An individual-based dynamic model to assess interventions to mitigate opioid overdose risk.

BACKGROUND: Illicit opioid overdose continues to rise in North America and is a leading cause of death. Mathematical modeling is a valuable tool to investigate the epidemiology of this public health issue, as it can characterize key features of population outcomes and quantify the broader effect of structural and interventional changes on overdose mortality. The aim of this study is to quantify and predict the impact of key harm reduction strategies at differing levels of scale-up on fatal and nonfatal overdose among a population of people engaging in unregulated opioid use in Toronto. METHODS: An individual-based model for opioid overdose was built featuring demographic and behavioural variation among members of the population. Key individual attributes known to scale the risk of fatal and nonfatal overdose were identified and incorporated into a dynamic modeling framework, wherein every member of the simulated population encompasses a set of distinct characteristics that govern demographics, intervention usage, and overdose incidence. The model was parametrized to fatal and nonfatal overdose events reported in Toronto in 2019. The interventions considered were opioid agonist therapy (OAT), supervised consumption sites (SCS), take-home naloxone (THN), drug-checking, and reducing fentanyl in the drug supply. Harm reduction scenarios were explored relative to a baseline model to examine the impact of each intervention being scaled from 0% use to 100% use on overdose events. RESULTS: Model simulations resulted in 3690.6 nonfatal and 295.4 fatal overdoses, coinciding with 2019 data from Toronto. From this baseline, at full scale-up, 290 deaths were averted by THN, 248 from eliminating fentanyl from the drug supply, 124 from SCS use, 173 from OAT, and 100 by drug-checking services. Drug-checking and reducing fentanyl in the drug supply were the only harm reduction strategies that reduced the number of nonfatal overdoses. CONCLUSIONS: Within a multi-faceted harm reduction approach, scaling up take-home naloxone, and reducing fentanyl in the drug supply led to the largest reduction in opioid overdose fatality in Toronto. Detailed model simulation studies provide an additional tool to assess and inform public health policy on harm reduction.

Risk factors for persistent fatal opioid-involved overdose clusters in Massachusetts 2011-2021: a spatial statistical analysis with socio-economic, accessibility, and prescription factors.

BACKGROUND: Fatal opioid-involved overdose rates increased precipitously from 5.0 per 100,000 population to 33.5 in Massachusetts between 1999 and 2022. METHODS: We used spatial rate smoothing techniques to identify persistent opioid overdose-involved fatality clusters at the ZIP Code Tabulation Area (ZCTA) level. Rate smoothing techniques were employed to identify locations of high fatal opioid overdose rates where population counts were low. In Massachusetts, this included areas with both sparse data and low population density. We used Local Indicators of Spatial Association (LISA) cluster analyses with the raw incidence rates, and the Empirical Bayes smoothed rates to identify clusters from 2011 to 2021. We also estimated Empirical Bayes LISA cluster estimates to identify clusters during the same period. We constructed measures of the socio-built environment and potentially inappropriate prescribing using principal components analysis. The resulting measures were used as covariates in Conditional Autoregressive Bayesian models that acknowledge spatial autocorrelation to predict both, if a ZCTA was part of an opioid-involved cluster for fatal overdose rates, as well as the number of times that it was part of a cluster of high incidence rates. RESULTS: LISA clusters for smoothed data were able to identify whether a ZCTA was part of a opioid involved fatality incidence cluster earlier in the study period, when compared to LISA clusters based on raw rates. PCA helped in identifying unique socio-environmental factors, such as minoritized populations and poverty, potentially inappropriate prescribing, access to amenities, and rurality by combining socioeconomic, built environment and prescription variables that were highly correlated with each other. In all models except for those that used raw rates to estimate whether a ZCTA was part of a high fatality cluster, opioid overdose fatality clusters in Massachusetts had high percentages of Black and Hispanic residents, and households experiencing poverty. The models that were fitted on Empirical Bayes LISA identified this phenomenon earlier in the study period than the raw rate LISA. However, all the models identified minoritized populations and poverty as significant factors in predicting the persistence of a ZCTA being part of a high opioid overdose cluster during this time period. CONCLUSION: Conducting spatially robust analyses may help inform policies to identify community-level risks for opioid-involved overdose deaths sooner than depending on raw incidence rates alone. The results can help inform policy makers and planners about locations of persistent risk.

