Regulating opioid prescribing to provide access to effective treatment while minimizing diversion: an overdue topic for research

Racial inequities in opioid use disorder management: can the anesthesiologist improve outcomes?

Opportunities for Prevention and Intervention of Opioid Overdose in the Emergency Department

To reverse adverse outcomes associated with the illicit use of prescription opiates, guidelines are needed to address prescription practices for such drugs, experts say.

To investigate associations of lifetime history of traumatic brain injury (TBI) with prescription opioid use and misuse among noninstitutionalized adults. Ohio Behavioral Risk Factor Surveillance System (BRFSS) participants in the 2018 cohort who completed the prescription opioid and lifetime history of TBI modules (n = 3448). Secondary analyses of a statewide population-based cross-sectional survey. Self-report of a lifetime history of TBI using an adaptation of the Ohio State University TBI-Identification Method. Self-report of past year: (1) prescription pain medication use (ie, prescription opioid use); and (2) prescription opioid misuse, defined as using opioids more frequently or in higher doses than prescribed and/or using a prescription opioid not prescribed to the respondent. In total, 22.8% of adults in the sample screened positive for a lifetime history of TBI. A quarter (25.5%) reported past year prescription opioid use, and 3.1% met criteria for prescription opioid misuse. A lifetime history of TBI was associated with increased odds of both past year prescription opioid use (adjusted odds ratio [AOR] = 1.52; 95% CI, 1.27-1.83; P < .01) and prescription opioid misuse (AOR = 1.65; 95% CI, 1.08-2.52; P < .05), controlling for sex, age, race/ethnicity, and marital status. Results from this study support the "perfect storm" hypothesis-that persons with a history of TBI are at an increased risk for exposure to prescription opioids and advancing to prescription opioid misuse compared with those without a history of TBI. Routine screening for a lifetime history of TBI may help target efforts to prevent opioid misuse among adults.

Preventing Prescription Opioid Overdose Deaths

Adolescent prescription opioid misuse, illicit opioid use and overdose

New Persistent Opioid Use After Surgery: A Risk Factor for Opioid Use Disorder?

Individuals with opioid use disorder (OUD) may experience worsening sleep quality over time, and a subset of individuals may have sleep disturbances that precede opioid use and do not resolve following abstinence. The purpose of the present study was to (1) collect retrospective reports of sleep across the lifespan and (2) identify characteristics associated with persistent sleep disturbance and changes in sleep quality in persons with OUD. Adults with OUD (n = 154) completed a cross-sectional study assessing current and past sleep disturbance, opioid use history, and chronic pain. Repeated-measures analysis of variance was used to examine changes in retrospectively reported sleep quality, and whether changes varied by screening positive for insomnia and/or chronic pain. Multivariate linear regression analyses were used to identify additional correlates of persistent sleep disturbance. Participants reported that their sleep quality declined over their lifespan. Changes in reported sleep over time varied based on whether the individual screened positive for co-occurring insomnia and/or chronic pain. In regression analyses, female sex (β = 0.16, P = .042), a greater number of treatment episodes (β = 0.20, P = .024), and positive screens for chronic pain (β = 0.19, P = .018) and insomnia (β=0.22, P = .013) were associated with self-reported persistent sleep disturbance. Only a portion of participants who screened positive for sleep disorders had received a formal diagnosis. OUD treatment providers should routinely screen for co-occurring sleep disturbance and chronic pain. Interventions that treat co-occurring OUD, sleep disturbance, and chronic pain are needed. Ellis JD, Mayo JL, Gamaldo CE, Finan PH, Huhn AS. Worsening sleep quality across the lifespan and persistent sleep disturbances in persons with opioid use disorder. J Clin Sleep Med. 2022;18(2):587-595.

