No change in substance use disorders or overdose after implementation of state Earned Income Tax Credit (EITC).

BACKGROUND: Inadequate income is associated with higher likelihood of experiencing a substance use disorder (SUD). This study tests whether the earned income tax credit (EITC), which issues supplemental income for workers with children in the U.S., is associated with lower rates of SUD and fatal overdose. METHODS: We examined the effects of state-level refundable EITC presence and generosity (i.e., state EITC rate as a % of federal rate) on SUD-related outcomes (SUD prevalence and intentional and unintentional fatal overdose) using a difference-in-difference methodology, with both two-way fixed-effects models and event study plots. Several sensitivity analyses were conducted to assess the robustness of findings. Five data sources were used to create a combined state-level longitudinal dataset. RESULTS: We did not find significant effects of refundable EITC presence or generosity on unintentional or intentional fatal overdose or SUD prevalence in two-way models. Event study models detected a very slight upward shift in SUD prevalence following refundable EITC implementation (not seen in sensitivity analyses) and no significant effects of EITC implementation on any of the fatal overdose outcomes. CONCLUSIONS: Evidence regarding income support programs is being highly sought by policy makers as income support programs have become increasingly popular policy levers since the start of the COVID-19 pandemic. Our study indicates EITC policies likely have no impact on SUD or overdose, however, other income support programs without family restrictions are important to investigate further.

Cost-effectiveness of drug consumption rooms in France: a modelling study.

BACKGROUND: People who inject drugs (PWID) experience many health problems which result in a heavy economic and public health burden. To tackle this issue, France opened two drug consumption rooms (DCRs) in Paris and Strasbourg in 2016. This study assessed their long-term health benefits, costs and cost-effectiveness. METHODS: We developed a model to simulate two fictive cohorts for each city (n=2,997 in Paris and n=2,971 in Strasbourg) i) PWID attending a DCR over the period 2016-2026, ii) PWID attending no DCR. The model accounted for HIV and HCV infections, skin abscesses and related infective endocarditis, drug overdoses and emergency department visits. We estimated the number of health events and associated costs over 2016-2026, the lifetime number of quality-adjusted life-years (QALYs) and costs, and the incremental cost-effectiveness ratio (ICER). RESULTS: The numbers of abscesses and associated infective endocarditis, drug overdoses, and emergency department visits decreased significantly in PWID attending DCRs (-77%, -69%, and -65%, respectively) but the impact on HIV and HCV infections was modest (-11% and -6%, respectively). This resulted in savings of €6.6 (Paris) and €5.8 (Strasbourg) millions of medical costs. The ICER of DRCs was €30,600/QALY (Paris) and €9,200/QALY (Strasbourg). In scenario analysis where drug consumption spaces are implemented inside existing harm reduction structures, these ICERs decreased to €21,400/QALY and €2,500/QALY, respectively. CONCLUSIONS: Our findings show that DCRs are highly effective and efficient to prevent harms in PWID in France, and advocate extending this intervention to other cities by adding drug consumption spaces inside existing harm reduction centers.

"Deaths of despair" over the business cycle: New estimates from a shift-share instrumental variables approach.

This study presents new evidence of the effects of short-term economic fluctuations on suicide, fatal drug overdose, and alcohol-related mortality among working-age adults in the United States from 2003-2017. Using a shift-share instrumental variables approach, I find that a one percentage point increase in the aggregate employment rate decreases current-year non-drug suicides by 1.7 percent. These protective effects are concentrated among working-age men and likely reflect a combination of individual labor market experiences as well as the indirect effects of local economic growth. I find no consistent evidence that short-term business cycle changes affect drug or alcohol-related mortality. While the estimated protective effects are small relative to secular increases in suicide in recent decades, these findings are suggestive of important, short-term economic factors affecting specific causes of death and should be considered alongside the longer-term and multifaceted social, economic, and cultural determinants of America's "despair" epidemic.

Trends in Out-of-Pocket Costs for and Characteristics of Pharmacy-Dispensed Naloxone by Payer Type.

This study examines mean yearly out-of-pocket cost for naloxone dispensed from retail pharmacies by payer between 2018 and 2022 and by prescription characteristics and payer in 2022.

The economic burden of opioid use disorder and fatal opioid overdose in the United States, 2017.

