US regional and demographic differences in prescription opioid and heroin-related overdose hospitalizations

Comparison of 10-year atherosclerotic cardiovascular disease (ASCVD) risk in metropolitan and rural areas of South of Iran

The first step to reducing the growing burden of cardiovascular disease (CVD) is to find modifiable risk factors with the highest burden in each population. Urban and rural citizens may have different priorities in this regard. This study aimed to compare the 10-year incidence probability of CVD events and its associated risk factors between rural and urban areas in Iran. Data was extracted from two big cohorts, Fasa Adults Cohort Study (FACS) and Shiraz Heart Study (SHS), with participation of over 12,000 general population. Linear regression models were used to test the difference in CVD risk between two populations. Totally, 6,258 FACS and 6,101 SHS participants entered the study. Urban participants had a significantly higher mean ASCVD score (4.43% vs. 5.51%, p-value < 0.001). Also, they significantly showed higher body mass index, waist circumference, cholesterol level, fasting blood glucose level, systolic blood pressure, educational attainment, and occupational status. However, the prevalence of smoking was higher in rural areas. Notably, socioeconomic parameters including marital, occupational, and educational statuses seem to have strong impact on cardiovascular risk factors. After adjustment for all confounders, living in the urban areas seemed to be associated with higher atherosclerotic CVD risk (β = 0.78, 95%CI: [0.69-1.05]), which was consistent across both sexes. Given the higher risk of cardiovascular events in urban areas and different profiles of risk factors between these two regions, preventive strategies should be precisely and separately designed for each population by the health authorities and policymakers in order to reduce the CVD toll efficiently.

Substance use during the COVID-19 pandemic among persons with traumatic spinal cord injury: A cross-sectional perspective

STUDY DESIGN

Analysis of data from two cohorts of Spinal Cord Injury Model Systems Database (SCIMS) participants, pre-pandemic (2017-2019, n = 6368) and during pandemic (2020, n = 1889).

OBJECTIVES

To examine differences in substance use during the pandemic compared to the years prior to the pandemic.

SETTING

19 SCIMS Centers.

METHODS

Participant characteristics, wellness (depression, life satisfaction, resilience), participation, and substance use between the two cohorts were compared. Multiple logistic regression examined the association of the pandemic with substance use after accounting for other factors.

RESULTS

Characteristics of the two cohorts were similar. Cannabis and sedative uses were not greatly different (28.8% vs 25.1%, and 8.3% vs 6.6%) but did reach statistical significance. Non-prescribed opioid use was double for the pandemic group (6.6% vs 3.3%). Alcohol use patterns were similar across the two cohorts. Measures of wellness were similar, while the pandemic group reported lower participation. The odds of use of cannabis, sedatives, and opioids were 1.3, 1.3, and 2.2 times greater, respectively, for the pandemic cohort after accounting for demographics, wellness, and participation. Greater use of non-prescribed opioids was reported during the pandemic in the South compared to prior to the pandemic (13.8% vs 6.1%).

CONCLUSIONS

The pandemic may have been associated with increased use of non-prescribed substances in the traumatic spinal cord injury population. Efforts to pursue longitudinal investigations would be warranted for definitive analysis of trends. The provision of demonstrably effective substance use treatment resources delivered via accessible methods will likely be needed in this population, particularly opioid treatment.

State-level factors associated with implementation of prescription drug monitoring program integration and mandatory use policies, United States, 2009-2020

BACKGROUND

Prescription drug monitoring programs (PDMPs) have been widely adopted as a tool to address the prescription opioid epidemic in the United States. PDMP integration and mandatory use policies are 2 approaches states have implemented to increase use of PDMPs by prescribers. While the effectiveness of these approaches is mixed, it is unclear what factors motivated states to implement them. This study examines whether opioid dispensing, adverse health outcomes, or other non-health-related factors motivated implementation of these PDMP approaches.

METHODS

Time-to-event analysis was performed using lagged state-year covariates to reflect values from the year prior. Extended Cox regression estimated the association of states' rates of opioid dispensing, prescription opioid overdose deaths, and neonatal opioid withdrawal syndrome with implementation of PDMP integration and mandatory use policies from 2009 to 2020, controlling for demographic and economic factors, state government and political factors, and prior opioid policies.

RESULTS

In our main model, prior opioid dispensing (HR 2.31, 95% CI 1.17, 4.57), neonatal opioid withdrawal syndrome hospitalizations (HR 1.55, 95% CI 1.09, 2.19), and number of prior opioid policies (HR 2.13, 95% CI 1.13, 4.00) were associated with mandatory use policies. Prior prescription opioid overdose deaths (HR 1.21, 95% CI 1.08, 1.35) were also associated with mandatory use policies in a model that did not include opioid dispensing or neonatal opioid withdrawal syndrome. No study variables were associated with implementation of PDMP integration.

CONCLUSION

Understanding state-level factors associated with implementing PDMP approaches can provide insights into factors that motivate the adoption of future public health interventions.

A state-level history of opioid overdose deaths in the United States: 1999-2021

We examined a natural history of opioid overdose deaths from 1999-2021 in the United States to describe state-level spatio-temporal heterogeneity in the waves of the epidemic. We obtained overdose death counts by state from 1999-2021, categorized as involving prescription opioids, heroin, synthetic opioids, or unspecified drugs. We developed a Bayesian multivariate multiple change point model to flexibly estimate the timing and magnitude of state-specific changes in death rates involving each drug type. We found substantial variability around the timing and severity of each wave across states. The first wave of prescription-involved deaths started between 1999 and 2005, the second wave of heroin-involved deaths started between 2010 and 2014, and the third wave of synthetic opioid-involved deaths started between 2014 and 2021. The severity of the second and third waves was greater in states in the eastern half of the country. Our study highlights state-level variation in the timing and severity of the waves of the opioid epidemic by presenting a 23-year natural history of opioid overdose mortality in the United States. While reinforcing the general notion of three waves, we find that states did not uniformly experience the impacts of each wave.

Exemplar Hospital initiation trial to Enhance Treatment Engagement (EXHIT ENTRE): protocol for CTN-0098B a randomized implementation study to support hospitals in caring for patients with opioid use disorder

BACKGROUND

Hospitalizations involving opioid use disorder (OUD) are increasing. Medications for opioid use disorder (MOUD) reduce mortality and acute care utilization. Hospitalization is a reachable moment for initiating MOUD and arranging for ongoing MOUD engagement following hospital discharge. Despite existing quality metrics for MOUD initiation and engagement, few hospitals provide hospital based opioid treatment (HBOT). This protocol describes a cluster-randomized hybrid type-2 implementation study comparing low-intensity and high-intensity implementation support strategies to help community hospitals implement HBOT.

METHODS

Four state implementation hubs with expertise in initiating HBOT programs will provide implementation support to 24 community hospitals (6 hospitals/hub) interested in starting HBOT. Community hospitals will be randomized to 24-months of either a low-intensity intervention (distribution of an HBOT best-practice manual, a lecture series based on the manual, referral to publicly available resources, and on-demand technical assistance) or a high-intensity intervention (the low-intensity intervention plus funding for a hospital HBOT champion and regular practice facilitation sessions with an expert hub). The primary efficacy outcome, adapted from the National Committee on Quality Assurance, is the proportion of patients engaged in MOUD 34-days following hospital discharge. Secondary and exploratory outcomes include acute care utilization, non-fatal overdose, death, MOUD engagement at various time points, hospital length of stay, and discharges against medical advice. Primary, secondary, and exploratory outcomes will be derived from state Medicaid data. Implementation outcomes, barriers, and facilitators are assessed via longitudinal surveys, qualitative interviews, practice facilitation contact logs, and HBOT sustainability metrics. We hypothesize that the proportion of patients receiving care at hospitals randomized to the high-intensity arm will have greater MOUD engagement following hospital discharge.

DISCUSSION

Initiation of MOUD during hospitalization improves MOUD engagement post hospitalization. Few studies, however, have tested different implementation strategies on HBOT uptake, outcome, and sustainability and only one to date has tested implementation of a specific type of HBOT (addiction consultation services). This cluster-randomized study comparing different intensities of HBOT implementation support will inform hospitals and policymakers in identifying effective strategies for promoting HBOT dissemination and adoption in community hospitals.

TRIAL REGISTRATION

NCT04921787.

Trends, outcomes, and factors associated with in-hospital opioid overdose following major surgery

Background

With the growing opioid epidemic across the US, in-hospital utilization of opioids has garnered increasing attention. Using a national cohort, this study sought to characterize trends, outcomes, and factors associated with in-hospital opioid overdose (OD) following major elective operations.

Methods

We identified all adult (≥18 years) hospitalizations entailing select elective procedures in the 2016-2020 National Inpatient Sample. Patients who experienced in-hospital opioid overdose were characterized as OD (others: Non-OD). The primary outcome of interest was in-hospital OD. Multivariable logistic and linear regression models were developed to evaluate the association between in-hospital OD and mortality, length of stay (LOS), hospitalization costs, and non-home discharge.

