus and explore disagreement/uncertainty.

KEY RESULTS

Forty-two participants completed round 1, 22 completed round 2, 30 completed round 3, and 28 completed round 4. Half of round 1 participants were female (52%), and the majority were white (83%). Most (71%) were physicians, and most participants practiced in academic primary (40%) or specialty care (19%).The most frequently cited common and challenging behaviors were missing appointments, taking opioids for symptoms other than pain, using more opioid medication than prescribed, asking for an increase in opioid dose, aggressive behavior, and alcohol and other substance use. Across behaviors, participants agreed that patient education and information gathering were important approaches. Participants also agreed that stopping opioids is not important initially, but if initial approaches do not work, tapering opioids and stopping opioids immediately may become important approaches.

CONCLUSIONS

This study presents clinical expert consensus on how to manage concerning behaviors among patients on LTOT. Future research is needed to investigate how implementing these management strategies would impact patient outcomes, practice and policy.

The current utilization and perceptions of prescription drug monitoring programs among emergency medicine providers in Florida

BACKGROUND

Pain is among the most commonly treated symptoms in the emergency department, and opioids are commonly prescribed from the emergency department to treat moderate to severe pain. Prescription drug monitoring programs (PDMP) can be used to assist physicians identify individuals at increased risk to misuse or abuse opioids. While the use of the PDMP has been shown useful among clinicians, in the past, utilization of the PDMP has been less than optimal. The objective of this study was to assess the current utilization and perceptions of the prescription drug monitoring program among emergency medicine providers in Florida.

METHODS

A survey assessing the utilization and perception of Florida's prescription drug monitoring program was distributed to emergency medicine providers in Florida over a 5 week period. Attending physicians, physicians in training, and extenders from a variety of practice types were assessed.

RESULTS

A total of 88 surveys were completed. Over two thirds (67%) of the respondents were male. The majority of respondents were attending physicians (62%), 13 (14%) were residents, and 21 (23%) were extenders. Nearly all (99%) were aware of Electronic-Florida Online Reporting of Controlled Substance Evaluation Program (EFORCSE) and 84% had registered accounts. More than 2/3 (73%) reported feeling pressured to prescribe opioids, and 70% reported receiving no formal education on identifying individuals at increased risk of opioid misuse. Approximately half (51%) reported that they used EFORCSE only when they suspect the patient may misuse the medication, 21% reported that they rarely used EFORCSE, and only 3% reported using PDMP every time that they prescribed opioids. Residents used PDMP less frequently than extenders and attending physicians. The most common barriers associated with PDMP use were related to access.

CONCLUSIONS

Although most providers reported that they were aware of their states' PDMP, utilization of the PDMP among emergency medicine providers in Florida remains low. Low utilization was associated with barriers to access. If further enhancements to PDMPs can be made to improve accessibility, then rates of PDMP utilization may increase.

What Factors Affect Physicians' Decisions to Prescribe Opioids in Emergency Departments?

Objective: With 42% of all emergency department visits in the United States related to pain, physicians who work in this setting are tasked with providing adequate pain management to patients with varying primary complaints and medical histories. Complicating this, the United States is in the midst of an opioid overdose epidemic. State governments and national organizations have developed guidelines and legislation to curtail opioid prescriptions in acute care settings, while also incentivizing providers for patient satisfaction and completeness of pain control. In order to inform future policies that focus on provider pain medication prescribing, we sought to characterize the factors physicians weigh when considering treating pain with opioids in the emergency department. Methods: We conducted and transcribed open-ended, semistructured qualitative interviews with 52 physicians at a national emergency medicine conference. Results: Participants reported a wide range of factors contributing to their opioid prescribing patterns related to three domains: 1) provider assessment of pain characteristics, 2) patient-based considerations, and 3) practice environment. Pain characteristics include the characteristics of various acute and chronic pain syndromes, including physicians’ empathy due to their own experiences with pain. Patient characteristics include “trustworthiness,” race and ethnicity, and the concern for risk of misuse. Factors related to the practice environment include hospital policy, legislation/regulation, and guidelines. Conclusion: The decision to prescribe opioids to patients in the emergency department is complex and nuanced. Physicians are interested in guidance and are concerned about the competing pressures placed on their opioid prescribing due to incentives related to patient satisfaction scores on one hand and inflexible policies that do not allow for individualized, patient-centered decisions on the other.