BACKGROUND: The United States (U.S.) is experiencing an ongoing opioid crisis. Economic burden estimates that describe the impact of the crisis are needed when considering federal and state resources devoted to addressing overdoses. In this study, we estimate the societal costs for opioid use disorder and fatal overdose from all opioids in 2017. METHODS: We estimated costs of fatal overdose from all opioids and opioid use disorder based on the incidence of overdose deaths and the prevalence of past-year opioid use disorder for 2017. Incidence of fatal opioid overdose was obtained from the National Vital Statistics System; prevalence of past-year opioid use disorder was estimated from the National Survey of Drug Use and Health. Costs were estimated for health care, criminal justice and lost productivity. Costs for the reduced quality of life for opioid use disorder and life lost due to fatal opioid overdose were valued using U.S. Department of Health and Human Services guidelines for valuing reductions in morbidity and mortality. RESULTS: Costs for opioid use disorder and fatal opioid overdose in 2017 were estimated to be $1.02 trillion. The majority of the economic burden is due to reduced quality of life from opioid use disorder and the value of life lost due to fatal opioid overdose. CONCLUSIONS: These estimates can assist decision makers in understanding the magnitude of opioid use disorder and fatal overdose. Knowing the magnitude and distribution of the economic burden can inform public policy, clinical practice, research, and prevention and response activities.

The cost of opioid use disorder and the value of aversion.

BACKGROUND: The objective of this study was twofold. First, to update and estimate the economic burden of opioid use disorder (OUD) to the U.S. from the perspectives of the healthcare sector, taxpayer, and society, overall and by age. Second, to estimate the mean present value of averting an OUD, overall and by age, for use in economic evaluations of prevention-focused interventions. METHODS: This was a retrospective secondary analysis using 2018 data from the National Survey on Drug Use and Health, and the CDC WONDER Database on all U.S. persons, at least 12 years old, with an OUD, or who died of opioid overdose. Total OUD-related costs were estimated according to age and stakeholder perspective. Mean costs weighted by insurance type and the probability of mortality were estimated for each age, then used to estimate the mean present value of OUD aversion according to age and stakeholder perspective. RESULTS: The total annual OUD-related costs to the U.S. in 2018 were $786.8 billion to society, $93 billion to taxpayers, and $89.1 billion to the healthcare sector. The mean present value of averting an OUD, across all ages, was $2.2 million, $325,125, and $244,030 from the societal, taxpayer, and healthcare sector perspectives, respectively. CONCLUSIONS AND RELEVANCE: The age-specific values of averting an OUD allow for more robust and targeted economic evaluations of competing interventions to reduce the burden of opioids on multiple stakeholders. The rise in the annual OUD-related cost largely reflects the increase in overdose deaths attributable to synthetic opioids (e.g., fentanyl).

Healthcare cost associations of patients who use illicit drugs in Florida: a retrospective analysis.

BACKGROUND: Illicit drug use increases visits to the hospital. Research is limited on the costs of these healthcare visits by illicit drug. METHODS: Florida's Agency for Health Care Administration's emergency department and inpatient datasets from 2016 to 2018 were analyzed. Adults who used an illicit drug were included in the study population resulting in 709,658 observations. Cost-to-charge ratios were used to estimate healthcare costs. Linear regression analyzed associations of illicit drugs with total healthcare cost. RESULTS: Total healthcare costs are estimated at $6.4 billion over the 3 year period. Medicare paid for the most patient care ($2.16 billion) with Medicaid and commercial insurance each estimated at $1.36 billion. Cocaine (9.25%) and multiple drug use (6.12%) increased the costs of an ED visit compared to a patient with cannabis SUD. Opioids (23.40%) and inhalants use (16.30%) increased the costs of inpatient compared to cannabis SUD. CONCLUSION: Healthcare costs are high of patients with illicit drug SUD and poisoning, over half of which are paid for with tax payer dollars and to an unknown degree hospital write-offs. Injuries and illness of patients using cocaine and multiple drugs are associated with more expensive ED patient care and opioids and inhalants are associated with more expensive inpatient care.

Socioeconomic marginalization and opioid-related overdose: A systematic review.

