Key Data Gaps Regarding the Public Health Issues Associated with Opioid Analgesics

Scoping Literature Review of Disease Modeling of the Opioid Crisis

Opioid misuse continues to cause significant harm. To investigate current research, we conducted a scoping literature review of disease spread models of opioid misuse from January 2000 to December 2022. In total, 85 studies were identified and examined for the opioids modeled, model type, data sources used and model calibration and validation. Most of the studies (58%, 49) only modeled heroin; the next largest categories were prescription opioids and unspecified opioids which accounted for 9% (8) each. Most models were theoretical compartmental models (57) or applied compartmental models (21). Previously published research was the most used data source (38), and a majority of the model validation involved the researchers setting initial conditions to verify theoretical results (30). To represent typical opioid use more accurately, multiple opioids need to be incorporated into the disease spread models, and applying different modeling techniques may allow other insights into opioid misuse spread.

Factors associated with frequent or daily use of prescription opioids among adults with chronic pain in the United States

OBJECTIVES

We aimed to estimate utilization rates of prescription opioids among adults with chronic pain in the United States (US) and identify factors associated with the frequent or daily use of prescription opioids.

METHODS

This was a case-control analysis of the 2019 National Health Interview Survey of adults.

RESULTS

Over 50.2 million adults in the US reported chronic pain in the past 3 months, but only 10.5% of this group said they used prescription opioids frequently or daily to manage their pain. Adults with chronic pain were significantly more likely to use opioids if they had incomes below the federal poverty level (15.7%), relied on public health insurance (14.8%), had been hospitalized in the past year (17.8%), or rated their health as fair or poor (18.4%). The highest rates of opioid use were reported among adults with severe (24.4%) or moderate disability (18.9%).

CONCLUSIONS

Approximately 5.3 million adults use prescription opioids frequently or daily to manage chronic pain. These individuals should receive regular clinical assistance to manage their pain, including medication management and, when appropriate, referral to evidence-based treatment programs for opioid use disorder.

Temporal trends in smoking and nicotine dependence in relation to co-occurring substance use in the United States, 2005-2016

BACKGROUND

Despite an overall decline in tobacco use in the United States, secular trends of smoking and nicotine dependence with co-occurring substance use are not well characterized.

METHODS

We examined self-reported tobacco and other substance use in 22,245 participants age 21-59 in the United States from six waves of the National Health and Nutrition Examination Survey (NHANES). Using Joinpoint regression, we assessed secular trends of smoking and nicotine dependence as a function of co-occurring use of alcohol, prescription opioids, marijuana/hashish, cocaine/heroin/methamphetamine, or other injection drug use. Multivariable logistic regressions were fitted to identify the potential risk factors.

RESULTS

During 2005-2016, the prevalence of current smoking decreased (without co-occurring substance use: 17.0 %-12.7 %; with co-occurring use of one substance: 35.3 % to 24.6 %; with co-occurring use of two or more substances: 53.8 %-42.2 %), and moderate-to-severe nicotine dependence decreased as well (8.0 %-4.2 %, 16.0 %-8.8 %, and 23.9 %-15.7 %, respectively). Smoking and nicotine dependence were more likely in those with co-occurring use of one substance (current smoking: odds ratio [OR] = 2.22, 95 % confidence interval [CI] = 2.01-2.45); nicotine dependence: OR = 1.88, 95 % CI = 1.63-2.17) and in those with co-occurring use of two or more substances (current smoking: OR = 5.25, 95 % CI = 4.63-5.95; nicotine dependence: OR = 3.24, 95 % CI = 2.72-3.87).

CONCLUSIONS

Co-occurring substance use was associated with smaller reductions in tobacco use, over time, and with increased odds of nicotine dependence. This suggests that co-occurring substance users should be regarded as a tobacco-related disparity group and prioritized for tobacco control interventions.

Association between mothers' postoperative opioid prescriptions and opioid-related events in their children: A population-based cohort study

BACKGROUND

Postoperative opioid prescriptions may be associated with risks of unintentional poisoning and drug diversion in other household members. The objective of this study was to explore the association between mothers' postoperative opioid prescriptions and incidence of opioid-related events in their children (aged 1 to 24 years).

DATA AND METHODS

This retrospective cohort study used individually linked administrative health data from Ontario, Canada. A population-based sample of 170,156 opioid-naïve mothers (aged 15 to 64) (see Figure 1) who underwent surgery between 2013 and 2017 in Ontario was linked through birth records to create a cohort of their 283,550 opioid-naïve children (aged 1 to 24). The association between postoperative opioid analgesic prescriptions filled by mothers within seven days of discharge after surgery and opioid-related events (emergency department presentations or inpatient admissions for opioid poisoning, or mental and behavioural disorders attributable to opioid use) in their children within one year of their mother's discharge was assessed.

RESULTS

Overall, 60.4% of the children in the cohort had a mother who filled a postoperative opioid prescription. The incidence of opioid-related events in children in the year after a mother's surgery was low overall (n=36/283,550, 0.01%), but higher among children whose mother filled a postoperative opioid prescription (n=29/171,139, 0.02%, vs. n=7/112,411, 0.01%, p=0.02), including in an analysis adjusting for child's age, mother's age, rural residence, neighbourhood income quintile and mother's Charlson comorbidity index score (adjusted odds ratio, 2.42 [95% confidence interval (CI), 1.05 to 5.54], p=0.04).

DISCUSSION

Postoperative opioid prescriptions for mothers may contribute to opioid-related events in their children. These findings further underscore the importance of safe, effective opioid prescribing, as well as of patient and public education about the use, storage and disposal of these medications.