A simple heuristic for allocating opioid settlement funding to reduce overdose mortality in the United States.

As resolution for opioid-related claims and litigation against pharmaceutical manufacturers and other stakeholders, state and local governments are newly eligible for millions of dollars of settlement funding to address the overdose crisis in the United States. To inform effective use of opioid settlement funds, we propose a simple framework that highlights the principal determinants of overdose mortality: the number of people at risk of overdose each year, the average annual number of overdoses per person at risk, and the average probability of death per overdose event. We assert that the annual number of overdose deaths is a function of these three determinants, all of which can be modified through public health intervention. Our proposed heuristic depicts how each of these drivers of drug-related mortality - and the corresponding interventions designed to address each term - operate both in isolation and in conjunction. We intend for this framework to be used by policymakers as a tool for identifying and evaluating public health interventions and funding priorities that will most effectively address the structural forces shaping the overdose crisis and reduce overdose deaths.

Scaling Emergency Department Opioid Use Disorder Treatment Across California to Reduce Overdose Deaths, 2019-2023.

Since April 2019, CA Bridge has worked with emergency departments (EDs) in diverse geographic and emergency care settings across California to scale up low-threshold buprenorphine access, patient navigation programs, harm reduction services, and take-home naloxone. Between April 2019 and June 2023, 268 (81.0%) of 331 acute care hospitals in California received funding and technical assistance from CA Bridge and completed data reporting. These hospitals provided navigation services during 279 025 patient encounters and gave patients buprenorphine in 89 549 ED visits. (Am J Public Health. 2024;114(9):874-878. https://doi.org/10.2105/AJPH.2024.307710).

United States marijuana legalization and opioid mortality trends before and during the first year of the COVID-19 pandemic.

BACKGROUND: To determine if marijuana legalization was associated with reduced opioid mortality. STUDY DESIGN: The United States (US) opioid mortality trend during the 2010-2019 decade was compared in states and District of Columbia (jurisdictions) that had implemented marijuana legalization with states that had not. Acceleration of opioid mortality during 2020, the first year of the coronavirus disease 2019 (COVID-19) pandemic, was also compared in recreational and medicinal-only legalizing jurisdictions. METHODS: Joinpoint methodology was applied to the Centers for Disease Control and Prevention WONDER data. Trends in legalizing jurisdictions were cumulative aggregates. RESULTS: The overall opioid and fentanyl death rates and the percentage of opioid deaths due to fentanyl increased more during 2010-2019 in jurisdictions that legalized marijuana than in those that did not (pairwise comparison p = 0.007, 0.05, and 0.006, respectively). By 2019, the all-opioid and fentanyl death rates were 44 and 50 percent greater in the legalizing than in the nonlegalizing jurisdictions, respectively. When the COVID-19 pandemic hit in 2020, jurisdictions that implemented recreational marijuana legalization before 2019 had significantly greater increases in both overall opioid and fentanyl death rates than jurisdictions with medicinal-only legalization. For all-opioids, the mean (95 percent confidence interval) 2019-to-2020 increases were 46.5 percent (36.6, 56.3 percent) and 29.1 percent (20.2, 37.9 percent), respectively (p = 0.02). For fentanyl, they were 115.6 percent (80.2, 151.6 percent) and 55.4 percent (31.6, 79.2 percent), respectively (p = 0.01). CONCLUSIONS: During the past decade, marijuana legalization in the US was associated at the jurisdiction level with a greater acceleration in opioid death rate. An even greater increase in opioid mortality occurred in recreational-legalizing jurisdictions with the onset of the COVID-19 pandemic. Marijuana legalization is correlated with worsening of the US opioid epidemic.