BACKGROUND: Socioeconomic marginalization (SEM) is an important but under-explored determinant of opioid overdose with important implications for health equity and associated public policy initiatives. This systematic review synthesizes evidence on the role of SEM in both fatal and non-fatal overdose among people who use opioids. METHODS: Studies published between January 1, 2000 and March 31, 2018 were identified through searching electronic databases, citations, and by contacting experts. The titles, abstracts, citation information, and descriptor terms of citations were screened by two team members. Data were synthesized using the lumping technique. RESULTS: A total of 37 studies met inclusion criteria and were included in the review, with 34 of 37 finding a significant association between at least one socioeconomic factor and overdose. The included studies contained variables related to eight socioeconomic factors: criminal justice system involvement, income, employment, social support, health insurance, housing/homelessness, education, and composite measures of socio-economic status. Most studies found associations in the hypothesized direction, whereby increased SEM was associated with a higher rate or increased likelihood of the overdose outcome measured. The review revealed an underdeveloped evidence base. CONCLUSIONS: Nearly all reviewed studies found a connection between a socioeconomic variable and overdose, but more research is needed with an explicit focus on SEM, using robust and nuanced measures that capture multiple dimensions of disadvantage, and collect data over time to better inform decision making around opioid overdose.

Cost-Effectiveness of Intranasal Naloxone Distribution to High-Risk Prescription Opioid Users.

OBJECTIVES: To determine the cost-effectiveness of pharmacy-based intranasal naloxone distribution to high-risk prescription opioid (RxO) users. METHODS: We developed a Markov model with an attached tree for pharmacy-based naloxone distribution to high-risk RxO users using 2 approaches: one-time and biannual follow-up distribution. The Markov structure had 6 health states: high-risk RxO use, low-risk RxO use, no RxO use, illicit opioid use, no illicit opioid use, and death. The tree modeled the probability of an overdose happening, the overdose being witnessed, naloxone being available, and the overdose resulting in death. High-risk RxO users were defined as individuals with prescription opioid doses greater than or equal to 90 morphine milligram equivalents (MME) per day. We used a monthly cycle length, lifetime horizon, and US healthcare perspective. Costs (2018) and quality-adjusted life-years (QALYs) were discounted 3% annually. Microsimulation was performed with 100 000 individual trials. Deterministic and probabilistic sensitivity analyses were conducted. RESULTS: One-time distribution of naloxone prevented 14 additional overdose deaths per 100 000 persons, with an incremental cost-effectiveness ratio (ICER) of $56 699 per QALY. Biannual follow-up distribution led to 107 additional lives being saved with an ICER of $84 799 per QALY compared with one-time distribution. Probabilistic sensitivity analyses showed that a biannual follow-up approach would be cost-effective 50% of the time at a willingness-to-pay (WTP) threshold of $100 000 per QALY. Naloxone effectiveness and proportion of overdoses witnessed were the 2 most influential parameters for biannual distribution. CONCLUSION: Both one-time and biannual follow-up naloxone distribution in community pharmacies would modestly reduce opioid overdose deaths and be cost-effective at a WTP of $100 000 per QALY.

Heroin overdose masquerades as methomyl poisoning: a case report.

BACKGROUND: Methomyl is the most common cause of suicidal death but heroin is the most common cause of accidental death. The problem is to determine the exact cause and manner of death between methomyl or heroin toxicity. The evidence from autopsy includes crime scene investigation, toxicological analysis by liquid chromatography with mass spectrometry, and knowledge of methomyl and heroin intoxication. CASE PRESENTATION: A 35-year-old Thai man and a 30-year-old Thai woman were found showing evidence of cyanosis, with a fine froth around the nose and mouth. Postmortem interval time was 24 hours. According to the police's and hotel owner's records, the couple stayed together for 1 day before being found dead in bed, naked, with a foul and a fine froth around the nose and mouth. A methomyl insecticide sachet and a plastic box containing white powder form of heroin were found at the scene. Laboratory tests of the male corpse identified the presence of methomyl in the blood of the stomach and morphine, codeine, methadone, and tramadol in the systemic blood. Blood cholinesterase enzyme activity and morphine concentration was 3416 U/L or 53% (normal 6400 U/L) and 0.058 µg/ml respectively. Laboratory test of the female corpse identified the presence of methomyl in the stomach and blood, and cholinesterase enzyme activity was 1965 U/L or 30.7%. CONCLUSIONS: Cause of death of the male corpse was deemed to be due to heroin intoxication as the blood concentration of morphine was more than the lethal concentration with a morphine/codeine ratio of more than 1:1. Methomyl intoxication of the male corpse was unlikely to be the cause of death because methomyl systemic blood concentration was found to be very low, < 2.5 µg/ml, and cholinesterase enzyme levels did not indicate lethal activity (< 10-15% of normal). The main problem regarding an insurance claim is that the policy will not pay out in the case of heroin-associated deaths, as it is an addictive drug. The policy would pay out on death by suicide with methomyl insecticide, which was not prohibited by the insurance company after 1 year of insurance. So, it is not clear whether or not the family will receive money from the insurance company.