Results

Of an estimated 11,096,064 hospitalizations meeting study criteria, 5375 (0.05 %) experienced a perioperative OD. Compared to others, OD were older (66 [57-73] vs 64 [54-72] years, p < 0.001), more commonly female (66.3 vs 56.7 %, p < 0.001), and in the lowest income quartile (26.4 vs 23.2 %, p < 0.001). After adjustment, female sex (Adjusted Odds Ratio [AOR] 1.68, 95 % Confidence Interval [CI] 1.47-1.91, p < 0.001), White race (AOR 1.19, CI 1.01-1.42, p = 0.04), and history of substance use disorder (AOR 2.51, CI 1.87-3.37, p < 0.001) were associated with greater likelihood of OD. Finally, OD was associated with increased LOS (β +1.91 days, CI [1.60-2.21], p < 0.001), hospitalization costs (β +$7500, CI [5900-9100], p < 0.001), and greater odds of non-home discharge (AOR 2.00, CI 1.61-2.48, p < 0.001).

Conclusion

Perioperative OD remains a rare but costly complication after elective surgery. While pain control remains a priority postoperatively, protocols and recovery pathways must be re-examined to ensure patient safety.

"Make yourself un-NIMBY-able": stakeholder perspectives on strategies to mobilize public and political support for overdose prevention centers in the United States of America

BACKGROUND

Overdose prevention centers (OPCs), also known as supervised injection facilities and safe consumption sites, are evidenced-based interventions for preventing overdose deaths and drug-related morbidities. The pathways to legalizing OPCs in the USA have confronted multiple social, political, and legal obstacles. We conducted a multi-site, qualitative study to explore heterogeneities in these pathways in four jurisdictions, as well as to understand stakeholder perspectives on valuable strategies for galvanizing political and public support for OPCs.

METHODS

From July 2022 to February 2023, we conducted 17 semi-structured, in-depth interviews with OPC policymakers, service providers, advocates, and researchers from California, New York City, Philadelphia, and Rhode Island, where efforts have been undertaken to authorize OPCs. Using inductive thematic analysis, we identified and compared contextually relevant, salient approaches for increasing support for OPCs.

RESULTS

Participants described several strategies clustering around five distinct domains: (1) embedding OPC advocacy into broader overdose prevention coalitions to shape policy dialogs; (2) building rapport with a plurality of powerbrokers (e.g., lawmakers, health departments, law enforcement) who could amplify the impact of OPC advocacy; (3) emphasizing specific benefits of OPCs to different audiences in different contexts; (4) leveraging relationships with frontline workers (e.g., emergency medicine and substance use treatment providers) to challenge OPC opposition, including 'NIMBY-ism,' and misinformation; and (5) prioritizing transparency in OPC decision-making to foster public trust.

CONCLUSION

While tailored to the specific socio-political context of each locality, multiple OPC advocacy strategies have been deployed to cultivate support for OPCs in the USA. Advocacy strategies that are multi-pronged, leverage partnerships with stakeholders at multiple levels, and tailor communications to different audiences and settings could yield the greatest impact in increasing support for, and diffusing opposition to, future OPC implementation.

Testing the test strips: laboratory performance of fentanyl test strips

BACKGROUND

The overdose crisis driven by synthetic opioids continues to escalate in the USA. We evaluated the efficacy of multiple manufacturing lots of a fentanyl test strip (FTS) to detect fentanyl and fentanyl analogs and assessed cross-reactivity with possible interferences.

METHODS

Drug standards were dissolved in water in a laboratory setting and serially diluted. Drug dilutions were tested using five different manufacturing lots of BTNX Rapid Response (20 ng/mL cutoff) lateral flow chromatographic immunoassay strips to assess lot-to-lot variability for FTS sensitivity and cross-reactivity for the analytes of interest.

RESULTS

All five manufacturing lots cross-reacted with fentanyl and eleven fentanyl analogs. Diphenhydramine, lidocaine, MDMA, and methamphetamine were found to cause false positives with the strips. There was notable lot-to-lot variability in the sensitivity of the strips for fentanyl, fentanyl analogs, and known interferences.

DISCUSSION

FTS remains an important overdose prevention tool, but lot-to-lot variability in performance complicates robust instructions that balance the prevention of false positives and false negatives. Continued lot-to-lot performance assessment is recommended to ensure health education for FTS remains accurate. More sophisticated drug checking technologies and services are needed in the community landscape to augment personal FTS use to facilitate informed consumption and overdose risk mitigation.

A Mixed Methods Analysis of Southern HIV Service Organizations' Implementation of Harm Reduction to Address the HIV and Opioid Syndemic

Southern HIV Service Organizations (SHSOs) are promising sites for the adoption and implementation of harm reduction as a means for addressing the HIV and opioid syndemic. However, little research to date has examined exactly how harm reduction is operationalized within and among SHSOs. Using program evaluation data (i.e., organizational assessment data and semi-structured qualitative group interview data with SHSO staff), this study aimed to characterize organizational implementation of harm reduction among SHSOs that sought harm reduction capacity-building assistance (i.e., training, coaching, funding) from the SUSTAIN Center. Authors utilized a convergent mixed methods design in which quantitative and qualitative approaches were employed in parallel to gain simultaneous insights into how harm reduction was operationalized in SHSOs and how the local context influenced implementation. Means and proportions of each organizational assessment domain were compared. Thematic analysis of group interview transcripts examined SHSO staff perceptions of harm reduction implementation in their respective communities. Quantitative results revealed that SHSOs most commonly operationalize harm reduction in the Outreach, Advocacy, and Principles domains but struggle to do so in terms of Services and Organizational Infrastructure. Qualitative results revealed that various factors in SHSOs' local context, such as the community's lack of knowledge and understanding of harm reduction, limited harm reduction services, and a challenging socio-political context, influence SHSOs implementation of harm reduction. Taken together, analyses reveal that (1) SHSOs expend significant effort conducting outreach activities because Southern communities are generally unaware of harm reduction, (2) SHSOs continually advocate for harm reduction in the midst of a challenging socio-political context, and (3) SHSOs offer fewer harm reduction services and integrate harm reduction into their organizational infrastructure to a lesser extent due to external, contextual factors. The combination of organizational-level data and SHSO staff insights provided by this mixed methods study have implications for policy advocacy, funding initiatives, and capacity-building efforts.

Responding to the US opioid crisis: leveraging analytics to support decision making

The US is experiencing a severe opioid epidemic with more than 80,000 opioid overdose deaths occurring in 2022. Beyond the tragic loss of life, opioid use disorder (OUD) has emerged as a major contributor to morbidity, lost productivity, mounting criminal justice system costs, and significant social disruption. This Current Opinion article highlights opportunities for analytics in supporting policy making for effective response to this crisis. We describe modeling opportunities in the following areas: understanding the opioid epidemic (e.g., the prevalence and incidence of OUD in different geographic regions, demographics of individuals with OUD, rates of overdose and overdose death, patterns of drug use and associated disease outbreaks, and access to and use of treatment for OUD); assessing policies for preventing and treating OUD, including mitigation of social conditions that increase the risk of OUD; and evaluating potential regulatory and criminal justice system reforms.

Resilience and traumatic childhood experiences of patients with opioid use disorder

We aim to explore childhood traumatic experiences and resilience of patients with OUD and compare these variables to healthy controls. Ninety-five patients and 83 healthy controls completed the Sociodemographic Data Form, Connor Davidson Psychological Resilience Scale (CDRS), and Childhood Trauma Questionnaire-33 (CTQ-33). We found that CTQ correlated negatively with CDRS in patients. T-test results showed significant differences between both groups regarding total and subscales' scores of CTQ-except overprotection-over control. Physical neglect predicted a decrease in resilience in patients with OUD. In conclusion, childhood traumas and resilience could be essential factors during patients' follow-up and treatment process with OUD.

Estimated Reductions in Opioid Overdose Deaths With Sustainment of Public Health Interventions in 4 US States

Importance

In 2021, more than 80 000 US residents died from an opioid overdose. Public health intervention initiatives, such as the Helping to End Addiction Long-term (HEALing) Communities Study (HCS), are being launched with the goal of reducing opioid-related overdose deaths (OODs).

Objective

To estimate the change in the projected number of OODs under different scenarios of the duration of sustainment of interventions, compared with the status quo.

Design, Setting, and Participants

This decision analytical model simulated the opioid epidemic in the 4 states participating in the HCS (ie, Kentucky, Massachusetts, New York, and Ohio) from 2020 to 2026. Participants were a simulated population transitioning from opioid misuse to opioid use disorder (OUD), overdose, treatment, and relapse. The model was calibrated using 2015 to 2020 data from the National Survey on Drug Use and Health, the US Centers for Disease Control and Prevention, and other sources for each state. The model accounts for reduced initiation of medications for OUD (MOUDs) and increased OODs during the COVID-19 pandemic.

Exposure

Increasing MOUD initiation by 2- or 5-fold, improving MOUD retention to the rates achieved in clinical trial settings, increasing naloxone distribution efforts, and furthering safe opioid prescribing. An initial 2-year duration of interventions was simulated, with potential sustainment for up to 3 additional years.

Main Outcomes and Measures

Projected reduction in number of OODs under different combinations and durations of sustainment of interventions.