ObjectiveDemonstrate the use of timely, actionable data from a data visualization tool, the California Opioid Overdose Surveillance Dashboard, which integrates statewide, geographic- and demographic-specific data, by describing the changes in opioid overdose deaths in California.IntroductionCalifornia continues to face a serious public health crisis with the opioid epidemic having substantial health and economic impacts. The epidemic is dynamic and rapidly changing, involving both prescription opioids influenced by prescribing and dispensing patterns as well as illicit opioids influenced by the availability of heroin and recently, the increased availability of fentanyl. The complexity of the issue necessitates data-informed actions through multi-sector, strategic collaboration at both the state and local levels to address the problem comprehensively. With nearly 2,000 opioid overdose deaths per year and wide variation of overdose rates across counties and demographic groups, there is a need for integrated, timely, actionable data for use by state policy makers, local opioid safety coalitions, media, community stakeholders, and the public to monitor and combat this dynamic epidemic at the state and local level. Using fatality data from the California Opioid Overdose Surveillance Dashboard1, the opioid overdose epidemic is described along with the differential geographic and demographic impacts.MethodsAs part of California Department of Public Health’s Prevention for States grant funded by the Centers for Disease Control and Prevention, the California Opioid Overdose Surveillance Dashboard was developed as a data tool to provide enhanced visualization and integration of non-fatal and fatal opioid-involved overdose data and opioid prescription data. The dashboard was built on an open source RStudio server using Shiny, an R package that provides a framework for building web applications. Data incorporated on the dashboard include emergency department visits, hospitalizations, fatalities, and prescriptions related to opioid overdoses among California residents, presented in raw counts, crude rates, and age-adjusted rates at the state, county, and zip code levels, as well as by sex, age, and race/ethnicity. Overdose deaths are identified using ICD-10 (International Classification of Diseases, 10th Revision) codes X40-X44, X60-X64, X85, Y10-Y14, and T40.0-T40.6, recorded in the underlying cause of death and multiple cause of death fields on death certificates. Fentanyl overdose deaths are identified using a text search on contributing cause of death fields on death certificates. Using data from the California Opioid Overdose Surveillance Dashboard, we present one perspective of the epidemic by using 2017 death data to describe the changing trend and geographic and demographic variation of prescription drug, heroin, and fentanyl overdose deaths.ResultsOverall trends from 2011-2017 show that deaths due to opioid overdoses have increased. Prescription drug overdose death rates have slightly decreased by 6% from 3.93/100,000 in 2011 to 3.7/100,000 in 2017. Heroin overdose death rates have increased by 89% from 0.90/100,000 in 2011 to 1.70/100,000 in 2017. Fentanyl overdose death rates have increased by 320% from 0.25/100,000 in 2011 to 1.05/100,000 in 2017. The highest rates of prescription opioid overdose deaths are primarily concentrated in northern rural counties, while the highest rates of heroin and fentanyl overdose deaths are more dispersed throughout the state with many coastal counties showing higher rates of overdose deaths (Figure 1). Prescription opioid overdose deaths are concentrated among older ages showing highest rates among 55 to 59 year olds (8.27/100,000). In contrast, heroin and fentanyl overdose death rates are concentrated among younger ages with the highest rates seen among 25 to 29 year olds, 4.54/100,000 and 2.78/100,000, respectively (Figure 2). Males died from prescription opioid, heroin, and fentanyl overdoses at significantly higher rates than females. Prescription opioid and fentanyl overdose death rates (11.5/100,000 and 4.80/100,000, respectively) are significantly higher among Native Americans compared to other races/ethnicities (Table 1). Non-Hispanic whites had significantly higher prescription opioid and heroin overdose death rates (6.90/100,000 and 2.96/100,000, respectively) compared to non-Hispanic black, Hispanic, and Asian residents of California.ConclusionsFatality data from 2017 show the characteristics of the opioid overdose epidemic in California are changing. While still high, overdose deaths from prescription opioids, seen primarily in older age groups and northern rural California, are slightly declining. Concurrently, we are seeing sharp rises in heroin and fentanyl overdose death rates among younger adults throughout the state. Regardless of any change in trend, there remain clear disparities in overdose death rates by race/ethnicity; with Native Americans having the highest rates for both prescription and illicit opioids, and non-Hispanic whites have higher rates of prescription opioid and heroin overdose deaths.Given the varying demographic and geographic impacts based on the type of opioid, as demonstrated with the use of death data, there needs to be targeted data-informed interventions to address and prevent prescription and illicit opioid overdoses. Death data is just one perspective on the epidemic, other data sources (emergency department visits, hospitalizations, and prescriptions) are needed complete the picture to truly provide a robust data-informed approach. The California Opioid Overdose Surveillance dashboard integrates these multiple data sources and serves as a valuable tool in providing specific and timely data to inform approaches and interventions at the state and local level in continuing to fight California’s opioid overdose epidemic. The enhanced visualization, geographic- and demographic-specific data, and increasingly timely data allow for state and local policy makers, local opioid safety coalitions, and community stakeholders to track the dynamics and impact of the epidemic and to identify those who are most vulnerable and differentially impacted.References1 California Opioid Overdose Surveillance Dashboard https://discovery.dev.cdph.ca.gov/CDIC/ODdash/