Evidence that social-economic factors play an important role in drug overdose deaths.

BACKGROUND: Drug overdose deaths in the United States increased from approximately 16,000 per year in 2001 to 41,000 per year in 2014. Although every US state witnessed an increase, the increases were much larger in some states than others. There was also variation as a function of race and ethnicity. Non-Hispanic Whites accounted for more than 80% of the deaths, and in some states their rates were about ten times greater per capita than Hispanic and Non-White rates. State and temporal differences provide an opportunity to evaluate explanations of what is driving drug overdose deaths. In this report, we evaluate the degree to which state level variation in opioid prescription rates and social-economic conditions explain state level variation in overdose death rates. METHODS AND DATA: We used publicly available data from the Center for Disease Control (CDC), Bureau of Labor Statistics (BLS), Drug Enforcement Agency (DEA) and the Opportunity Insights project. RESULTS: Legally prescribed opioids, social capital and work force participation accounted for 53-69% of the between-state variation in overdose deaths in Non-Hispanic Whites. Prescriptions and the two social economic measures accounted for about the same amounts of unique variation, but shared variation among the three independent variables was the strongest predictor of overdose deaths. Panel regression results of the year-to-year changes in overdose deaths were similar. However, the pattern of correlations for Hispanics and Non-Whites was quite different. Neither opioid prescriptions nor social capital were significant predictors of overdose deaths in the between-state and between-year Hispanic and Non-White regression analyses. CONCLUSIONS: Common variation in opioid prescriptions rates, social capital, and work force participation proved the strongest predictor of drug overdose deaths in Non-Hispanic Whites. We discuss reasons why the same did not hold for the Hispanic/Non-White population.

Impact of a community-based naloxone distribution program on opioid overdose death rates.

BACKGROUND: In August 2013, a naloxone distribution program was implemented in North Carolina (NC). This study evaluated that program by quantifying the association between the program and county-level opioid overdose death (OOD) rates and conducting a cost-benefit analysis. METHODS: One-group pre-post design. Data included annual county-level counts of naloxone kits distributed from 2013 to 2016 and mortality data from 2000-2016. We used generalized estimating equations to estimate the association between cumulative rates of naloxone kits distributed and annual OOD rates. Costs included naloxone kit purchases and distribution costs; benefits were quantified as OODs avoided and monetized using a conservative value of a life. RESULTS: The rate of OOD in counties with 1-100 cumulative naloxone kits distributed per 100,000 population was 0.90 times (95% CI: 0.78, 1.04) that of counties that had not received kits. In counties that received >100 cumulative kits per 100,000 population, the OOD rate was 0.88 times (95% CI: 0.76, 1.02) that of counties that had not received kits. By December 2016, an estimated 352 NC deaths were avoided by naloxone distribution (95% CI: 189, 580). On average, for every dollar spent on the program, there was $2742 of benefit due to OODs avoided (95% CI: $1,237, $4882). CONCLUSIONS: Our estimates suggest that community-based naloxone distribution is associated with lower OOD rates. The program generated substantial societal benefits due to averted OODs. States and communities should continue to support efforts to increase naloxone access, which may include reducing legal, financial, and normative barriers.

Estimated impact of supervised injection facilities on overdose fatalities and healthcare costs in New York City.