Racial/ethnic trends in opioid and polysubstance opioid overdose mortality in adolescents and young adults, 1999-2020.

OBJECTIVES: Previous reports have described variations in opioid overdose mortalities among different race/ethnicity groups. We have analyzed racial/ethnicity trends in opioid and polysubstance opioid overdose mortalities in adolescents and young adults to further characterize differences and potential sub-epidemics within this specific population. METHODS: We used mortality data from the U.S. Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) Multiple Cause of Death file from 1999 to 2020. Drug overdose mortalities were identified using International Classification of Diseases, Tenth Revision (ICD-10) codes. Joinpoint regression was used to examine mortality rates for all opioids, opioids with a stimulant, opioids with benzodiazepines, and opioids with alcohol among racial/ethnic groups (non-Hispanic white, non-Hispanic Black, Hispanic, non-Hispanic other) in adolescents and young adults. RESULTS: The Average Annual Percent Change (AAPC) for mortality due to opioid and polysubstance opioid overdose increased for all racial/ethnic groups where data was available for analysis from 1999 to 2020. For mortality due to any opioid and any opioid with a stimulant, the greatest AAPC was seen among non-Hispanic Blacks. CONCLUSIONS: Unprecedented increases in mortality due to opioid overdose occurred in the last two decades among adolescents and young adults. Heterogenous trends support the notion that the previously defined opioid overdose epidemic "waves" may not accurately depict the effects of the crisis in all race/ethnicity groups. Additionally, alarming increases in opioid-stimulant overdose mortality starting in 2012 further characterize the interrelated effects of the third and fourth waves.

Reducing overdose deaths among persons with opioid use disorder in connecticut.

BACKGROUND: People in Connecticut are now more likely to die of a drug-related overdose than a traffic accident. While Connecticut has had some success in slowing the rise in overdose death rates, substantial additional progress is necessary. METHODS: We developed, verified, and calibrated a mechanistic simulation of alternative overdose prevention policy options, including scaling up naloxone (NLX) distribution in the community and medications for opioid use disorder (OUD) among people who are incarcerated (MOUD-INC) and in the community (MOUD-COM) in a simulated cohort of people with OUD in Connecticut. We estimated how maximally scaling up each option individually and in combinations would impact 5-year overdose deaths, life-years, and quality-adjusted life-years. All costs were assessed in 2021 USD, employing a health sector perspective in base-case analyses and a societal perspective in sensitivity analyses, using a 3% discount rate and 5-year and lifetime time horizons. RESULTS: Maximally scaling NLX alone reduces overdose deaths 20% in the next 5 years at a favorable incremental cost-effectiveness ratio (ICER); if injectable rather than intranasal NLX was distributed, 240 additional overdose deaths could be prevented. Maximally scaling MOUD-COM and MOUD-INC alone reduce overdose deaths by 14% and 6% respectively at favorable ICERS. Considering all permutations of scaling up policies, scaling NLX and MOUD-COM together is the cost-effective choice, reducing overdose deaths 32% at ICER $19,000/QALY. In sensitivity analyses using a societal perspective, all policy options were cost saving and overdose deaths reduced 33% over 5 years while saving society $338,000 per capita over the simulated cohort lifetime. CONCLUSIONS: Maximally scaling access to naloxone and MOUD in the community can reduce 5-year overdose deaths by 32% among people with OUD in Connecticut under realistic budget scenarios. If societal cost savings due to increased productivity and reduced crime costs are considered, one-third of overdose deaths can be reduced by maximally scaling all three policy options, while saving money.

Contemporary burden and trends of opioid-overdose mortality in New York State.