An investigation of completion times on the Screener and Opioid Assessment for Patients with Pain - revised (SOAPP-R)

Background

Respondents’ scores to the Screener and Opioid Assessment for Patients with Pain – revised (SOAPP-R) have been shown to be predictive of aberrant drug-related behavior (ADB). However, research is lacking on whether an individual’s completion time (the amount of time that he/she takes to finish the screener) has utility in predicting ADB, despite the fact that response speed has been useful in predicting behavior in other fields. The purpose of this study was to evaluate the degree to which SOAPP-R completion time is predictive of ADB.

Materials and methods

This retrospective study analyzed completion-time data from 82 adult emergency department patients who completed the SOAPP-R on a tablet computer. The utility of SOAPP-R completion times in predicting ADB was assessed via logistic regression and the area under the curve (AUC) statistic. An external measure of ADB using Prescription Drug Monitoring Program data defined ADB to have occurred in individuals with at least four opioid prescriptions and at least four prescribers in 12 months.

Results

Although there was a slight trend for individuals with greater completion times to have greater odds of ADB (odds ratio 1.004 in simple logistic regression), the association between SOAPP-R completion time and ADB was not statistically significant in either simple logistic regression (P=0.307) or multiple logistic regression adjusting for SOAPP-R score (P=0.419). AUC values for the prediction of ADB using completion time alone, SOAPP-R score alone, and both completion time and SOAPP-R score were 0.63, 0.64, and 0.65, respectively.

Conclusion

There was no significant evidence that SOAPP-R completion times were predictive of ADB among emergency department patients. However, the AUC value for completion times was only slightly less than that for SOAPP-R total scores.

Enhancing health care equity with Indigenous populations: evidence-based strategies from an ethnographic study

BACKGROUND

Structural violence shapes the health of Indigenous peoples globally, and is deeply embedded in history, individual and institutional racism, and inequitable social policies and practices. Many Indigenous communities have flourished, however, the impact of colonialism continues to have profound health effects for Indigenous peoples in Canada and internationally. Despite increasing evidence of health status inequities affecting Indigenous populations, health services often fail to address health and social inequities as routine aspects of health care delivery. In this paper, we discuss an evidence-based framework and specific strategies for promoting health care equity for Indigenous populations.

METHODS

Using an ethnographic design and mixed methods, this study was conducted at two Urban Aboriginal Health Centres located in two inner cities in Canada, which serve a combined patient population of 5,500. Data collection included in-depth interviews with a total of 114 patients and staff (n = 73 patients; n = 41 staff), and over 900 h of participant observation focused on staff members' interactions and patterns of relating with patients.

RESULTS

Four key dimensions of equity-oriented health services are foundational to supporting the health and well-being of Indigenous peoples: inequity-responsive care, culturally safe care, trauma- and violence-informed care, and contextually tailored care. Partnerships with Indigenous leaders, agencies, and communities are required to operationalize and tailor these key dimensions to local contexts. We discuss 10 strategies that intersect to optimize effectiveness of health care services for Indigenous peoples, and provide examples of how they can be implemented in a variety of health care settings.

CONCLUSIONS

While the key dimensions of equity-oriented care and 10 strategies may be most optimally operationalized in the context of interdisciplinary teamwork, they also serve as health equity guidelines for organizations and providers working in various settings, including individual primary care practices. These strategies provide a basis for organizational-level interventions to promote the provision of more equitable, responsive, and respectful PHC services for Indigenous populations. Given the similarities in colonizing processes and Indigenous peoples' experiences of such processes in many countries, these strategies have international applicability.

A Call for Better Opioid Prescribing Training and Education

Pain is the most common complaint in the emergency department (ED), and emergency physicians face unique challenges in making opioid-related treatment decisions. Medical students and residents experience significant variation in the quality of education they receive both about opioid prescribing as well as substance-use detection and intervention in the ED. To achieve a better standard of education, clinical educators will need to (a) develop a clearer understanding of the risk for aberrant opioid prescribing in the ED, (b) recognize prescribing bias and promote uptake of evidence-based opioid prescribing guidelines in their EDs, and

A Randomized Controlled Trial of a Citywide Emergency Department Care Coordination Program to Reduce Prescription Opioid Related Emergency Department Visits

BACKGROUND

Increasing prescription overdose deaths have demonstrated the need for safer emergency department (ED) prescribing practices for patients who are frequent ED users.

OBJECTIVES

We hypothesized that the care of frequent ED users would improve using a citywide care coordination program combined with an ED care coordination information system, as measured by fewer ED visits by and decreased controlled substance prescribing to these patients.