BACKGROUND: The opioid epidemic in the United States has resulted in over 42,000 U.S. opioid overdose fatalities in 2016 alone. In New York City (NYC) opioid overdoses have reached a record high, increasing from 13.6 overdose deaths/100,000 to 19.9/100,000 from 2015 to 2016. Supervised injection facilities (SIFs) provide a hygienic, safe environment in which pre-obtained drugs can be consumed under clinical supervision to quickly reverse opioid overdoses. While SIFs have been implemented worldwide, none have been implemented to date in the United States. This study estimates the potential impact on opioid overdose fatalities and healthcare system costs of implementing SIFs in NYC. METHODS: A deterministic model was used to project the number of fatal opioid overdoses avoided by implementing SIFs in NYC. Model inputs were from 2015 to 2016 NYC provisional overdose data (N = 1852) and the literature. Healthcare utilization and costs were estimated for fatal overdoses that would have been avoided from implementing one or more SIFs. RESULTS: One optimally placed SIF is estimated to prevent 19-37 opioid overdose fatalities annually, representing a 6-12% decrease in opioid overdose mortality for that neighborhood; four optimally placed SIFs are estimated to prevent 68-131 opioid overdose fatalities. Opioid overdoses cost the NYC healthcare system an estimated $41 million per year for emergency medical services, emergency department visits, and hospitalizations. Implementing one SIF is estimated to save $0.8-$1.6 million, and four SIFs saves $2.9-$5.7 million in annual healthcare costs from opioid overdoses. CONCLUSIONS: Implementing SIFs in NYC would save lives and healthcare system costs, although their overall impact may be limited depending on the geographic characteristic of the local opioid epidemic. In cities with geographically dispersed opioid epidemics such as NYC, multiple SIFs will be required to have a sizeable impact on the total number of opioid overdose fatalities occurring each year.

Unclassified drug overdose deaths in the opioid crisis: emerging patterns of inequity.

OBJECTIVE: Examine whether individual, geographic, and economic phenotypes predict missing data on specific drug involvement in overdose deaths, manifesting inequities in overdose mortality data, which is a key data source used in measuring the opioid epidemic. MATERIALS AND METHODS: We combined national data sources (mortality, demographic, economic, and geographic) from 2014-2016 in a multi-method analysis of missing drug classification in the overdose mortality records (as defined by the use of ICD-10 T50.9 on death certificates). We examined individual disparities in decedent-level multivariate logistic regression models, geographic disparities in spatial analysis (heat maps), and economic disparities in a combination of temporal trend analyses (descriptive statistics) and both decedent- and county-level multivariate logistic regression models. RESULTS: Our analyses consistently found higher rates of unclassified overdoses in decedents of female gender, White race, non-Hispanic ethnicity, with college education, aged 30-59 and those from poorer counties. Despite the fact that unclassified drug overdose death rates have reduced over time, gaps persist between the richest and poorest counties. There are also striking geographic differences both across and within states. DISCUSSION: Given the essential role of mortality data in measuring the scale of the opioid epidemic, it is important to understand the individual and community inequities underlying the missing data on specific drug involvements. Knowledge of these inequities could enhance our understanding of the opioid crisis and inform data-driven interventions and policies with more equitable resource allocations. CONCLUSION: Multiple individual, geographic, and economic disparities underlie unclassified overdose deaths, with important implications for public health informatics and addressing the opioid crisis.

Socioeconomic and geographical disparities in prescription and illicit opioid-related overdose deaths in Orange County, California, from 2010-2014.

Background: Reports indicate a geographic effect of socioeconomic inequalities on the occurrence of opioid-related fatal overdoses. This study aims to (1) estimate the rates of opioid-related overdoses, (2) estimate the association of benzodiazepine co-ingestion with opioid-related deaths, (3) estimate associations between socioeconomic indicators and opioid-related deaths, and (4) map the distribution of fatal overdoses, in Orange County (OC), California. Methods: An ecologic study was conducted of all opioid- related deaths (1205 total) from 2010 to 2014 obtained from the OC Coroner Division database (1065 OC residents, 55 nonresidents, 85 OC homeless) (analyzed 2016-2017). Rates of opioid overdose, benzodiazepine co-ingestion prevalence, and associations with socioeconomic status (SES; education, poverty, median income) using ZIP code analysis in the residential and homeless communities were calculated. Results: Of 1205 deaths, 904 involved prescription-type opioids, 223 involved heroin, 39 involved both, and 39 not stated; 973 were classified unintentional overdoses, 180 suicides, and 52 undetermined; 49% of cases involved benzodiazepines. Prescription-type opioid and heroin death rates for residents were 5.4/ 100,000 person-years (95% confidence interval [CI]: 5.0-5.8) and 1.2/100,000 person-years (95% CI: 1.0-1.4), respectively. Males, age group 45-54, and Caucasian race had the highest rate (13.6/100,000) of opioid mortality. The highest death rates were seen in homeless adults, at 136/100,000 person-years for prescription-type opioids (95% CI: 99.0-185.5) and 156/100,000 person-years for heroin (95% CI: 116.8-209.5). Conclusions: The burden of prescription-type opioid-related deaths in OC affects all demographics and levels of SES; there is a disproportionately high rate of opioid-related deaths in the OC homeless population.