BACKGROUND: Limited research exists on contemporary opioid overdose mortality burden and trends in New York State, with most studies focusing on New York City. This study aimed to assess opioid overdose burden and death trends in New York State by age, sex, race/ethnicity, geographic area, opioid type, and overdose intent from 1999 to 2020. METHODS: Mortality data were obtained from the Centers for Disease Control and Prevention's WONDER database. Opioid overdose decedents were identified using relevant International Classification of Diseases, 10th Revision codes. Joinpoint regression analyzed trends, estimating annual and average annual percentage changes in age-adjusted mortality rates (AAMR). 95% confidence intervals were derived using the Parametric Method. RESULTS: From 1999 to 2020, New York State recorded 34,109 opioid overdose deaths (AAMR = 7.9 per 100,000 persons; 95% CI: 7.8-7.9). The overall trend increased by 12.6% per year (95% CI: 10.8, 14.4) from 2004 to 2020. Subgroups exhibited varying trends, with an 11.1% yearly increase among Non-Hispanic White persons from 2007 to 2020 (95% CI: 9.0, 13.2), a 24.6% annual rise among Non-Hispanic Black persons from 2012 to 2020 (95% CI: 17.7, 31.8), and an 18.3% increase yearly among Hispanic individuals from 2011 to 2020 (95% CI: 14.0, 22.9). Recent trends have worsened in both males and females, across all age groups, in both New York City (NYC) and areas outside NYC, and for heroin, natural and semisynthetic opioids, and synthetic opioids. CONCLUSIONS: Opioid overdose mortality in New York State has worsened significantly in the last two decades. Further research is essential to identify driving factors for targeted public health interventions.

A Dynamic Model of Opioid Overdose Deaths in Canada during the Co-Occurring Opioid Overdose Crisis and COVID-19 Pandemic.

With over 40,000 opioid-related overdose deaths between January 2016 and June 2023, the opioid-overdose crisis is a significant public health concern for Canada. The opioid crisis arose from a complex system involving prescription opioid use, the use of prescription opioids not as prescribed, and non-medical opioid use. The increasing presence of fentanyl and its analogues in the illegal drugs supply has been an important driver of the crisis. In response to the overdose crisis, governments at the municipal, provincial/territorial, and federal levels have increased actions to address opioid-related harms. At the onset of the COVID-19 pandemic, concerns emerged over how the pandemic context may impact the opioid overdose crisis. Using evidence from a number of sources, we developed a dynamic mathematical model of opioid overdose death to simulate possible trajectories of overdose deaths during the COVID-19 pandemic. This model incorporates information on prescription opioid use, opioid use not as prescribed, non-medical opioid use, the level of fentanyl in the drug supply, and a measure of the proportion deaths preventable by new interventions. The simulated scenarios provided decision makers with insight into possible trajectories of the opioid crisis in Canada during the COVID-19 pandemic, highlighting the potential of the crisis to take a turn for the worse under certain assumptions, and thus, informing planning during a period when surveillance data were not yet available. This model provides a starting point for future models, and through its development, we have identified important data and evidence gaps that need to be filled in order to inform future action.

Characteristics of Opioid Toxicity Deaths Among Adolescents and Young Adults in Ontario Prior To and During the COVID-19 Pandemic.