To examine how the risks of incident opioid use disorder (OUD), non-fatal and fatal overdose have changed over time among opioid-naive individuals receiving an initial opioid prescription. Retrospective, longitudinal study using the Massachusetts Chapter 55 data set, which linked multiple administrative data sets to study the opioid epidemic. We identified the cumulative incidence of OUD, non-fatal and fatal overdose among the opioid-naive initiating opioid treatment in Massachusetts from 2011 to 2014 and estimated rates of these outcomes at 6months and at 1, 2, 3 and 4years to 2015. We used Cox regression to examine the association between characteristics of the initial prescription and risk of these outcomes. Massachusetts, USA. Massachusetts residents aged ≥11years in 2011-15 who were opioid-naive (no opioid prescriptions or evidence of OUD in the 6months prior to the index prescription) (n=2 154 426). The mean age was 49.1years, 55.3% were female and 47.3% had commercial insurance. Opioid prescriptions were identified in the Prescription Monitoring Program (PMP) database, as were the characteristics of the initial prescription database. The outcomes of OUD and non-fatal overdose were identified from claims in the All Payer Claims Database (APCD) and hospital encounters in the acute hospital case mix files. Fatal overdoses were identified using Registry of Vital Records and Statistics (RVRS) death certificates and the Office of the Chief Medical Examiner (OCME) circumstances of death and toxicology reports. Among opioid-naive individuals receiving an initial opioid prescription, the risk of incident OUD appears to have declined between 2011 and 2014, while rates of overdose were largely unchanged. For example, the 1-year OUD rate was 1.18% in 2011, 1.11% in 2012, 1.26% in 2013 and 0.94% in 2014. Longer therapy duration was associated with higher risk of OUD [hazard ratio (HR)=2.24, 95% confidence interval (CI)=2.19-2.29 for duration of 3 or more months], non-fatal (HR=1.67, 95% CI=1.53-1.82) and fatal opioid overdose (HR=2.24, 95% CI=1.91-2.61). Concurrent benzodiazepine treatment was also associated with higher risk of OUD (HR=1.14, 95% CI =1.12-1.17), non-fatal (HR=1.20, 95% CI=1.10-1.30) and fatal overdose (HR=1.86, 95% CI =1.61-2.16). Among opioid-naive individuals in Massachusetts receiving an initial opioid prescription, the risk of incident opioid use disorder appears to have declined between 2011 and 2014, while rates of overdose were largely unchanged. Longer therapy duration and concurrent benzodiazepines were associated with higher rates of opioid use disorder and opioid overdose.

Association Between Opioid Prescribing and Suicide Risk in the United States.