The Prevalence and Cost of Medicare Beneficiaries Diagnosed and At Risk for Opioid Abuse, Dependence, and Poisoning.

BACKGROUND: Reliance on prescription opioids to manage pain has been associated with increases in diversion, overdose, and addiction. Prevalence of misuse and abuse has been shown to be higher among government-insured populations than commercially insured populations. However, the prevalence and costs of misuse/abuse among the Medicare fee-for-service (FFS) population has not been studied. OBJECTIVES: To (a) determine the prevalence and costs of prescription opioid misuse/abuse and (b) evaluate the prevalence and costs associated with those identified as at risk for opioid misuse/abuse in Medicare FFS beneficiaries. METHODS: This retrospective case-control study used Medicare claims data for the calendar years of 2010 and 2011 and included Medicare beneficiaries aged at least 18 years. The index date was the date of first diagnosed misuse/abuse or at risk for abuse and had to occur between July 1, 2010, and June 30, 2011, and beneficiaries had to have at least 6 months continuous eligibility before and after the index date. Matching (1:1) was used for comparing opioid misusers/abusers with nonabuser controls, as well as comparing patients at risk for opioid abuse with controls not at risk for abuse. Controls were matched to cases by gender, age, disability, and geographic region. The index date of the control patient was set equal to the index date of the matched case. RESULTS: Prevalence of misuse/abuse in the Medicare FFS population was 13.1 per 1,000 persons, with the majority among patients receiving Medicare based on disability (76.2%). The prevalence of at risk for misuse/abuse was 117.4 per 1,000 persons. Approximately half of the Medicare FFS patients used an opioid. Overall total annual unadjusted mean costs of health care resources were significantly greater for abusers than for matched controls ($46,194 vs. $21,964; P < 0.0001), with a mean annual excess cost of $24,230. The overall total adjusted 6-month post-index mean costs of health care resources for abusers was significantly greater than that of matched controls ($33,942 vs. $10,754; P < 0.0001), with a mean excess cost of $23,188. CONCLUSIONS: The prevalence of diagnosed abuse among Medicare FFS population (13.1 per 1,000 persons) was higher than other payer groups studied using similar ICD-9-CM codes, and the majority of abuse was among those receiving Medicare based on disability (76.2%). The prevalence of at-risk abuse was 9 times higher than the prevalence of diagnosed abuse. As with other studies, health care resource utilization and costs were significantly greater for diagnosed abuse than matched controls. DISCLOSURES: This study was sponsored by Pfizer. Roland is a Pfizer employee and stockholder and was involved in all aspects of the study as part of a mid-career fellowship in pharmacoeconomics with the University of Utah. Ye and Stevens are employees of University of Utah, and Oderda was an employee of University of Utah, which received financial support from Pfizer in connection with the development of this manuscript. Oderda also reports consulting fees from Pfizer, Trevena, and Pacira, unrelated to this study. The results of this study were presented at the Academy of Managed Care Pharmacy Nexus 2015; October 26-29, 2015; Orlando, FL, and the AMCP Managed Care & Specialty Pharmacy Annual Meeting 2016; April 19-22, 2016; San Francisco, CA.

Urban-rural variation in the socioeconomic determinants of opioid overdose.

BACKGROUND: Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. METHODS: In this serial cross-sectional study of zip codes in 17 states, 2002-2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. RESULTS: Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06-1.07]; 5% low education: 1.02 [1.02-1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87-0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11-1.13]; 5% unemployment: 1.04 [1.02-1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87-0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02-1.16]). CONCLUSIONS: Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

Cost-effectiveness of naloxone kits in secondary schools.