PURPOSE: To characterize opioid toxicity deaths among adolescents and young adults in Ontario, Canada, prior to and during the first year of the COVID-19 pandemic. METHODS: We conducted a descriptive, cross-sectional study of opioid toxicity deaths among individuals aged 15-24 in Ontario in the year prior to (March 17, 2019, to March 16, 2020) and the first year of the pandemic (March 17, 2020, to March 16, 2021) using administrative health databases. We analyzed circumstances surrounding death, substances contributing to death, and health-care encounters prior to death. RESULTS: We identified 284 deaths among Ontarians aged 15-24, including 115 in the year preceding and 169 in the first year of the pandemic. Fentanyl contributed to 84.3% of deaths in the prepandemic year, rising to 93.5% (p = .012) the following year. Stimulants contributed to approximately half of deaths in both periods (41.7% prepandemic and 49.1% during pandemic). In both periods, roughly one in 4 decedents had a health-care encounter in the week prior to death and less than 20% of those with an opioid use disorder received opioid agonist treatment in the 30 days prior to death. DISCUSSION: Among young Ontarians, the number of opioid-related deaths increased by 47% in the first year of the COVID-19 pandemic. Fentanyl contributed to the vast majority of deaths, with non-opioid substances (primarily stimulants) also contributing to approximately half of deaths. Patterns of health-care utilization prior to death suggest opportunities to better connect this population to services that address opioid use disorder needs and promote harm reduction.

Higher First 30-Day Dose of Buprenorphine for Opioid Use Disorder Treatment Is Associated With Decreased Mortality.

OBJECTIVE: Buprenorphine is a medication for opioid use disorder that reduces mortality. This study aims to investigate the less well-understood relationship between the dose in the early stages of treatment and the subsequent risk of death. METHODS: We used Kentucky prescription monitoring data to identify adult Kentucky residents initiating transmucosal buprenorphine medication for opioid use disorder (January 2017 to November 2019). Average daily buprenorphine dose for days covered in the first 30 days of treatment was categorized as ≤8 mg, >8 to ≤16 mg, and >16 mg. Patients were followed for 365 days after the first 30 days of buprenorphine treatment. Endpoints were opioid-involved overdose death and death from other causes. Causes and dates of death were obtained using Kentucky death certificate records. Associations were evaluated using multivariable Fine and Gray models adjusting for patient baseline characteristics. RESULTS: In the cohort of 49,857 patients, there were 227 opioid-involved overdose deaths and 459 deaths from other causes. Compared with ≤8 mg, the adjusted subdistribution hazard ratio (aSHR) of opioid-involved overdose death decreased by 55% (aSHR, 0.45; 95% confidence interval [CI], 0.34-0.60) and 64% (aSHR, 0.36; 95% CI, 0.25-0.52) for patients receiving doses of >8 to ≤16 mg and >16 mg, respectively. The incidence of death from other causes was lower in patients receiving >8 to ≤16 mg (aSHR, 0.78; 95% CI, 0.62-0.98) and >16 mg (aSHR, 0.62; 95% CI, 0.47-0.80) versus ≤8 mg dose. CONCLUSIONS: Higher first 30-day buprenorphine doses were associated with reduced opioid-involved overdose death and death from other causes, supporting benefit of higher dosing in reducing mortality.

Examining the association of rurality with opioid-related morbidity and mortality in Georgia: A geospatial analysis.

INTRODUCTION: The US opioid epidemic continues to escalate, with overdose deaths being the most-used metric to quantify its burden. There is significant geographic variation in opioid-related outcomes. Rural areas experience unique challenges, yet many studies oversimplify rurality characterizations. Contextual factors, such as area deprivation, are also important to consider when understanding a community's need for treatment services and prevention programming. This study aims to provide a geospatial snapshot of the opioid epidemic in Georgia using several metrics of opioid-related morbidity and mortality and explore differences by rurality across counties. METHODS: This was a spatial ecologic study. Negative binominal regression was used to model the relationship of county rurality with four opioid-related outcomes - overdose mortality, emergency department visits, inpatient hospitalizations, and overdose reversals - adjusting for county-level sex, racial/ethnic, and age distributions. Area Deprivation Index was also included. RESULTS: There was significant geographic variation across the state for all four opioid-related outcomes. Counts remained highest among the metro areas. For rates, counties in the top quartile of rates varied by outcome and were often rural areas. In the final models, rurality designation was largely unrelated to opioid outcomes, with the exception of medium metro areas (inversely related to hospitalizations and overdose reversals) and non-core areas (inversely related to hospitalizations), as compared to large central metro areas. Higher deprivation was significantly related to increased ED visits and hospitalizations, but not overdose mortality and reversals. CONCLUSIONS: When quantifying the burden of the opioid epidemic in a community, it is essential to consider multiple outcomes of morbidity and mortality. Understanding what outcomes are problematic for specific communities, in combination with their demographic and socioeconomic context, can provide insight into gaps in the treatment continuum and potential areas for intervention. Additionally, compared to demographic and socioeconomic factors, rurality may no longer be a salient predictor of the severity of the opioid epidemic in an area.