Non-medical use of pharmaceuticals is an international issue, with a seven-fold increase in global morphine consumption over the past 20 years, and concurrent concerns about opioid availability and under-treatment of severe pain in regions such as Africa [1] , [2] . Currently, in the US, the economic costs of non-medical use of prescription opioids is more than $50 billion a year [3] , and deaths from pharmaceutical opioids exceed deaths from all other drug classes, constituting the majority of both fatal and non-fatal overdoses [4] , [5] . This year, the Australian government has commissioned a National Pharmaceutical Drug Misuse Strategy, signalling broad recognition that pharmaceuticals, as a group of substances, require consideration within illicit drug use policy. It is therefore timely to be presenting this special issue, consisting of papers covering many aspects of the multifaceted issues relating to problematic use of pharmaceutical drugs. This special issue brings together the latest research on pharmaceutical misuse covering epidemiology, treatment implications and harm reduction. The special issue begins with an article by Larance et al. addressing the importance of using precise and consistent terminology to describe behaviours relating to pharmaceutical use in the context of opioid treatment [6] . Such precision is far from simply an academic interest – the authors argue that lack of specificity in describing the problems that may occur during opioid treatment can hinder appropriate responses, create communication barriers between prescriber and patient, and undermine progress in this arena. A series of epidemiology papers addresses pharmaceutical use in South East Asia, New Zealand and the United States [7] -[9] . A particularly salient point is raised by Larance et al. in the case of South East Asia, where there is both a dramatic under-treatment of pain and significant diversion of opioid pharmaceuticals, demonstrating that the problem of ‘misuse’ is not simply removed by constricting the supply of opioids for legitimate medical applications, and instead judicious regulatory processes that can support medical practice are required [8] . Patterns of increasing use and non-medical use of prescription pain medication in the US are described by Maxwell [7] . In New Zealand, Wilkins et al. describe pharmaceutical use amongst distinct subpopulations of illicit drug users, demonstrating different patterns of use among injection drug users, ecstasy and methamphetamine users, suggesting different intervention approaches may be needed depending on the substance in question and the population engaging in the extra-medical use [9] . In the provision of pain management, development of iatrogenic dependence is an important concern. However, excessive fear of dependence can similarly interfere with successful treatment. ‘Opioiphobia’ has been described amongst prescribers, especially in settings such as emergency rooms [10] . It is likely that these fears are heightened when prescribing for those with a history of substance abuse. Examining this issue, Ling et al.[11] highlight some of the challenges in treating concurrent opioid dependence and pain, discussing the need to find the balance between minimising risks and negative consequences of opioid use whilst not reducing effective pain treatment. As noted by Brogan and Kelsall [12] , with an aging population on chronic opioid substitution treatments who may increasingly require pain treatment, this is an important area with a need to prevent stigma and minimise the under-treatment of pain in this population. Attempts to dichotomise patients into pain patients and ‘abusers’ is identified as an oversimplification of the very complex issues that face many who are dependent on pharmaceutical opioids [12] , [13] . Harm, and reducing harm, in relation to pharmaceuticals is addressed in a number of papers in this special issue. There are a range of harms particular to pharmaceutical misuse. Where tablets are injected, insoluble tablet components may enter the bloodstream and damage organs. Currently, despite the fact that some pharmaceuticals are known to be likely to be injected, there is no responsibility for the manufacturer to ensure potentially damaging insoluble ingredients such as talc are not included in these products. Emerging work to investigate effective particle filtration procedures is presented in this issue by Roux et al.[14] , providing important directions for harm reduction for injecting drug users who use pharmaceuticals. Outside of injecting subgroups, another further contributor to harm arises from the formulation of some opioid products. One example is products containing the opioid codeine, in combination with other ingredients such as paracetamol or ibuprofen that are toxic in the high doses that are often consumed where dependence develops [15] -[17] . Similarly, harms may inadvertently arise from the perception of safety associated with taking a medically prescribed substance: in a review of the effects of prescription medications on driving by Leung, it is apparent that there is a link between benzodiazepines and opioids and accidents, even at therapeutic levels, however more experimental evidence is required to inform policy and to allow medical professionals to best advise their patients about safety when driving if they are using these medications [18] . Within this theme of harms, in their commentary Hallinan et al.[19] discuss some of the complexities relating to pharmaceutical opioids, raising the challenging point that, in some respects, non-prescribed use of pharmaceuticals may in fact be less harmful than use of illicit opioids such as heroin. This presents a novel and thorny dilemma for harm minimisation policy relating to opioid use [19] . Evidence is emerging that the populations experiencing problems with pharmaceutical use are demographically broader than the traditional injecting drug use populations seen in drug and alcohol treatment services [20] . For example, an over-representation of females and the largest number of attendances in relationship to benzodiazepines was found by Lloyd and McElwee from an examination of ambulance attendances in Melbourne, Australia [21] . Research is required to understand the treatment needs, and to develop interventions for these populations of pharmaceutical users that are currently under-represented in the treatment system. In an examination of drug treatment entrants, Nielsen et al. found that most pharmaceutical opioid users appear similar to heroin users on many characteristics [22] . Few non-injecting opioid users are entering treatment, despite growing evidence that this is a population that exists, and are at considerable risk of harm. There is a need to establish if there are alternative treatment types, modalities or processes that would be particularly effective in these populations. There may be a place for novel therapies including web based treatment, which Parr et al. have found to show promise in benzodiazepine users [23] . However, the question remains as to how these populations can be better identified and engaged. There are a number of unique elements to pharmaceutical use and challenges in responding to their problematic use at the health systems and policy level. Firstly, the availability of these agents for therapeutic use is essential, so clearly any measures to prevent abuse or dependence must be mindful of this. Ensuring that patients are not denied therapeutic medications whilst at the same time minimising diversion of potent medications for non-medical use is a delicate balance. Secondly, the ‘suppliers’ of these substances, at some point in the supply chain, tend to be medical professionals, largely doctors and pharmacists. Finally, the ‘users’ of these substances, while often meeting criteria for dependence, may not even themselves recognise that they are using a substance with a dependence liability. Sproule [13] and Holliday [24] make clear that detection of problematic pharmaceutical use needs to improve at both the prescriber and the pharmacist level. While much can be done to better utilise the role of these health professionals, both authors note that doctors and pharmacists respectively currently do not have the resources (including real-time information) nor are they remunerated to conduct the range of activities required to reduce pharmaceutical misuse. Further concerns are raised by Dunlop [25] , about just how little we know about the magnitude of problems with pharmaceuticals in Australia, and limitations with access to addiction and pain services. While it is clear there is a problem to address, when we consider policy responses, such as those involving monitoring and prescribing restrictions for pharmaceuticals, we need to remain mindful that these drugs do indeed have beneficial clinical effects and that it is highly likely that the majority of medications that are prescribed are used within therapeutic guidelines. In the debates around this issue, those coming from an addictions perspective must take care not to cause a ‘moral panic’, as this may increase problems such as opiophobia and create barriers to the access of indicated and effective treatments. For example, some prescription monitoring systems have been reported to reduce use of appropriate medications among cancer and cardiac patients [26] . There is also evidence showing that doctors switch to less restricted but also less effective medications for their patients in response to increased prescription scrutiny [27] . We also need to consider other potential unintended consequences of possible policy responses. What will we do when we have better e-records? Is the treatment system ready to respond to the estimated 1 500 000 prescription opioid dependent people in Australia [28] when their prescribers become aware of dependence, and can no longer supply these medications? What is the duty of care if an identified individual does not comply with treatment recommendations and displays aberrant behaviours? Does refusal to supply further prescriptions push dependent individuals into the illicit market? With rapid developments in information technology and e-health access, we are at a pivotal point in responding to the issue of problem pharmaceutical use. This special issue contributes important information better describing populations that use pharmaceuticals whilst also identifying some populations that we need to know much more about. Treatment approaches are considered, with examples of the complexity of this patient group, as well as potential treatment options for pharmaceutical users. We are left with food for thought with some interesting discussion on the place of harm reduction with pharmaceutical use. Carefully considered responses are required which engage all the stakeholders in this drug problem, including the patients and illicit consumers, the pharmacists, prescribers, pharmaceutical companies, and government regulatory agencies. The supply chains in this process are largely distinct from illicit drug markets, and hence previously developed responses may not translate well to pharmaceuticals. This is the time to develop considered and effective policy and treatment responses before morbidity and mortality further increase, tipping the scale to extreme regulatory responses which may see effective medications simply becoming unattainable.