Results

Compared with the status quo, the estimated annual reduction in OODs at the end of the second year of interventions was 13% to 17% in Kentucky, 17% to 27% in Massachusetts, 15% to 22% in New York, and 15% to 22% in Ohio. Sustaining all interventions for an additional 3 years was estimated to reduce the annual number of OODs at the end of the fifth year by 18% to 27% in Kentucky, 28% to 46% in Massachusetts, 22% to 34% in New York, and 25% to 41% in Ohio. The longer the interventions were sustained, the better the outcomes; however, these positive gains would be washed out if interventions were not sustained.

Conclusions and Relevance

In this decision analytical model study of the opioid epidemic in 4 US states, sustained implementation of interventions, including increased delivery of MOUDs and naloxone supply, was found to be needed to reduce OODs and prevent deaths from increasing again.

Narrative minireview of the spatial epidemiology of substance use disorder in the United States: Who is at risk and where?

Drug overdose is the leading cause of death by injury in the United States. The incidence of substance use disorder (SUD) in the United States has increased steadily over the past two decades, becoming a major public health problem for the country. The drivers of the SUD epidemic in the United States have changed over time, characterized by an initial heroin outbreak between 1970 and 1999, followed by a painkiller outbreak, and finally by an ongoing synthetic opioid outbreak. The nature and sources of these abused substances reveal striking differences in the socioeconomic and behavioral factors that shape the drug epidemic. Moreover, the geospatial distribution of the SUD epidemic is not homogeneous. The United States has specific locations where vulnerable communities at high risk of SUD are concentrated, reaffirming the multifactorial socioeconomic nature of this epidemic. A better understanding of the SUD epidemic under a spatial epidemiology framework is necessary to determine the factors that have shaped its spread and how these patterns can be used to predict new outbreaks and create effective mitigation policies. This narrative minireview summarizes the current records of the spatial distribution of the SUD epidemic in the United States across different periods, revealing some spatiotemporal patterns that have preceded the occurrence of outbreaks. By analyzing the epidemic of SUD-related deaths, we also describe the epidemic behavior in areas with high incidence of cases. Finally, we describe public health interventions that can be effective for demographic groups, and we discuss future challenges in the study and control of the SUD epidemic in the country.

Demographic and Clinical Correlates of Treatment Completion among Older Adults with Heroin and Prescription Opioid Use Disorders

In this study using 2015-2018 Treatment Episode Data Set-Discharge (TEDS-D) cases age 55+ for heroin (N = 101,524) or prescription opioids (PO; N = 25,510) as the primary substance, we examined treatment completion rates and correlates. We fit separate logistic regression models for heroin and PO cases with treatment completion status (completed vs. discontinued due to dropout/termination/other reasons) for each treatment setting (detoxification, residential rehabilitation, and outpatient) as the dependent variable. Results show that detoxification cases had the highest completion rates and outpatient cases had the lowest (14.8% for heroin and 24.0% for PO cases). A consistently significant correlate of treatment completion was legal system referral for heroin cases and having a bachelor's degree for PO cases. Medication-assisted therapy was associated with higher odds of completing residential treatment for both types of opioids but lower odds of completing detoxification and outpatient treatment. Treatment duration >30 days tended to have higher odds of completion. PO cases age 65+ had higher odds of completing residential treatment than cases age 55-64. Racial/ethnic minorities tended to have lower odds of outpatient treatment completion. Study findings underscore the importance of helping older adults complete treatment, especially those who are racial/ethnic minorities and receiving outpatient treatment.

Are we contributing to the opioid epidemic? A systematic review on systemic opioid use in dermatology

BACKGROUND

Although dermatologists treat many painful skin conditions and perform procedures that may require analgesic use, there is a lack of evidence synthesis on opioid use in dermatology.

OBJECTIVE

To conduct a systematic review of the evidence on the use of opioid analgesics in dermatology.

METHODS

We applied the PRISMA guidelines and systematically reviewed literature that examined opioid use in dermatology published between 1980 and 2020 in the PubMed, EMBASE, and Cochrane databases. This review was registered with PROSPERO (CRD42020204864).

RESULTS

We identified 24 studies that analyzed 52,705,201 patients and 13,099 dermatologists. Between 34% and 87.5% of patients received opioids following dermatologic procedures; however, many did not use the entirety of their prescriptions, and 35-69% did not use any of their prescription. Top opioid prescribers were more likely to be Mohs surgeons, male, and practice in the South. Variability exists in the current evidence for opioid prescribing for nonprocedural dermatologic disease.

CONCLUSION

While opioid prescribing in dermatology is low compared with other specialties, patients are not utilizing the entirety of their prescriptions. Opioid prescribing for nonprocedural dermatologic disease varies; treatments focused on targeting the pathogenesis of these diseases is important to minimize opioid use. Dermatologists should consider limiting opioid prescribing and utilizing nonnarcotic analgesics.

Healthcare Utilization of Patients with Opioid Use Disorder in US Hospitals from 2016 to 2019: Focusing on Racial and Regional Variances

BACKGROUND

There is a lack of US population-based research on healthcare utilization differences caused by opioid misuse.

OBJECTIVE

The aim of this study was to explore disparities in healthcare utilization by type of opioid use disorder, race, region, and other patient factors for a more targeted prevention and treatment program.

METHODS

The National Inpatient Sample of the United States was used to identify patients with opioid use disorder (n = 101,231, weighted n = 506,155) from 2016 to 2019. Type of opioid use disorder was defined as opioid dependence/unspecified use, adverse effects of opioids, opioid misuse, and opioid poisoning (also known as overdose). We examined the sample characteristics and the association between type of disorder, racial and regional variables, and healthcare utilization, measured by hospital charges and length of stay. The multivariate survey linear regression model was used.

RESULTS

Among 506,155 patients, most were categorized as opioid dependence/unspecified use (56.3%) and opioid poisoning (42.7%). The number of opioid use disorder patients during the study decreased; however, overall total charges and length of stay continuously increased. Survey linear results showed that opioid poisoning, adverse effects, and abuse were associated with higher hospital charges than opioid dependence; however, length of stay was significantly lower for these groups. White patients compared with minorities, and West, Northeast, and South regions were associated with higher hospital charges and length of stay.

CONCLUSION

Significant differences in healthcare utilization exist between type of disorder, race, and region. Such findings illustrate that tailored treatment regimens are required to bridge the gaps in care and combat the opioid crisis. Minorities with opioid use disorder utilize healthcare the least, possibly because of affordability, and need culturally sensitive and financially feasible treatment options.

Harm reduction implementation among HIV service organizations (HSOs) in the U.S. south: a policy context analysis and results from a survey of HSOs

BACKGROUND

HIV service organizations are integral to serving communities disproportionately impacted by the HIV and opioid epidemics in the U.S. South. Addressing these intersecting epidemics requires implementation of evidence-based approaches, such as harm reduction. However, little is known about the extent to which Southern HIV service organizations implement harm reduction. This manuscript examines: 1) the implementation context of harm reduction in the South, 2) Southern HIV service organization implementation of harm reduction, and 3) the impact of different contexts within the South on HIV service organization implementation of harm reduction.

METHODS

To examine implementation context, authors analyzed nation-wide harm reduction policy and drug-related mortality data. To examine HIV service organization implementation of harm reduction, authors performed frequency distributions on survey data (n = 207 organizations). Authors then constructed logistic regressions, using state mortality data and policy context as predictors, to determine what contextual factors predicted HIV service organization implementation of harm reduction.

RESULTS

Drug-related mortality data revealed an increased need for harm reduction, and harm reduction policy data revealed an increased political openness to harm reduction. Frequency distributions revealed that approximately half of the HIV service organizations surveyed reported that their organizations reflect a harm reduction orientation, and only 26% reported providing harm reduction services. Despite low utilization rates, HIV service organizations indicated a strong interest in harm reduction. Logistic regressions revealed that while increased mortality rates do not predict HIV service organization implementation of harm reduction, a harm reduction-friendly policy context does.

DISCUSSION

This study highlights how regions within a high-income country can face unique barriers to healthcare and therefore require a unique understanding of implementation context. Study findings indicate a rapidly changing implementation context where increased need meets increased political opportunity to implement harm reduction, however there is a lag in HIV service organization adoption of harm reduction. Financial resources, capacity building, and continued policy advocacy are required for increased HIV service organization adoption of harm reduction.

Modeling the evolution of the US opioid crisis for national policy development

The opioid crisis is a major public health challenge in the United States, killing about 70,000 people in 2020 alone. Long delays and feedbacks between policy actions and their effects on drug-use behavior create dynamic complexity, complicating policy decision-making. In 2017, the National Academies of Sciences, Engineering, and Medicine called for a quantitative systems model to help understand and address this complexity and guide policy decisions. Here, we present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), a dynamic simulation model developed in response to that charge. SOURCE tracks the US population aged ≥12 y through the stages of prescription and illicit opioid (e.g., heroin, illicit fentanyl) misuse and use disorder, addiction treatment, remission, and overdose death. Using data spanning from 1999 to 2020, we highlight how risks of drug use initiation and overdose have evolved in response to essential endogenous feedback mechanisms, including: 1) social influence on drug use initiation and escalation among people who use opioids; 2) risk perception and response based on overdose mortality, influencing potential new initiates; and 3) capacity limits on treatment engagement; as well as other drivers, such as 4) supply-side changes in prescription opioid and heroin availability; and 5) the competing influences of illicit fentanyl and overdose death prevention efforts. Our estimates yield a more nuanced understanding of the historical trajectory of the crisis, providing a basis for projecting future scenarios and informing policy planning.