BACKGROUND: We seek to identify conditions under which a plan by the Toronto District School Board (TDSB) to equip high schools with naloxone kits would be cost-effective. METHODS: We developed a decision-analytic model to evaluate the costs, benefits, and cost-effectiveness of a school-based naloxone program. We estimated model inputs from the medical literature and used Toronto-specific sources whenever available. We present our results varying both the expected total number of opioid overdoses per year across all 112 TDSB high schools and the effectiveness of a school-based naloxone program in reducing mortality. RESULTS: A school naloxone program likely costs less than CAD$50,000 per quality-adjusted life-year gained if the overdose frequency is at least once each year and it reduces opioid poisoning mortality by at least 40% (from 10% to <6.0%) or if the overdose frequency is at least two per year and the program reduces mortality by at least 20% (from 10% to <8.0%). The results are sensitive to the intensity and cost of staff training, the lifetime costs and life-expectancy of overdose survivors, and the probability of an overdose being fatal in the absence of a school naloxone program. CONCLUSIONS: School naloxone programs are relatively inexpensive, but that does not ensure that they are a cost-effective use of resources. While potentially cost-effective, if the risk of an overdose in a Toronto high school is low, then other programs aimed at improving the health and wellbeing of students may be better use of limited resources.

Sociodemographic factors, prescription history and opioid overdose deaths: a statewide analysis using linked PDMP and mortality data.

BACKGROUND: Opioid overdose deaths have continued to rise in Tennessee (TN) with fentanyl emerging as a major contributor. Current data are needed to identify at-risk populations to guide prevention strategies. We conducted a large statewide observational study among TN adult decedents (2013-2016) to evaluate the association of sociodemographic factors and prescribing patterns with opioid overdose deaths. METHODS: Among drug overdose decedents identified using death certificate data (n = 5483), we used logistic regression to estimate adjusted odds ratios and 95% confidence intervals for characteristics associated with prescription opioid (PO) (excluding fentanyl), fentanyl, and heroin alone overdoses. Among decedents linked to TN's Prescription Drug Monitoring Database using deterministic algorithms, we obtained prescription history in the year before death (n = 3971), which was evaluated by type of overdose using descriptive statistics. RESULTS: Younger, non-White decedents had lower odds of PO overdose, while females and benzodiazepines as a contributing cause were associated with increased odds of PO overdose. Younger age, Non-Hispanic Black race/ethnicity, greater than high school education, and cocaine/other stimulants as a contributing cause were associated with increased odds of fentanyl or heroin overdoses. Over 55% of PO, 39.2% of fentanyl, and 20.7% of heroin overdoses had an active opioid prescription at death. For PO, fentanyl, and heroin decedents, respectively, 46.0%, 30.5%, and 26.2% had an active prescription for benzodiazepines at death. CONCLUSIONS: Prescription opioid overdose deaths were associated with different sociodemographic profiles and prescribing history compared to fentanyl and heroin overdose deaths in TN. Data can guide prevention strategies to reduce opioid overdose mortality.

Mapping Drug Overdose Demographic and Socioeconomic Characteristics in the Community.

INTRODUCTION: Drug use and drug overdose have increased at an alarming rate. OBJECTIVE: To identify demographic and neighborhood social and economic factors associated with higher risk of overdose. These findings can be used to inform development of community programs and appropriately devote resources to prevent and treat drug abuse. METHODS: The electronic health records of all patients seen in the emergency department or admitted to the hospital for a drug overdose in 2016 at Gundersen Health System in La Crosse, Wisconsin, were reviewed retrospectively. Patient data collected included age, sex, race/ethnicity, insurance type, overdose intention (intentional, unintentional), drug involved, and total charge for the episode of care. Patient residence was geocode mapped to census tract to analyze the relationship of drug overdose to neighborhood characteristics. Overdose rates were calculated by census tract and compared by several sociodemographic characteristics. RESULTS: Four hundred nineteen patients were included in this study. Forty percent of overdoses were unintentional. Patients who were older, male, nonwhite, and who had no insurance were more likely to have unintentional overdoses. Opiates and heroin were most commonly present in unintentional overdoses, whereas benzodiazepines and sedatives were more common in intentional overdoses. Patients living in census tracts with a higher percentage of residents with some college also had a higher rate of unintentional overdose. Rates of overdose at the census tract level varied and were higher in tracts with lower median income, low income inequality ratio, high percentage of college attendance, and higher percentage of nonwhite residents. The average charge per overdose was $14,771 (median = $9,497) and totaled $6,188,923 for the year. CONCLUSIONS: This study provides demographic, geographic, and socioeconomic detail about drug overdose in the community that can be used to focus future treatment and prevention interventions.