Evidence of Modeling Impact in Development of Policies for Controlling the Opioid Epidemic and Improving Public Health: A Scoping Review

BACKGROUND

Opioid addiction and overdose rates are reaching unprecedented levels in the U.S., with around 47,736 overdose deaths in 2017. Many stakeholders affect the opioid epidemic, including government entities, healthcare providers and policymakers, and opioid users. Simulation and conceptual modeling can help us understand the dynamics of the opioid epidemic by simplifying the real world and informing policymakers about different health interventions that could reduce the deaths caused by opioid overdose in the United States every year.

OBJECTIVES

To conduct a scoping review of simulation and conceptual models that propose policies capable of controlling the opioid epidemic. We demonstrate the strengths and limitations of these models and provide a framework for further improvement of future decision support tools.

METHODS

Using the methodology of a scoping review, we identified articles published after 2000 from eight electronic databases to map the literature that uses simulation and conceptual modeling in developing public health policies to address the opioid epidemic.

RESULTS

We reviewed 472 papers of which 14 were appropriate for inclusion. Each used either system dynamics simulation modeling, mathematical modeling, conceptual modeling, or agent-based modeling. All included studies tested and proposed strategies to improve health outcomes related to the opioid epidemic. Factors considered in the models included physicians prescribing opioids, trafficking, users recruiting new users, and doctor shopping; no model investigated the impact of age and spatial factors on the dynamics of the epidemic. Key findings from these studies were (1) prevention of opioid initiation is better than treatment of opioid addiction, (2) the analysis of an intervention's impact should include both benefits and harms, and (3) interventions with short-term benefits might have a counterproductive impact on the epidemic in long run.

CONCLUSIONS

While most studies examined the role of prescription opioids and trafficking on this epidemic, the transition of patients from prescription opioid use to nonprescription use including heroin and synthetic opioids such as fentanyl impacts the system significantly and results in an epidemic with quite different characteristics than what it had a decade ago. We recommend including the impact of age and geographic location on the opioid epidemic using modeling methods.

The Pain Divide: a cross-sectional analysis of chronic pain prevalence, pain intensity and opioid utilisation in England

OBJECTIVES

Our central research question was, in England, are geographical inequalities in opioid use driven by health need (pain)? To answer this question, our study examined: (1) if there are regional inequalities in rates of chronic pain prevalence, pain intensity and opioid utilisation in England; (2) if opioid use and chronic pain are associated after adjusting for individual-level and area-level confounders.

DESIGN

Cross-sectional study design using data from the Health Survey for England 2011.

SETTING

England.

PRIMARY AND SECONDARY OUTCOME MEASURES

Chronic pain prevalence, pain intensity and opioid utilisation.

PARTICIPANTS

Participant data relating to chronic pain prevalence, pain intensity and opioid usage data were obtained at local authority level from the Health Survey for England 2011; in total, 5711 respondents were included in our analysis.

METHODS

Regional and local authority data were mapped, and a generalised linear model was then used to explore the relationships between the data. The model was adjusted to account for area-level and individual-level variables.

RESULTS

There were geographical variations in chronic pain prevalence, pain intensity and opioid utilisation across the English regions-with evidence of a 'pain divide' between the North and the South, whereby people in the North of England more likely to have 'severely limiting' or 'moderately limiting' chronic pain. The intensity of chronic pain was significantly and positively associated with the use of opioid analgesics.

CONCLUSIONS

There are geographical differences in chronic pain prevalence, pain intensity and opioid utilisation across England-with evidence of a 'pain divide'. Given the public health concerns associated with the long-term use of opioid analgesics-and their questionable activity in the management of chronic pain-more guidance is needed to support prescribers in the management of chronic pain, so the initiation of opioids can be avoided.

Cracking the Code: Using Data to Combat the Opioid Crisis

The goal of this article is to understand the value of data and to call for efforts to explore improved data sharing and collection among local, state, and federal agencies. It discusses the data available and existing barriers to sharing it. It also looks at examples of data sharing initiatives and analysis, such as mapping and visualization tools. The article then examines relevant regulations and calls for reforms. Finally, the article considers objections, including privacy interests, data security, and the costs and benefits of data sharing initiatives.

Dynamic model of nonmedical opioid use trajectories and potential policy interventions

BACKGROUND

Nonmedical use of pharmaceutical opioid analgesics (POA) increased dramatically over the past two decades and remains a major health problem in the United States, contributing to over 16 000 accidental poisoning deaths in 2010.

OBJECTIVES

To create a systems-oriented theory/model to explain the historical behaviors of interest, including the various populations of nonmedical opioid users and accidental overdose mortality within those populations. To use the model to explore policy interventions including tamper-resistant drug formulations and strategies for reducing diversion of opioid medicines.

METHODS

A system dynamics model was constructed to represent the population of people who initiate nonmedical POA usage. The model incorporates use trajectories including development of use disorders, transitions from reliance on informal sharing to paying for drugs, transition from oral administration to tampering to facilitate non-oral routes of administration, and transition to heroin use by some users, as well as movement into and out of the population through quitting and mortality. Empirical support was drawn from national surveys (NSDUH, TEDS, MTF, and ARCOS) and published studies.

RESULTS

The model was able to replicate the patterns seen in the historical data for each user population, and the associated overdose deaths. Policy analysis showed that both tamper-resistant formulations and interventions to reduce informal sharing could significantly reduce nonmedical user populations and overdose deaths in the long term, but the modeled effect sizes require additional empirical support.

CONCLUSION

Creating a theory/model that can explain system behaviors at a systems level scale is feasible and facilitates thorough evaluation of policy interventions.