Best practices for community-based overdose education and naloxone distribution programs: results from using the Delphi approach

BACKGROUND

Opioid-related overdose deaths have surged in the USA over the last two decades. Overdose fatalities are preventable with the timely administration of naloxone. Syringe service programs (SSP) have pioneered community-based naloxone distribution through overdose prevention and naloxone distribution (OEND) programs. There is a dearth of information with regards to best practices for community-based OEND.

METHODS

We utilized a modified Delphi approach to develop a set of best practices for OEND delivery. Starting with an initial list of best practices, we engaged 27 experts, in the field of OEND programming who reviewed, made recommendations for changes, and assigned a priority to each best practice.

RESULTS

Two rounds of input resulted in a final list of 20 best practices organized into four categories. The mean priority scores ranged from 1.17 to 2.17 (range 1 to 3). The top 5 ranked best practices were ensuring that SSP participants have low barrier, consistent, needs-based access to naloxone and that there is ample naloxone available within communities. While the remaining fifteen best practices were deemed important, they had more to do with organizational culture and implementation climate.

CONCLUSIONS

Increasing community-based OEND delivery is essential to reduce opioid overdose deaths; however, it will be insufficient to add programs without an eye toward quality of implementation and fidelity to the model upon which the evidence is based. This list of best practices summarizes the consensus among OEND experts and can serve as a tool for SSPs providing OEND programming to improve services.

Association of pre-admission opioid abuse and/or dependence on major complications in traumatic brain injury (TBI) patients

SETTING

In the last few decades, an opioid related health crisis has been a challenging problem in many countries around the world, especially the United States. Better understanding of the association of pre-admission opioid abuse and/or dependence (POAD) on specific major complications in traumatic brain injury (TBI) patients can aid the medical team in improving patient care management and outcomes.

STUDY OBJECTIVE

Our goal is to assess and quantify the risk of POAD on in-hospital mortality and major complications in TBI patients.

DESIGN

We conducted a retrospective study and used the National Inpatient Sample (NIS) database from 2004 to 2015 to investigate the impact of POAD on in-hospital mortality and major complications in TBI patients. We utilized propensity score matching and conditional logistic regression models, adjusted with injury severity score (ISS) and comorbidities, to obtain the adjusted odds ratios (OR).

MAIN RESULTS

POAD TBI patients had lower risks of in-hospital mortality (OR 0.58; p < 0.001) and acute myocardial infarction (OR 0.53; p = 0.045), while a higher risk of respiratory (OR 1.59; p < 0.001) and neurologic complications (OR 2.54; p < 0.001), compared to non-POAD TBI patients. Additionally, POAD patients were significantly more likely to have sepsis (OR 2.16, p < 0.001), malnutrition (OR 1.56, p < 0.001), delirium (OR 2.81, p < 0.001), respiratory failure (OR 1.79, p < 0.001), and acute renal failure (OR 1.83, p < 0.001). POAD TBI patients had shorter length of hospital stay compared to non-POAD TBI patients (mean 8.0 vs 9.2 days, p < 0.001).

CONCLUSIONS

POAD TBI patients have a lower in-hospital mortality, shorter duration of hospitalization and a lower risk of acute myocardial infarction, while they are more likely to have respiratory failure, delirium, sepsis, malnutrition, and acute renal failure compared to TBI patients without POAD. Prospective study is warranted to further confirm these findings.

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models are a tool to help us understand and address thiscomplex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings; created a database of model parameters used for model calibration; and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and agent-based models (16%). Intervention cost-effectiveness was evaluated in 40% of the studies, and 39% focused on services for people with opioid use disorder (OUD). In 61% of the eligible articles, authors discussed calibrating their models to empirical data, and in 31%, validation approaches used in the modeling process were discussed. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation or relapse, emergency medical services, and death parameters. From this database, potential model inputs can be identified and models can be compared with prior work. Simulation models should be used to tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.

The Overdose Crisis and Using Alone: Perspectives of People Who Use Drugs in Rural and Semi-Urban Areas of British Columbia

Background: A significant rise in the rate of overdose deaths in British Columbia (BC), driven by fentanyl contamination of the illicit drug supply, led to the declaration of a public health emergency in 2016. Those at greatest risk of death are people who use alone. This community-based participatory action research study based in the Fraser East region of BC study aimed to overview underlying factors that contribute to unwitnessed overdoses in semi-urban and rural settings. Methods: This descriptive study used a community-based participatory action research model with peer research associates (PRAs) involved at various research stages. In total, 22 interviews were conducted with participants aged 19 and over who used illicit drugs in the Fraser East since the start of the public health emergency in 2016. A collaborative data analysis approach was taken for data interpretation, and content analysis was performed to explore themes surrounding using alone. Results: Among people who use drugs (PWUD), using alone was found to be influenced by (a) the availability of drugs and personal funds, (b) personal safety, (c) stigma and shame, (d) protecting privacy, (e) mental health conditions and addiction, and (f) the lack of engagement with harm reduction services. At times, using alone was due to unforeseen, episode-specific situations. Conclusion: A multi-dimentional and context-specific approach is needed in overdose prevention and response for people who use drugs alone. There is need for enhanced approaches that address or include support services for families to reduce stigma and isolation of those at risk of an overdose.

Current Best Practices for Acute and Chronic Management of Patients with Opioid Use Disorder

This comprehensive review on opioids summarizes the scope of the current opioid epidemic, the diagnosis and treatment of opioid use disorder, and the medical and psychiatric complications of opioid use.

Accessibility to Medication for Opioid Use Disorder After Interventions to Improve Prescribing Among Nonaddiction Clinics in the US Veterans Health Care System

IMPORTANCE

With increasing rates of opioid use disorder (OUD) and overdose deaths in the US, increased access to medications for OUD (MOUD) is paramount. Rigorous effectiveness evaluations of large-scale implementation initiatives using quasi-experimental designs are needed to inform expansion efforts.

OBJECTIVE

To evaluate a US Department of Veterans Affairs (VA) initiative to increase MOUD use in nonaddiction clinics.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement initiative used interrupted time series design to compare trends in MOUD receipt. Primary care, pain, and mental health clinics in the VA health care system (n = 35) located at 18 intervention facilities and nonintervention comparison clinics (n = 35) were matched on preimplementation MOUD prescribing trends, clinic size, and facility complexity. The cohort of patients with OUD who received care in intervention or comparison clinics in the year after September 1, 2018, were evaluated. The preimplementation period extended from September 1, 2017, through August 31, 2018, and the postimplementation period from September 1, 2018, through August 31, 2019.

EXPOSURES

The multifaceted implementation intervention included education, external facilitation, and quarterly reports.

MAIN OUTCOMES AND MEASURES

The main outcomes were the proportion of patients receiving MOUD and the number of patients per clinician prescribing MOUD. Segmented logistic regression evaluated monthly proportions of MOUD receipt 1 year before and after initiative launch, adjusting for demographic and clinical covariates. Poisson regression models examined yearly changes in clinician prescribing over the same time frame.

RESULTS

Overall, 7488 patients were seen in intervention clinics (mean [SD] age, 53.3 [14.2] years; 6858 [91.6%] male; 1476 [19.7%] Black, 417 [5.6%] Hispanic; 5162 [68.9%] White; 239 [3.2%] other race [including American Indian or Alaska Native, Asian, Native Hawaiian or other Pacific Islander, and multiple races]; and 194 [2.6%] unknown) and 7558 in comparison clinics (mean [SD] age, 53.4 [14.0] years; 6943 [91.9%] male; 1463 [19.4%] Black; 405 [5.4%] Hispanic; 5196 [68.9%] White; 244 [3.2%] other race; 250 [3.3%] unknown). During the preimplementation year, the proportion of patients receiving MOUD in intervention clinics increased monthly by 5.0% (adjusted odds ratio [AOR], 1.05; 95% CI, 1.03-1.07). Accounting for this preimplementation trend, the proportion of patients receiving MOUD increased monthly by an additional 2.3% (AOR, 1.02; 95% CI, 1.00-1.04) during the implementation year. Comparison clinics increased by 2.6% monthly before implementation (AOR, 1.03; 95% CI, 1.01-1.04), with no changes detected after implementation. Although preimplementation-year trends in monthly MOUD receipt were similar in intervention and comparison clinics, greater increases were seen in intervention clinics after implementation (AOR, 1.04; 95% CI, 1.01-1.08). Patients treated with MOUD per clinician in intervention clinics saw greater increases from before to after implementation compared with comparison clinics (incidence rate ratio, 1.50; 95% CI, 1.28-1.77).

CONCLUSIONS AND RELEVANCE

A multifaceted implementation initiative in nonaddiction clinics was associated with increased MOUD prescribing. Findings suggest that engagement of clinicians in general clinical settings may increase MOUD access.