Opioid-Related Overdose Deaths in Maryland (2018), by Industry and Occupation.

OBJECTIVES: Opioid-related overdose deaths (OROD) increase annually, yet little is known about workplace risk factors. This study assessed differences in OROD rates across industry and occupation in Maryland, in addition to demographic differences within industry and occupation. METHODS: The 2018 State Unintentional Drug Overdose Reporting System was used to compare OROD between industries and occupations. RESULTS: The leading industries in OROD included the following: construction, manufacturing, and transportation and warehousing. Occupational groups were similar: construction and extraction, production, and transportation and material moving. There were also differences by sex (greater rates in men), age (greater rates in older workers), and race/ethnicity (varied patterns in rates). CONCLUSIONS: Employers and state leaders should work collaboratively to target prevention and intervention for workplaces at highest risk for OROD. Construction was highest and needs supports that respond to the workplace culture.

State-level variation in distribution of oxycodone and opioid-related deaths from 2000 to 2021: an ecological study of ARCOS and CDC WONDER data in the USA.

OBJECTIVES: This study aims to characterise oxycodone's distribution and opioid-related overdoses in the USA by state from 2000 to 2021. DESIGN: This is an observational study. SETTING: More than 80 000 Americans died of an opioid overdose in 2021 as the USA continues to struggle with an opioid crisis. Prescription opioids play a substantial role, introducing patients to opioids and providing a supply of drugs that can be redirected to those seeking to misuse them. METHODS: The Drug Enforcement Administration annual summary reports from the Automation of Reports and Consolidated Orders System provided weights of oxycodone distributed per state by business type (pharmacies, hospitals and practitioners). Weights were converted to morphine milligram equivalents (MME) per capita and normalised for population. The Centers for Disease Control and Prevention Wide-ranging ONline Data for Epidemiologic Research provided mortality data for heroin, other opioids, methadone, other synthetic narcotics and other/unspecified narcotics. RESULTS: There was a sharp 280.13% increase in total MME/person of oxycodone from 2000 to 2010, followed by a slower 54.34% decrease from 2010 to 2021. Florida (2007-2011), Delaware (2003-2020) and Tennessee (2012-2021) displayed consistent and substantial elevations in combined MME/person compared with other states. In the peak year (2010), there was a 15-fold difference between the highest and lowest states. MME/person from only pharmacies, which constituted >94% of the total, showed similar results. Hospitals in Alaska (2000-2001, 2008, 2010-2021), Colorado (2008-2021) and DC (2000-2011) distributed substantially more MME/person over many years compared with other states. Florida stood out in practitioner-distributed oxycodone, with an elevation of almost 15-fold the average state from 2006 to 2010. Opioid-related deaths increased +806% from 2000 to 2021, largely driven by heroin, other opioids and other synthetic narcotics. CONCLUSIONS: Oxycodone distribution across the USA showed marked differences between states and business types over time. Investigation of opioid policies in states of interest may provide insight for future actions to mitigate opioid misuse.

Trends in Fatal Opioid-Related Overdose in American Indian and Alaska Native Communities, 1999-2021.