An Urgent Need to Focus on Youth With Opioid Use Disorder

The US opioid epidemic is complex and dynamic, yet relatively little is known regarding its likely future impact and the potential mitigating impact of interventions to address it. To estimate the future burden of the opioid epidemic and the potential of interventions to address the burden. A decision analytic dynamic Markov model was calibrated using 2010-2018 data from the National Survey on Drug Use and Health, Centers for Disease Control and Prevention, National Health and Nutrition Examination Survey, the US Census, and National Epidemiologic Survey on Alcohol and Related Conditions-III. Data on individuals 12 years or older from the US general population or with prescription opioid medical use; prescription opioid nonmedical use; heroin use; prescription, heroin, or combined prescription and heroin opioid use disorder (OUD); 1 of 7 treatment categories; or nonfatal or fatal overdose were examined. The model was designed to project fatal opioid overdoses between 2020 and 2029. The model projected prescribing reductions (5% annually), naloxone distribution (assumed 5% reduction in case-fatality), and treatment expansion (assumed 35% increase in uptake annually for 4 years and 50% relapse reduction), with each compared vs status quo. Projected 10-year overdose deaths and prevalence of OUD. Under status quo, 484 429 (95% confidence band, 390 543-576 631) individuals were projected to experience fatal opioid overdose between 2020 and 2029. Projected decreases in deaths were 0.3% with prescribing reductions, 15.4% with naloxone distribution, and 25.3% with treatment expansion; when combined, these interventions were associated with 179 151 fewer overdose deaths (37.0%) over 10 years. Interventions had a smaller association with the prevalence of OUD; for example, the combined intervention was estimated to reduce OUD prevalence by 27.5%, from 2.47 million in 2019 to 1.79 million in 2029. Model projections were most sensitive to assumptions regarding future rates of fatal and nonfatal overdose. The findings of this study suggest that the opioid epidemic is likely to continue to cause tens of thousands of deaths annually over the next decade. Aggressive deployment of evidence-based interventions may reduce deaths by at least a third but will likely have less impact for the number of people with OUD.

Opioids for the treatment of acute pain and the pain of malignancy have been strongly encouraged for more than 25 years.1 In the past 2 decades, the treatment of chronic noncancer pain using long-term opioid therapy has become more common. However, recent studies have revealed the astonishing rapidi