Faculty Bibliography

Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7-7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6-7 million US adolescents and adults.

BACKGROUND:Substance-related interactions with the criminal justice system are a potential touchpoint to identify people at risk for firearm violence. We used an agent-based model to simulate the change in firearm violence after disqualifying people from owning a firearm given prior alcohol- and drug-related misdemeanors. METHODS:We created a population of 800,000 agents reflecting a 15% sample of the adult New York City population. RESULTS:Disqualification from purchasing firearms for 5 years after an alcohol-related misdemeanor conviction reduced population-level rates of firearm homicide by 1.0% [95% CI 0.4-1.6%] and suicide by 3.0% [95% CI 1.9-4.0%]. Disqualification based on a drug-related misdemeanor conviction reduced homicide by 1.6% [95% CI 1.1-2.2%] and suicide by 4.6% [95% CI 3.4-5.8%]. Reductions were generally 2 to 8 times larger for agents meeting the disqualification criteria. CONCLUSIONS:Denying firearm access based on a history of drug and alcohol misdemeanors may reduce firearm violence among the high-risk group. Enactment of substance use-related firearms denial criteria needs to be balanced against concerns about introducing new sources of disenfranchisement among already vulnerable populations.

BACKGROUND:Firearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the impact of high-risk (disqualification) and population-based (price increase) approaches on firearm homicide in New York City (NYC). METHODS:We simulated 800,000 agents reflecting a 15% sample of the adult population of NYC. Three groups were considered and disqualified from all firearm ownership for five years, grouped based on prevalence: low prevalence (psychiatric hospitalization, alcohol-related misdemeanor and felony convictions, 0.23%); moderate prevalence (drug misdemeanor convictions, domestic violence restraining orders, 1.03%); and high prevalence (all other felony/misdemeanor convictions, 2.30%). Population-level firearm ownership was impacted by increasing the price of firearms, assuming 1% price elasticity. RESULTS:In this hypothetical scenario, to reduce firearm homicide by 5% in NYC, 25% of the moderate prevalence group, or 12% of the high prevalence group needed to be effectively disqualified; even when all of the low prevalence group was disqualified, homicide did not decrease by 5%. An 18% increase in price similarly reduced firearm homicide by 5.37% (95% CI 4.43-6.31%). Firearm homicide declined monotonically as the proportion of disqualified individuals increased and/or price increased. A combined intervention that both increased price and effectively disqualified "high-risk" groups achieved approximately double the reduction in homicide as any one intervention alone. Increasing illegal firearm ownership by 20%, a hypothetical response to price increases, did not meaningfully change results. CONCLUSION:A key takeaway of our study is that adopting high-risk versus population-based approaches should not be an "either-or" question. When individual risk is variable and diffuse in the population, "high-risk approaches" to firearm violence need to focus on relatively prevalent groups and be highly efficacious in disarming people at elevated risk to achieve meaningful reductions in firearm homicide, though countering issues of social justice and stigma should be carefully considered. Similar reductions can be achieved with population-based approaches, such as price increases, albeit with fewer such countering issues.

IMPORTANCE:Benzodiazepines are prescribed for the treatment of adolescent sleep disorders; however, benzodiazepine overdoses occur, often in combination with opioids. OBJECTIVE:To evaluate whether benzodiazepine treatment for sleep disorders, compared with alternative pharmacologic treatments (trazodone, hydroxyzine, zolpidem, zaleplon, and eszopiclone), is associated with increased risk of drug overdose for young people. DESIGN, SETTING, AND PARTICIPANTS:This cohort study included privately insured people 10 to 29 years of age identified from a US commercial claims database (MarketScan), from January 1, 2009, to December 31, 2018. Young people with a sleep disorder diagnosis initiating benzodiazepine (n = 23 084) or comparator pharmacologic treatments (n = 66 706) were included in the study. Statistical analysis was performed from November 1, 2021, to May 16, 2022. EXPOSURES:New use of benzodiazepine treatment or comparator pharmacologic treatments (defined as ≥1 year without a prescription for benzodiazepine or comparator medications). MAIN OUTCOMES AND MEASURES:Incident diagnosed drug overdoses were identified from inpatient and emergency department records within 6 months of treatment initiation. The propensity score-adjusted cumulative incidence of overdose and hazard ratios (HRs) were estimated with intention-to-treat (analyzed based on initial treatment) and as-treated analyses (added censoring at treatment discontinuation). Results were stratified by prior prescription opioid fill. RESULTS:The cohort included 23 084 young people initiating benzodiazepine treatment (14 444 female participants [62.6%]; mean [SD] age, 23 [4.1] years) and 66 706 initiating a comparator treatment (38 446 female participants [57.6%]; mean [SD] age, 22 [4.4] years). Six months after treatment initiation, 9.7% (95% CI, 9.3%-10.1%) of benzodiazepine users and 12.3% (95% CI, 12.1%-12.6%) of the comparator group were still receiving treatment. The crude incidence of drug overdose at 6 months was 0.9% for benzodiazepine initiators and 0.8% for comparator treatment initiators. In adjusted analyses, an increased risk of drug overdose was associated with benzodiazepines vs comparator treatments (intention-to-treat analysis: HR, 1.25 [95% CI, 1.03-1.51]; as-treated analysis: HR, 1.44 [95% CI, 1.14-1.80]). This association was stronger among young people with a recent prescription opioid fill vs those without a recent prescription opioid fill (as-treated analysis: adjusted HR, 2.01 [95% CI, 1.24-3.25] vs adjusted HR, 1.31 [95% CI, 1.00-1.70]). CONCLUSIONS AND RELEVANCE:The findings of this study suggest that benzodiazepines, compared with alternative pharmacologic treatments for common sleep disorders, were associated with an increased risk of drug overdose among young people during the following 6-month period, especially among those with a recent opioid prescription. Drug overdose is an important safety consideration when treating young people with benzodiazepines.