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups

OBJECTIVES

To assess fairness and bias of a previously validated machine learning opioid misuse classifier.

MATERIALS & METHODS

Two experiments were conducted with the classifier's original (n = 1000) and external validation (n = 53 974) datasets from 2 health systems. Bias was assessed via testing for differences in type II error rates across racial/ethnic subgroups (Black, Hispanic/Latinx, White, Other) using bootstrapped 95% confidence intervals. A local surrogate model was estimated to interpret the classifier's predictions by race and averaged globally from the datasets. Subgroup analyses and post-hoc recalibrations were conducted to attempt to mitigate biased metrics.

RESULTS

We identified bias in the false negative rate (FNR = 0.32) of the Black subgroup compared to the FNR (0.17) of the White subgroup. Top features included "heroin" and "substance abuse" across subgroups. Post-hoc recalibrations eliminated bias in FNR with minimal changes in other subgroup error metrics. The Black FNR subgroup had higher risk scores for readmission and mortality than the White FNR subgroup, and a higher mortality risk score than the Black true positive subgroup (P < .05).

DISCUSSION

The Black FNR subgroup had the greatest severity of disease and risk for poor outcomes. Similar features were present between subgroups for predicting opioid misuse, but inequities were present. Post-hoc mitigation techniques mitigated bias in type II error rate without creating substantial type I error rates. From model design through deployment, bias and data disadvantages should be systematically addressed.

CONCLUSION

Standardized, transparent bias assessments are needed to improve trustworthiness in clinical machine learning models.

Individual and Community Factors Associated with Naloxone Co-prescribing Among Long-term Opioid Patients: a Retrospective Analysis

BACKGROUND

Naloxone co-prescribing to individuals at increased opioid overdose risk is a key component of opioid overdose prevention efforts.

OBJECTIVE

Examine naloxone co-prescribing in the general population and assess how co-prescribing varies by individual and community characteristics.

DESIGN

Retrospective cross-sectional study. We conducted a multivariable logistic regression of 2017-2018 de-identified pharmacy claims representing 90% of all prescriptions filled at retail pharmacies in 50 states and the District of Columbia.

PATIENTS

Individuals with opioid analgesic treatment episodes > 90 days MAIN MEASURES: Outcome was co-prescribed naloxone. Predictor variables included insurance type, primary prescriber specialty, receipt of concomitant benzodiazepines, high-dose opioid episode, county urbanicity, fatal overdose rates, poverty rates, and primary care health professional shortage areas.

KEY RESULTS

Naloxone co-prescribing occurred in 2.3% of long-term opioid therapy episodes. Medicaid (aOR 1.87, 95%CI 1.84 to 1.90) and Medicare (aOR 1.48, 95%CI 1.46 to 1.51) episodes had higher odds of naloxone co-prescribing than commercial insurance episodes, while cash pay (aOR 0.77, 95%CI 0.74 to 0.80) and other insurance episodes (aOR 0.81, 95%CI 0.79 to 0.83) had lower odds. Odds of naloxone co-prescribing were higher among high-dose opioid episodes (aOR 3.19, 95%CI 3.15 to 3.23), when concomitant benzodiazepines were prescribed (aOR 1.12, 95%CI 1.10 to 1.14), and in counties with higher fatal overdose rates.

CONCLUSION

Co-prescription of naloxone represents a tangible clinical action that can be taken to help prevent opioid overdose deaths. However, despite recommendations to co-prescribe naloxone to patients at increased risk for opioid overdose, we found that co-prescribing rates remain low overall. States, insurers, and health systems should consider implementing strategies to facilitate increased co-prescribing of naloxone to at-risk individuals.

Prescription Opioid Characteristics and Nonfatal Overdose Among Patients Discharged from Tennessee Emergency Departments

BACKGROUND

Despite increasing trends of nonfatal opioid overdoses in emergency departments (EDs), population-based studies comparing prescription opioid dosing patterns before and after nonfatal opioid overdoses are limited.

OBJECTIVES

To evaluate characteristics of prescribing behaviors before and after nonfatal overdoses, with a focus on opioid dosage.

METHODS

Included were 5,395 adult residents of Tennessee discharged from hospital EDs after a first nonfatal opioid overdose (2016-2017). Patients were linked to eligible prescription records in the Tennessee Controlled Substance Monitoring Database. We estimated odds ratios (OR) and 95% confidence intervals (CI) to evaluate characteristics associated with filling opioid prescriptions 90 days before overdose and with high daily dose (≥ 90 morphine milligram equivalents) 90 days after overdose.

RESULTS

Among patients who filled a prescription both before and after an overdose, the percentage filling a low, medium, and high dose was 33.7%, 31.9%, and 34.4%, respectively, after an opioid overdose (n = 1,516). Most high-dose users before an overdose (>70%) remained high-dose users with the same prescriber after the overdose. Male gender, ages ≥ 35 years, and medium metro residence were associated with increased odds of high-dose filling after an opioid overdose. Patients filling overlapping opioid-benzodiazepine prescriptions and with > 7 days' supply had increased odds of filling high dose after an opioid overdose (OR 1.4, 95% CI 1.08-1.70 and OR 3.7, 95% CI 2.28-5.84, respectively).

CONCLUSIONS

In Tennessee, many patients treated in the ED for an overdose are still prescribed high-dose opioid analgesics after an overdose, highlighting a missed opportunity for intervention and coordination of care between ED and non-ED providers.

Do Injured Workers Receive Opioid Prescriptions Outside the Workers' Compensation System?: The Case of Private Group Health Insurances

OBJECTIVES

We explored the impact of workplace injury on receiving opioid prescriptions from employer-sponsored private group health insurances (GHI) and how long injured workers receive opioid prescriptions after injury.

METHODS

We used a difference-in-differences method and MarketScan databases for the years 2013 to 2015.

RESULTS

Estimated odds for injured workers relative to noninjured workers to receive opioid prescriptions from the GHI within 60 and 180 days from the index date of injury were 4.9 and 1.5, respectively. In addition, the number of opioid prescriptions received within 60 days of injury was 2.5 times higher.

CONCLUSION

Workplace injury could be a risk factor for both short and long-term prescription opioid use. Studies that use only workers' compensation medical claim data likely underestimate the magnitude of the impact of workplace injuries on opioid prescriptions.

The rise of illicit fentanyls, stimulants and the fourth wave of the opioid overdose crisis

PURPOSE OF REVIEW

This review provides an update on recently published literature on the rise of illicit fentanyls, risks for overdose, combinations with other substances, e.g. stimulants, consequences, and treatment.

RECENT FINDINGS

Overdose due to illicit synthetic opioids (e.g. fentanyl and fentanyl analogs) continues to rise in the US both preceding and during the COVID-19 pandemic. Fentanyl-related overdose is rising in new geographic areas e.g. the western USA. Stimulant-related overdose is also increasing nationwide driven by methamphetamine and cocaine. Polysubstance use, e.g. the use of a stimulant along with an opioid is driving stimulant-related overdose. Other medical consequences of injection drug use are rising including HIV and hepatitis C infections. Medication approaches to treating opioid use disorder remain the standard of care and there are new promising pharmacological approaches to treating methamphetamine use disorder.

SUMMARY

A 'fourth wave' of high mortality involving methamphetamine and cocaine use has been gathering force in the USA. Availability and use of illicit fentanyls are still the major drivers of overdose deaths and the current rise in stimulant-related deaths appears entwined with the ongoing opioid epidemic.

Medically treated opioid overdoses among New Jersey Medicaid beneficiaries: Rapid growth and complex comorbidity amid growing fentanyl penetration

OBJECTIVE

Medically treated opioid overdoses identify a population at high risk of subsequent mortality and need for treatment. This study reports on medically treated opioid overdose trends in a state with rapid fentanyl spread.

METHODS

We conducted stratified trend analysis of medically treated overdose due to heroin, synthetic opioids, methadone, or other natural opioids among New Jersey Medicaid beneficiaries aged 12-64 years (2014-2019); evaluated associations with demographics and co-occurring conditions; and examined trends in fentanyl penetration in suspected heroin seizures from New Jersey State Police data.

RESULTS

Overdose risk more than tripled from 2014 to 2019, from 120.5 to 426.8 per 100,000 person-years, respectively. Increases primarily involved heroin and synthetic opioids and were associated with co-occurring alcohol and other non-opioid drug disorders, major depressive disorder, and hepatitis C. Concurrent changes in the drug exposure environment (2015-2019) included an increase in fentanyl penetration (proportion of suspected heroin seizures that included fentanyls) from 2% to 80%, and a decrease in the proportion of Medicaid beneficiaries who received opioid analgesic prescriptions from 23% to 13%.

CONCLUSION

Results document a rapid increase in overdose risk among individuals with opioid use disorder in an environment in which fentanyl is highly prevalent, and highlight the need for intensified services and engagement of non-treatment seekers, and integrated models to address multiple co-occurring conditions and risk factors.

Validation of the Opioid Overdose Risk Behavior Scale, version 2 (ORBS-2)

OBJECTIVE

To examine the factor structure of a revised and expanded opioid overdose risk behavior scale and assess its associations with known overdose indicators and other clinical constructs.