INTRODUCTION: Opioid-related overdose mortality rates have increased sharply in the U.S. over the past two decades, and inequities across racial and ethnic groups have been documented. Opioid-related overdose trends among American Indian and Alaska Natives require further quantification and assessment. METHODS: Observational, U.S. population-based registry data on opioid-related overdose mortality between 1999 and 2021 were extracted in 2023 using ICD-10 codes from the U.S. Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research multiple cause of death file by race, Hispanic ethnicity, sex, and age. Segmented time series analyses were conducted to estimate opioid-related overdose mortality growth rates among the American Indian and Alaska Native population between 1999 and 2021. Analyses were performed in 2023. RESULTS: Two distinct time segments revealed significantly different opioid-related overdose mortality growth rates within the overall American Indian and Alaska Native population, from 0.36 per 100,000 (95% CI=0.32, 0.41) between 1999 and 2019 to 6.5 (95% CI=5.7, 7.31) between 2019 and 2021, with the most pronounced increase among those aged 24-44 years. Similar patterns were observed within the American Indian and Alaska Native population with Hispanic ethnicity, but the estimated growth rates were generally steeper across most age groups than across the overall American Indian and Alaska Native population. Patterns of opioid-related overdose mortality growth rates were similar between American Indian and Alaska Native females and males between 2019 and 2021. CONCLUSIONS: Sharp increases in opioid-related overdose mortality rates among American Indian and Alaska Native communities are evident by age and Hispanic ethnicity, highlighting the need for culturally sensitive fatal opioid-related overdose prevention, opioid use disorder treatment, and harm-reduction efforts. Future research should aim to understand the underlying factors contributing to these high mortality rates and employ interventions that leverage the strengths of American Indian and Alaska Native culture, including the strong sense of community.

Hospitalization, Overdose, and Mortality After Opioid Prescriptions Tied to Ophthalmic Surgery.

PURPOSE: Opioid prescriptions continue to carry significant short- and long-term systemic risks, even after ophthalmic surgery. The goal of this study was to identify any association of opioid prescription, after ophthalmic surgery, with postoperative hospitalization, opioid overdose, opioid dependence, and all-cause mortality. DESIGN: Retrospective, cross-sectional analysis. PARTICIPANTS: Patients undergoing an ophthalmic surgery in the OptumLabs Data Warehouse. METHODS: We used deidentified administrative claims data from the OptumLabs Data Warehouse to create 3 cohorts of patients for analysis from January 1, 2016, to June 30, 2022. The first cohort consisted of 1-to-1 propensity score-matched patients who had undergone ophthalmic surgery and had filled a prescription for an opioid and not filled a prescription for an opioid. The second cohort consisted of patients who were considered opioid naïve and had filled a prescription for an opioid matched to patients who had not filled a prescription for an opioid. The last cohort consisted of opioid-naïve patients matched across the following morphine milligram equivalents (MME) groups: ≤ 40, 41-80, and > 80. MAIN OUTCOME MEASURES: Short- and long-term risks of hospitalization, opioid overdose, opioid dependency/abuse, and death were compared between the cohorts. RESULTS: We identified 1 577 692 patients who had undergone an ophthalmic surgery, with 312 580 (20%) filling an opioid prescription. Among all patients, filling an opioid prescription after an ophthalmic surgery was associated with increased mortality (hazard rate [HR], 1.28; 95% confidence interval [CI], 1.25-1.31; P < 0.001), hospitalization (HR, 1.51; 95% CI, 1.49-1.53; P < 0.001), opioid overdose (HR, 7.31; 95% CI, 6.20-8.61, P < 0.001), and opioid dependency (HR, 13.05; 95% CI, 11.48-14.84; P < 0.001) compared with no opioid prescription. Furthermore, we found that higher MME doses of opioids were associated with higher rates of mortality, hospitalization, and abuse/dependence. CONCLUSIONS: Patients who filled an opioid prescription after an ophthalmic surgery experienced higher rates of mortality, hospitalization, episodes of opioid overdose, and opioid dependence compared with patients who did not fill an opioid prescription. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Recreational and Medical Cannabis Legalization and Opioid Prescriptions and Mortality.