Former industrial cities facing economic challenges and depopulation often experience high levels of firearm and other forms of violence. Within these cities, violent crime often clusters in neighborhoods affected by high levels of vacant and abandoned housing. This study estimates the effects of building demolition in Detroit, Michigan on the subsequent risk of violent crime using property-level data and longitudinal targeted maximum likelihood estimation. The primary outcome is violent Crime Index crimes (homicide, rape, robbery and aggravated assault). We estimate effects for this category of crimes as a whole and for the subset involving firearms. Drug and other lower-level crimes are included as secondary outcomes. We compare the risk of experiencing each crime type following building demolition in Census blocks and block groups to an estimate of the risk had there been no demolition in the 1-3 quarters prior in 2017. There were >2600 total demolitions in about 1700 blocks in 2017 in Detroit. Nearly all demolished buildings were sourced from tax foreclosures. Estimates suggest the risk for all crime types tested would have been statistically indistinguishable from the observed crime risk had demolitions in the prior 1-3 quarters of 2017 not occurred. Our results run counter to most previous research on this topic, which tends to show a protective effect of demolition on violent crime. Understanding why our results differ may provide important insights into the types of demolition programs with the greatest potential to reduce violent crime.

OBJECTIVE/UNASSIGNED:In the United States, adult cannabis use has increased over time, but less information is available on time trends in cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine change over time in cannabis use disorder diagnoses among veterans, an important population subgroup, and whether such trends differ by age group (<35 years, 35-64 years, ≥65 years), sex, or race/ethnicity. METHODS/UNASSIGNED:VHA electronic health records from 2005 to 2019 (range of Ns per year, 4,403,027-5,797,240) were used to identify the percentage of VHA patients seen each year with a cannabis use disorder diagnosis (ICD-9-CM, January 1, 2005-September 30, 2015; ICD-10-CM, October 1, 2015-December 31, 2019). Trends in cannabis use disorder diagnoses were examined by age and by race/ethnicity and sex within age groups. Given the transition in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM). RESULTS/UNASSIGNED:In 2005, the percentages of VHA patients diagnosed with cannabis use disorder in the <35, 35-64, and ≥65 year age groups were 1.70%, 1.59%, and 0.03%, respectively; by 2019, the percentages had increased to 4.84%, 2.86%, and 0.74%, respectively. Although the prevalence of cannabis use disorder was consistently higher among males than females, between 2016 and 2019, the prevalence increased more among females than males in the <35 year group. Black patients had a consistently higher prevalence of cannabis use disorder than other racial/ethnic groups, and increases were greater among Black than White patients in the <35 year group in both periods. CONCLUSIONS/UNASSIGNED:Since 2005, diagnoses of cannabis use disorder have increased substantially among VHA patients, as they have in the general population and other patient populations. Possible explanations warranting investigation include decreasing perception of risk, changing laws, increasing cannabis potency, stressors related to growing socioeconomic inequality, and use of cannabis to self-treat pain. Clinicians and the public should be educated about the increases in cannabis use disorder in general in the United States, including among patients treated at the VHA.

OBJECTIVES:To compare the characteristics of individual overdose decedents in Rhode Island, 2016-2020 to the neighborhoods where fatal overdoses occurred over the same time period. METHODS:We conducted a retrospective analysis of fatal overdoses occurring between January 1, 2016 and June 30, 2020. Using individual- and neighborhood-level data, we conducted descriptive analyses to explore the characteristics of individuals and neighborhoods most affected by overdose. RESULTS:Most overdose decedents during the study period were non-Hispanic White. Across increasingly more White and non-Hispanic neighborhoods, rates of fatal overdose per 100,000 person-years decreased. An opposite pattern was observed across quintiles of average neighborhood poverty. CONCLUSIONS:Rates of fatal overdose were higher in less White, more Hispanic, and poorer neighborhoods, suggesting modest divergence between the characteristics of individuals and the neighborhoods most severely affected. These impacts may not be uniform across space and may accrue differentially to more disadvantaged and racially/ethnically diverse neighborhoods.

Violations of the positivity assumption (also called the common support condition) challenge health policy research and can result in significant bias, large variance, and invalid inference. We define positivity in the single- and multiple-timepoint (i.e., longitudinal) health policy evaluation setting, and discuss real-world threats to positivity. We show empirical evidence of the practical positivity violations that can result when attempting to estimate the effects of health policies (in this case, Naloxone Access Laws). In such scenarios, an alternative is to estimate the effect of a shift in law enactment (e.g., the effect if enactment had been delayed by some number of years). Such an effect corresponds to what is called a modified treatment policy, and dramatically weakens the required positivity assumption, thereby offering a means to estimate policy effects even in scenarios with serious positivity problems. We apply the approach to define and estimate the longitudinal effects of Naloxone Access Laws on opioid overdose rates.