BACKGROUND

Opioid-related overdose remains high in the U.S. We lack strong instrumentation for assessing behavioral risk factors. We revised and expanded the opioid overdose risk behavior scale (ORBS-1) for use among a broader range of people who use opioids.

SETTING & SAMPLING FRAME

Using respondent-driven sampling we recruited adults (18+) reporting current unprescribed opioid use and New York City residence.

METHOD

Participants (N = 575) completed the ORBS-1, ORBS-2, and a variety of clinical measures and then completed the ORBS-2 and overdose risk outcomes across monthly follow-up assessments over a 13-month period.

RESULTS

Principal components analysis was used to identify six ORBS-2 subscales, Prescription Opioid Misuse, Risky Non-Injection Use, Injection Drug Use, Concurrent Opioid and Benzodiazepine Use, Concurrent Opioid and Alcohol Use, and Multiple-Drug Polysubstance Use. All subscales showed moderate non-parametric correlations with the ORBS-1 and with corresponding clinical constructs. Five of the subscales were significantly (p < .01) positively associated with self-reported non-fatal overdose. Of note, the Risky Non-Injection Use subscale was the most strongly associated with past-month overdose indicators.

CONCLUSIONS

Psychometrics for the opioid overdose risk behavior subscales identified suggest the ongoing utility of risk behavioral instrumentation for epidemiological research and clinical practice focused on risk communication and minimization. Use of the entire ORBS-2 measure can provide insight into the proximal/behavioral factors of greatest concern to reduce overdose mortality.

"Know your epidemic, know your response": Epidemiological assessment of the substance use disorder crisis in the United States

The United States (U.S.) is currently experiencing a substance use disorders (SUD) crisis with an unprecedented magnitude. The objective of this study was to recognize and characterize the most vulnerable populations at high risk of SUD mortality in the U.S., and to identify the locations where these vulnerable population are located. We obtained the most recent available mortality data for the U.S. population aged 15-84 (2005-2017) from the Centers for Diseases and Prevention (CDC). Our analysis focused on the unintentional substance poisoning to estimate SUD mortality. We computed health-related comorbidities and socioeconomic association with the SUD distribution. We identified the most affected populations and conducted a geographical clustering analysis to identify places with increased concentration of SUD related deaths. From 2005-2017, 463,717 SUD-related deaths occurred in the United States. White population was identified with the highest SUD death proportions. However, there was a surge of the SUD epidemic in the Black male population, with a sharp increase in the SUD-related death rate since 2014. We also found that an additional average day of mental distress might increase the relative risk of SUD-related mortality by 39%. The geographical distribution of the epidemic showed clustering in the West and Mid-west regions of the U.S. In conclusion, we found that the SUD epidemic in the U.S. is characterized by the emergence of several micro-epidemics of different intensities across demographic groups and locations within the country. The comprehensive description of the epidemic presented in this study could assist in the design and implementation of targeted policy interventions for addiction mitigation campaigns.

A Critical Review of the Social and Behavioral Contributions to the Overdose Epidemic

More than 750,000 people in the United States died from an overdose between 1999 and 2018; two-thirds of those deaths involved an opioid. In this review, we present trends in opioid overdose rates during this period and discuss how the proliferation of opioid prescribing to treat chronic pain, changes in the heroin and illegally manufactured opioid synthetics markets, and social factors, including deindustrialization and concentrated poverty, contributed to the rise of the overdose epidemic. We also examine how current policies implemented to address the overdose epidemic may have contributed to reducing prescription opioid overdoses but increased overdoses involving illegal opioids. Finally, we identify new directions for research to understand the causes and solutions to this critical public health problem, including research on heterogeneous policy effects across social groups, effective approaches to reduce overdoses of illegal opioids, and the role of social contexts in shaping policy implementation and impact.

Examining the gender composition of drug injecting initiation events: A mixed methods investigation of three North American contexts

BACKGROUND

Gender influences the health and social risks faced by individuals initiating drug injecting. Using mixed methods across three settings in North America, we investigated the gender composition of injection initiation events and the gendered risk environments in which they occurred.

METHODS

The PReventing Injecting by Modifying Existing Responses (PRIMER) study pooled data from three prospective community-recruited cohorts of people who inject drugs (PWID) in San Diego, USA, Vancouver, Canada, and Tijuana, Mexico. A qualitative subsample provided narrative data on their experiences of, and the contexts for, injection initiation events. Guided by Rhodes' risk environment framework, we examined the gender composition of initiation events stratified by city, and analyzed qualitative data using abductive thematic analyses.

RESULTS

Among 2,622 PWID (Tijuana: n = 531; San Diego: n = 352; Vancouver: n = 1,739), 112 (4.3%) reported providing initiation assistance to injection-naïve individuals in the previous six months. The proportion of gender concordant (e.g., male-male) initiation pairs varied, (χ2 = 10.32, p <0.001) with greater than expected concordance among pairs in Tijuana compared with those in Vancouver or San Diego. Sixty-one interviews provided context for the discrepancy across sites by highlighting the gendered injection initiation risk environments of prison/jail detention in Tijuana, intimate partnerships in San Diego, and overdose risk in Vancouver.

CONCLUSIONS

These results highlight how gender influences injection initiation events within spatial, social, and economic risk environments, and how this influence varies across settings. These findings can inform interventions to reduce the risk of injection initiation and related harms.

Factor structure and psychometric properties of the Connor-Davidson resilience scale (CD-RISC) in individuals with opioid use disorder

AIMS

Resilience is defined as the capacity for an individual to maintain normal functioning and resist the development of psychiatric disorders in response to stress and trauma. Although previous investigators have acknowledged the important role of resilience in those with substance use disorders, this is the first study to investigate the reliability, validity, and factor structure of the Connor-Davidson Resilience Scale (CD-RISC-25) in a sample of individuals with opioid use disorder (OUD). Additionally, we explored the relationship between trait resilience and the severity of drug-related problems.

METHODS

Four hundred and three participants (22 % female) with OUD completed the CD-RISC-25, Beck Depression Inventory (BDI-II), and the self-report Addiction Severity Index (ASI). Confirmatory factor analysis (CFA) tested the originally proposed 5-factor solution of the CD-RISC-25.

RESULTS

CFA results indicated that a 5-factor model of the CD-RISC-25 performed somewhat better than the 1-factor solution. Pearson correlation revealed a negative association between CD-RISC-25 (M = 75.82, SD = 15.78) and ASI drug-use composite score (M = .25, SD=-0.16), r=-0.148, p<.01, and between CD-RISC-25 and BDI-II (M = 11.33, SD = 10.58), r=-.237, p<.001.

CONCLUSIONS

Albeit providing only limited support for the original 5-factor structure, our results indicate that the scale may be useful for screening individuals with OUD who have a vulnerability to stress. Consistent with prior studies, higher resilience was associated with lower depression symptoms and addiction severity, further demonstrating the CD-RISC-25 ability to predict psychiatric stability. To inform the development of more targeted interventions, future studies should examine resilience longitudinally, in addition to exploring more comprehensive approaches to measuring resilience.

Can a Neighborhood Fall Sick? Opioid Addiction, Collective Violence and Currents of Death in Contemporary India

Opioid abuse is an increasingly global phenomenon. Rather than assuming it to be a uniformly global or neoliberal pathology, how might we better understand comparative and locally specific dimensions of opioid addiction? Working with neighborhoods as a unit of analysis, this article analyzes the striking differences between patterns of addiction and violence in two proximate and seemingly similar urban poor neighborhoods in Delhi, India. Rather than global or national etiologies, I suggest that an attention to sharp ecological variation within epidemics challenges social scientists to offer more fine-grained diagnostics. Using a combination of quantitative and ethnographic methods, I show how heroin addiction and collective violence might be understood as expressions of what Durkheim called "suicido-genetic currents." I suggest the idea of varying currents as an alternative to the sociology of neighborhood "effects" in understanding significant differences in patterns of self-harm and injury across demographically similar localities.

The Increasing Prevalence of Fentanyl: A Urinalysis-Based Study Among Individuals With Opioid Use Disorder in New York City

BACKGROUND AND OBJECTIVES

Opioid-related overdose deaths in North America have increased drastically, partially due to the increased prevalence of illicitly manufactured fentanyl. The current study sought to assess the prevalence and intentionality of fentanyl use among individuals with opioid use disorder (OUD).

METHODS

For this secondary analysis (study 1) we screened a total of 1118 urine samples from 316 participants with OUD from 2016 to 2019. Fentanyl knowledge and intentionality of use were assessed in a separate OUD sample (study 2; N = 33).

RESULTS

In study 1, 34.6% of all urine samples tested positive for fentanyl. Overall, 149 (47.2%) participants provided more than or equal to one urine sample that tested fentanyl-positive, and 93 (29.4%) provided more than or equal to two fentanyl-positive samples. The number of fentanyl-positive samples, relative to the number of samples tested each year, increased by 330% from year 1 to 3. Study 2 found all participants had pre-existing knowledge that drugs may be adulterated with fentanyl, yet 67% were surprised by their own fentanyl-positive test result.