Importance: While some have argued that cannabis legalization has helped to reduce opioid-related morbidity and mortality in the US, evidence has been mixed. Moreover, existing studies did not account for biases that could arise when policy effects vary over time or across states or when multiple policies are assessed at the same time, as in the case of recreational and medical cannabis legalization. Objective: To quantify changes in opioid prescriptions and opioid overdose deaths associated with recreational and medical cannabis legalization in the US. Design, Setting, and Participants: This quasiexperimental, generalized difference-in-differences analysis used annual state-level data between January 2006 and December 2020 to compare states that legalized recreational or medical cannabis vs those that did not. Intervention: Recreational and medical cannabis law implementation (proxied by recreational and medical cannabis dispensary openings) between 2006 and 2020 across US states. Main Outcomes and Measures: Opioid prescription rates per 100 persons and opioid overdose deaths per 100 000 population based on data from the US Centers for Disease Control and Prevention. Results: Between 2006 and 2020, 13 states legalized recreational cannabis and 23 states legalized medical cannabis. There was no statistically significant association of recreational or medical cannabis laws with opioid prescriptions or overall opioid overdose mortality across the 15-year study period, although the results also suggested a potential reduction in synthetic opioid deaths associated with recreational cannabis laws (4.9 fewer deaths per 100 000 population; 95% CI, -9.49 to -0.30; P = .04). Sensitivity analyses excluding state economic indicators, accounting for additional opioid laws and using alternative ways to code treatment dates yielded substantively similar results, suggesting the absence of statistically significant associations between cannabis laws and the outcomes of interest during the full study period. Conclusions and Relevance: The results of this study suggest that, after accounting for biases due to possible heterogeneous effects and simultaneous assessment of recreational and medical cannabis legalization, the implementation of recreational or medical cannabis laws was not associated with opioid prescriptions or opioid mortality, with the exception of a possible reduction in synthetic opioid deaths associated with recreational cannabis law implementation.

Distribution of intranasal naloxone to potential opioid overdose bystanders in Sweden: effects on overdose mortality in a full region-wide study.

OBJECTIVES: Distribution of take-home naloxone is suggested to reduce opioid-related fatalities, but few studies have examined the effects on overdose deaths in the general population of an entire community. This study aimed to assess the effects on overdose deaths of a large-scale take-home naloxone programme starting in June 2018, using an observational design with a historic control period. DESIGN: From the national causes of death register, deaths diagnosed as X42 or Y12 (International Classification of Diseases, 10th revision, ICD-10) were registered as overdoses. Numbers of overdoses were calculated per 100 000 inhabitants in the general population, and controlled for data including only individuals with a prior substance use disorder in national patient registers, to focus on effects within the primary target population of the programme. The full intervention period (2019-2021) was compared with a historic control period (2013-2017). SETTING: Skåne county, Sweden. PARTICIPANTS: General population. INTERVENTIONS: Large-scale take-home naloxone distribution to individuals at risk of overdose. PRIMARY AND SECONDARY OUTCOME MEASURES: Decrease in overdose deaths per 100 000 inhabitants, in total and within the population with substance use disorder diagnosis. RESULTS: Annual average number of overdose deaths decreased significantly from 3.9 to 2.8 per 100 000 inhabitants from the control period to the intervention period (a significant decrease in men, from 6.7 to 4.3, but not in women, from 1.2 to 1.3). Significant changes remained when examining only prior substance use disorder patients, and decreases in overdose deaths could not be attributed to a change in treatment needs for opioid use disorders in healthcare and social services. CONCLUSIONS: The present study, involving 3 years of take-home naloxone distribution, demonstrated a decreased overdose mortality in the population, however, only in men. The findings call for further implementation of naloxone programmes, and for further studies of potential effects and barriers in women. TRIAL REGISTRATION NUMBER: NCT03570099.