METHODS

We conducted a multisite randomized controlled trial (RCT) across all EDs in a metropolitan area; 165 patients with the most ED visits for complaints of pain were randomized. For the treatment arm, drivers of ED use were identified by medical record review. Patients and their primary care providers were contacted by phone. Each patient was discussed at a community multidisciplinary meeting where recommendations for ED care were formed. The ED care recommendations were stored in an ED information exchange system that faxed them to the treating ED provider when the patient presented to the ED. The control arm was subjected to treatment as usual.

RESULTS

The intervention arm experienced a 34% decrease (incident rate ratios = 0.66, p < 0.001; 95% confidence interval 0.57-0.78) in ED visits and an 80% decrease (odds ratio = 0.21, p = 0.001) in the odds of receiving an opioid prescription from the ED relative to the control group. Declines of 43.7%, 53.1%, 52.9%, and 53.1% were observed in the treatment group for morphine milligram equivalents, controlled substance pills, prescriptions, and prescribers, respectively.

CONCLUSION

This RCT showed the effectiveness of a citywide ED care coordination program in reducing ED visits and controlled substance prescribing.

Racial-Ethnic Disparities in Opioid Prescriptions at Emergency Department Visits for Conditions Commonly Associated with Prescription Drug Abuse

Prescription drug abuse is a growing problem nationally. In an effort to curb this problem, emergency physicians might rely on subjective cues such as race-ethnicity, often unknowingly, when prescribing opioids for pain-related complaints, especially for conditions that are often associated with drug-seeking behavior. Previous studies that examined racial-ethnic disparities in opioid dispensing at emergency departments (EDs) did not differentiate between prescriptions at discharge and drug administration in the ED. We examined racial-ethnic disparities in opioid prescription at ED visits for pain-related complaints often associated with drug-seeking behavior and contrasted them with conditions objectively associated with pain. We hypothesized a priori that racial-ethnic disparities will be present among opioid prescriptions for conditions associated with non-medical use, but not for objective pain-related conditions. Using data from the National Hospital Ambulatory Medical Care Survey for 5 years (2007-2011), the odds of opioid prescription during ED visits made by non-elderly adults aged 18-65 for 'non-definitive' conditions (toothache, back pain and abdominal pain) or 'definitive' conditions (long-bone fracture and kidney stones) were modeled. Opioid prescription at discharge and opioid administration at the ED were the primary outcomes. We found significant racial-ethnic disparities, with non-Hispanic Blacks being less likely (adjusted odds ratio ranging from 0.56-0.67, p-value < 0.05) to receive opioid prescription at discharge during ED visits for back pain and abdominal pain, but not for toothache, fractures and kidney stones, compared to non-Hispanic whites after adjusting for other covariates. Differential prescription of opioids by race-ethnicity could lead to widening of existing disparities in health, and may have implications for disproportionate burden of opioid abuse among whites. The findings have important implications for medical provider education to include sensitization exercises towards their inherent biases, to enable them to consciously avoid these biases from defining their practice behavior.

Emergency Department Opioid Prescribing Practices for Chronic Pain: a 3-Year Analysis

Chronic pain is a common reason for emergency department (ED) visits. Our objective was to describe opioid prescribing practices of ED providers when treating patients with chronic pain. We retrospectively evaluated opioid prescriptions from EDs at two tertiary care military hospitals. We queried the outpatient record database to obtain a list of opioid medications prescribed and ICD-9 codes associated with visits for chronic pain. We collected provider type and gender, number of pills, opioid type, and refills. We compared the incidence with chi-square or Fisher's exact tests. Wilcoxon test was used for non-parametric continuous variables. Over 3 years, 28,103 visits generated an opioid prescription. One thousand three hundred twenty-two visits were associated with chronic pain, and 443 (33 %) visits were associated with an opioid prescription. Providers were 79 % physicians, 19 % physician assistants (PAs), 81 % male, and 69 % active duty military. Medications were 43 % oxycodone, 30 % hydrocodone, 9.5 % tramadol, 2.5 % codeine, and 15 % other. The number of pills was 20 [interquartile range (IQR) 15-30] (range 1-240), morphine equivalents (M.E.) per pill was 7.5 [7.5-7.5] (2.5-120) and total M.E. per prescription was 150 [112.5-270] (15-6000). Physicians were more likely to prescribe a non-opioid than PAs (77 vs 45 %, p < 0.0001). Civilian providers were more likely to prescribe an opioid than active duty providers (58 vs 42 %, p < 0.0001). Providers prescribed a median of 20 pills per prescription and most commonly prescribed oxycodone. PAs were more likely to prescribe an opioid for chronic pain than physicians. Civilian providers were more likely to prescribe an opioid than active duty providers.