DISCUSSION AND CONCLUSIONS

Like previous studies, our data indicate the high prevalence of fentanyl exposure and low perception of fentanyl-related risk among individuals with OUD, respectively, suggesting that opioid overdose harm reduction efforts may need to focus more on drug users' understanding of risks related to fentanyl use and adulteration of drugs.

SCIENTIFIC SIGNIFICANCE

The current studies provide longitudinal data on fentanyl exposure prevalence and risk perception that is uniquely granular by assessing OUD treatment status, and by identifying potential associations between fentanyl exposure with the presence of other drug use and nonfatal overdose. (Am J Addict 2021;30:65-71).

Suspected Nonfatal Drug-Related Overdoses Among Youth in the US: 2016-2019

BACKGROUND AND OBJECTIVES

During the current drug overdose crisis, the United States is experiencing a significant number of overdose deaths, hospitalizations, and emergency department visits. Given the vulnerability of young persons to substance use, it is important to assess how this crisis affects the nation's youth. In this study, we investigate trends in suspected nonfatal drug-related overdoses (all-drugs, opioids, heroin, and stimulants) among youth using syndromic surveillance data from 2016 to 2019.

METHODS

A retrospective analysis of emergency department syndromic surveillance data were used to detect quarterly trends in suspected drug overdoses from April 2016 through September 2019 among youth aged 0 to 10, 11 to 14, and 15 to 24 years. Syndrome definitions were developed using chief complaint free-text and discharge diagnosis codes to identify overdoses involving all-drugs, opioids, heroin, and stimulants. Pearson χ² tests detected quarter-to-quarter changes, and joinpoint regression analysis assessed trends over time.

RESULTS

On average, there was a 2.0% increase for youth aged 0 to 10 years and a 2.3% increase for youth aged 11 to 14 years for suspected all-drug overdoses. Suspected heroin overdoses decreased by an average of 3.3% per quarter for youth aged 15 to 24 years. Among all age groups, suspected stimulant overdoses increased across the study period, 3.3% for 0 to 10-year-olds, 4.0% for 11- to 14-year-olds, and 2.3% for 15- to 24-year-olds.

CONCLUSIONS

Suspected stimulant-involved drug overdoses appear to be rising among youth. These findings could inform targeted interventions, such as stimulant-focused prevention, and comprehensive approaches, including school-based prevention and other strategies to lower morbidity and mortality.

Association of Electronic Prescribing of Controlled Substances With Opioid Prescribing Rates

IMPORTANCE

The majority of US states have passed mandates requiring the use of electronic prescribing of controlled substances (EPCS) as a tool to reduce rates of opioid prescribing. It is not known whether increasing use of EPCS will have the intended effect.

OBJECTIVE

To assess the association between use of EPCS and trends in opioid prescribing.

DESIGN, SETTING, AND PARTICIPANTS

In this retrospective, longitudinal cohort study of all patients and prescribers in the 50 US states and the District of Columbia from 2010 to 2018, changes in state-level use of EPCS and concurrent changes in opioid prescribing in each state are described. Then the association between changes in the use of EPCS and opioid prescribing are estimated using state and year fixed-effects models that include covariates for policy change and state demographic change. Data Analysis was performed on May 5, 2020.

MAIN OUTCOMES AND MEASURES

The proportion of controlled substances in each state prescribed using EPCS based on opioid prescriptions per 100 persons and morphine milligram equivalents (MME) of opioids.

RESULTS

In 2018, the population-weighted percent of opioids prescribed using EPCS was 27%, up from 0% as of 2013. National rates of opioid prescriptions decreased from 78 prescriptions per 100 persons in 2013 to 53 in 2018. Over the same period, there was a decrease from 64 071 MME per 100 persons in 2013 to 40 906 MME per 100 persons in 2018, representing 36% of the 2013 level. By 2018, EPCS increased to 69.4% in states with mandates for its use and 23.6% in states without mandates. In multivariable models, a 10 percentage-point increase in the use of EPCS was associated with an additional 2 prescriptions per 100 persons (95% CI, 1.3-2.8) and a 0.8% (95% CI, 0.06%-1.5%) increase in MME per 100 persons.

CONCLUSIONS AND RELEVANCE

These data suggest that an increased use of EPCS was not associated with decreased opioid prescribing or a decrease in the amount prescribed and may have been associated with a small increase in opioid prescribing. Opioid prescribing is associated with a variety of social and public health factors, and thus, despite the appeal, EPCS adoption alone may be insufficient to reduce opioid prescribing. Policy makers should consider levers to ensure that EPCS is integrated with outside data and that information is actively used to inform prescribing decisions.

Prescription Opioid Dispensing Patterns Prior to Heroin Overdose in a State Medicaid Program: a Case-Control Study

BACKGROUND

A large proportion of individuals who use heroin report initiating opioid use with prescription opioids. However, patterns of prescription opioid use preceding heroin-related overdose have not been described.

OBJECTIVE

To describe prescription opioid use in the year preceding heroin overdose.

DESIGN

Case-control study comparing prescription opioid use with a heroin-involved overdose, non-heroin-involved opioid overdose, and non-overdose controls from 2015 to 2017.

PARTICIPANTS

Oregon Medicaid beneficiaries with linked administrative claims, vital statistics, and prescription drug monitoring program data.

MAIN MEASURES

Opioid, benzodiazepine, and other central nervous system depressant prescriptions preceding overdose; among individuals with one or more opioid prescription, we assessed morphine milligram equivalents per day, overlapping prescriptions, prescriptions from multiple prescribers, long-term use, and discontinuation of long-term use.

KEY RESULTS

We identified 1458 heroin-involved overdoses (191 fatal) and 2050 non-heroin-involved opioid overdoses (266 fatal). In the 365 days prior to their overdose, 45% of individuals with a heroin-involved overdose received at least one prescribed opioid compared with 78% of individuals who experienced a non-heroin-involved opioid overdose (p < 0.001). For both heroin- and non-heroin-involved overdose cases, the likelihood of receiving an opioid increased with age. Among heroin overdose cases with an opioid dispensed, the rate of multiple pharmacy use was the only high-risk opioid pattern that was greater than non-overdose controls (adjusted odds ratio 3.2; 95% confidence interval 1.48 to 6.95). Discontinuation of long-term opioid use was not common prior to heroin overdose and not higher than discontinuation rates among non-overdose controls.

CONCLUSIONS

Although individuals with a heroin-involved overdose were less likely to receive prescribed opioids in the year preceding their overdose relative to non-heroin opioid overdose cases, prescription opioid use was relatively common and increased with age. Discontinuation of long-term prescription opioid use was not associated with heroin-involved overdose.

Paralytic ileus in the United States: A cross-sectional study from the national inpatient sample

Introduction:

Paralytic ileus is a common clinical condition leading to significant morbidity and mortality. Most studies to date have focused on postoperative ileus, a common but not exclusive cause of the condition. There are limited epidemiological data regarding the incidence and impact of paralytic ileus and its relationship to other clinical conditions. In this cross-sectional study, we analyzed national inpatient hospitalization trends, demographic variation, cost of care, length of stay, and mortality for paralytic ileus hospitalizations as a whole.

Methods:

The National Inpatient Sample database was used to identify all hospitalizations with the diagnosis of paralytic ileus (International Classification of Diseases, 9th Revision code 560.1) as primary or secondary diagnosis during the period from 2001 to 2011. Statistical analysis was performed using Cochran–Armitage trend test, Wilcoxon rank sum test, and Poisson regression.

Results:

In 2001, there were 362,561 hospitalizations with the diagnosis of paralytic ileus as compared to 470,110 in 2011 (p < 0.0001). The age group 65–79 years was most commonly affected by paralytic ileus throughout the study period. In-hospital all-cause mortality decreased from 6.03% in 2001 to 5.10% in 2011 (p < 0.0001). However, the average cost of care per hospitalization increased from US$19,739 in 2001 to US$26,198 in 2011 (adjusted for inflation, p < 0.0001).

Conclusion:

There was a significant rise in the number of hospitalizations of paralytic ileus with increased cost of care and reduced all-cause mortality.

A mixed-methods approach to understanding overdose risk-management strategies among a nationwide convenience sample

BACKGROUND

This mixed-methods study compared drug use histories between individuals who had a reported non-fatal overdose to individuals who did not and described the overdose risk-management strategies as they were experienced by a sample of people who use drugs (PWUD). Shifts from non-medical prescription opioid use (NMPOU) to the use of heroin and synthetic opioids have been implicated in national increases in overdose incidences in the United States. However, relatively limited data exists regarding the narrative experiences of the evolving overdose risk management strategies among a nationwide sample of PWUD.

METHODS

Data recruitment was conducted via Amazon's mTurk crowdsourcing technology and was collected through semi-structured interviews that occurred in 2019. Participants (N = 60) with a history of NMPOU with transition to heroin or fentanyl use were recruited.

RESULTS

Participants reporting a previous non-fatal overdose were more likely to report a history of injection drug use, a history of heroin injection, greater overdose risk knowledge, and current medication for opioid use disorder (MOUD) use. Qualitative analysis revealed that participants attempted to mitigate overdose risk in primarily three ways: 1) self-regulation; 2) harm reduction; and 3) passive approach. Self-regulatory measures included administering small or incremental dosing, being mindful of personal tolerance limits, and avoiding the initiation of injection drug use. Harm reduction measures used to protect from overdose included carrying Narcan and relying on trusted drug-suppliers as references to drug purity. A passive approach indicated that participants relied on "luck" or divine support systems where religiosity and faith were endorsed as factors that mitigated personal overdose risk.

CONCLUSION

Participants reported successful overdose mitigation via self-regulation, which may suggest that PWUDs were capable at managing their drug use amid the overdose crisis. The importance of the drug-supplier relationship was critical to many in reducing their overdose risk as formal harm reduction services (e.g., safe injection sites) remain inaccessible in the U.S. Implications for drug policy and harm reduction interventions are discussed.

Concurrent Opioid and Benzodiazepine Utilization Patterns and Predictors Among Community-Dwelling Adults in the United States

OBJECTIVE

Using benzodiazepines and opioids together substantially increases the risk of fatal overdose. Yet, concurrent benzodiazepine and opioid prescribing rates continue to increase amid the opioid overdose epidemic. Therefore, this study sought to identify patterns and predictors associated with self-reported concurrent benzodiazepine and opioid use among community-dwelling adults.

METHODS

This retrospective, cross-sectional study used Medical Expenditure Panel Survey data from 2011, 2013, and 2015. The study population included adults (age ≥18) who did not die during the calendar year. The dependent variable was concurrent benzodiazepine and opioid use, which was identified with Multum Lexicon therapeutic class codes. Multivariable logistic regression analysis was conducted to examine the association of various individual-level factors with concurrent benzodiazepine and opioid use.

RESULTS

The final study sample consisted of 44,808 individuals (unweighted), of which 680 (1.6%) (weighted frequency=7,806,636) reported concurrent benzodiazepine and opioid use. Several individual-level factors were significantly associated with reporting use of this combination. For example, individuals with anxiety were more likely to report using both benzodiazepines and opioids (odds ratio [OR]=9.61, 95% confidence interval [CI]=7.37-12.5), and those with extreme pain levels were more likely to report concurrent use (OR=5.11, 95% CI=2.98-8.78). Other predictors of reporting concurrent benzodiazepine and opioid use were depression, arthritis, region, race-ethnicity, insurance, activities disability, general and mental health status, and smoking status.

CONCLUSIONS

Several individual-level factors were associated with reporting concurrent benzodiazepine and opioid use. Therefore, enhanced educational interventions targeting both clinicians and community-dwelling adults are warranted to minimize use of this high-risk medication combination.

Identifying Predictive Characteristics of Opioid Medication Use among a Nationally Representative Sample of United States Older Adults with Pain and Comorbid Hypertension or Hypercholesterolemia

The prevalence of older adults with pain and comorbid cardiovascular conditions is increasing in the United States (U.S.). This retrospective, cross-sectional database study used 2017 Medical Expenditure Panel Survey data and hierarchical logistic regression models to identify predictive characteristics of opioid use among a nationally representative sample of older U.S. adults (aged ≥50 years) with pain in the past four weeks and comorbid hypertension (pain-hypertension group) or hypercholesterolemia (pain-hypercholesterolemia group). The pain-hypertension group included 2733 subjects (n = 803 opioid users) and the pain-hypercholesterolemia group included 2796 subjects (n = 795 opioid users). In both groups, predictors of opioid use included: White race versus others, Hispanic versus non-Hispanic ethnicity, 1 versus ≥5 chronic conditions, little/moderate versus quite a bit/extreme pain, good versus fair/poor perceived mental health, functional limitation versus no functional limitation, smoker versus non-smoker, and Northeast versus West census region. In addition, Midwest versus West census region was a predictor in the pain-hypertension group, and 4 versus ≥5 chronic conditions was a predictor in the pain-hypercholesterolemia group. In conclusion, several characteristics of older U.S. adults with pain and comorbid hypertension or hypercholesterolemia were predictive of opioid use. These characteristics could be addressed to optimize individuals' pain management and help address the opioid overdose epidemic.

Economic Evaluation of Interventions to Address Opioid Misuse: A Systematic Review of Methods Used in Simulation Modeling Studies

OBJECTIVES

Several evidence-based interventions exist for people who misuse opioids, but there is limited guidance on optimal intervention selection. Economic evaluations using simulation modeling can guide the allocation of resources and help tackle the opioid crisis. This study reviews methods employed by economic evaluations using computer simulations to investigate the health and economic effects of interventions meant to address opioid misuse.

METHODS

We conducted a systematic mapping review of studies that used simulation modeling to support the economic evaluation of interventions targeting prevention, treatment, or management of opioid misuse or its direct consequences (ie, overdose). We searched 6 databases and extracted information on study population, interventions, costs, outcomes, and economic analysis and modeling approaches.

RESULTS

Eighteen studies met the inclusion criteria. All of the studies considered only one segment of the continuum of care. Of the studies, 13 evaluated medications for opioid use disorder, and 5 evaluated naloxone distribution programs to reduce overdose deaths. Most studies estimated incremental cost per quality-adjusted life-years and used health system and/or societal perspectives. Models were decision trees (n = 4), Markov (n = 10) or semi-Markov models (n = 3), and microsimulations (n = 1). All of the studies assessed parameter uncertainty though deterministic and/or probabilistic sensitivity analysis, 4 conducted formal calibration, only 2 assessed structural uncertainty, and only 1 conducted expected value of information analyses. Only 10 studies conducted validation.

CONCLUSIONS

Future economic evaluations should consider synergies between interventions and examine combinations of interventions to inform optimal policy response. They should also more consistently conduct model validation and assess the value of further research.

Examining correlations between opioid dispensing and opioid-related hospitalizations in Canada, 2007-2016

BACKGROUND

High levels of opioid-related mortality, as well as morbidity, contribute to the excessive opioid-related disease burden in North America, induced by high availability of opioids. While correlations between opioid dispensing levels and mortality outcomes are well-established, fewer evidence exists on correlations with morbidity (e.g., hospitalizations).

METHODS

We examined possible overtime correlations between medical opioid dispensing and opioid-related hospitalizations in Canada, by province, 2007-2016. For dispensing, we examined annual volumes of medical opioid dispensing derived from a representative, stratified sample of retail pharmacies across Canada. Raw dispensing information for 'strong opioids' was converted into Defined Daily Doses per 1000 population per day (DDD/1000/day). Opioid-related hospitalization rates referred to opioid poisoning-related admissions by province, for fiscal years 2007-08 to 2016-17, drawn from the national Hospital Morbidity Database. We assessed possible correlations between opioid dispensing and hospitalizations by province using the Pearson product moment correlation; correlation values (r) and confidence intervals were reported.

RESULTS

Significant correlations for overtime correlations between population-levels of opioid dispensing and opioid-related hospitalizations were observed for three provinces: Quebec (r = 0.87, CI: 0.49-0.97; p = 0.002); New Brunswick (r = 0.85;CI: 0.43-0.97; p = 0.004) and Nova Scotia (r = 0.78; CI:0.25-0.95; p = 0.012), with an additional province, Saskatchewan, (r = 0.073; CI:-0.07-0.91;p = 0.073) featuring borderline significance.

CONCLUSIONS

The correlations observed further add to evidence on opioid dispensing levels as a systemic driver of population-level harms. Notably, correlations were not identified principally in provinces with reported high contribution levels (> 50%) of illicit opioids to mortality, which are not captured by dispensing data and so may have distorted or concealed potential correlation effects due to contamination.

Variation in Abuse-Deterrent Formulation Opioid Prescribing in California, Florida, and Kentucky in 2018

PURPOSE

Abuse-deterrent formulation (ADF) opioid analgesics have been developed as a means to address prescription opioid abuse. ADF opioid use in clinical practice is not well described in the literature. This study characterizes ADF opioid prescribing patterns in 3 diverse states.

METHODS

This study used data from prescription drug monitoring programs (PDMPs) in California, Florida, and Kentucky. The sample includes all ADF opioid prescriptions for patients ≥18 years old during the study period (CY 2018). Standardized prescribing rates were calculated by age, sex, and county rurality. The ADF opioid prescribing rate was calculated per 1,000 adult recipients of opioid analgesics.

FINDINGS

The rate of ADF prescribing per 1,000 adult recipients of opioid analgesics was nearly twice as high in Florida (14.57; 95% CI: 14.44-14.69) than in California (8.30; 95% CI: 8.22-8.37) or Kentucky (8.20; 95% CI: 8.01-8.39). ADF prescribing rates were highest among adults ages 55-74 years and among males. ADF opioid prescribing in rural counties represented a greater proportion of total patients using opioid analgesics than in metro counties in California (RR 1.40; CI: 1.28-1.53). Opposite and less pronounced variation was observed in Kentucky (RR 0.93; 95% CI: 0.88-0.98), and a significant difference was not observed in Florida (RR 0.68; 95% CI: 0.38-1.19).

CONCLUSIONS

There were significant differences in the ADF prescribing rates among the 3 states and in rural versus metro counties within 2 states. ADF opioid prescribing by age and sex showed similar trends within states. Further research is needed to elucidate contextual factors which may lead to prescribing variation.