Estimation of opioid misuse prevalence in New York State counties, 2007-2018. A Bayesian spatio-temporal abundance model approach

An important challenge to addressing the opioid overdose crisis is the lack of information on the size of the population of people who misuse opioids (PWMO) in local areas. This estimate is needed for better resource allocation, estimation of treatment and overdose outcome rates using appropriate denominators (i.e., the population at risk), and proper evaluation of intervention effects. In this study, we used a Bayesian hierarchical spatio-temporal integrated abundance model that integrates multiple types of county-level surveillance outcome data, state-level information on opioid misuse, and covariates to estimate the latent (hidden) counts and prevalence of PWMO across New York State counties (2007-2018). The model assumes that each opioid-related outcome reflects a partial count of the number of PWMO, and leverages these multiple sources of data to circumvent limitations of parameter estimation associated with other types of abundance models. Model estimates showed a reduction in the prevalence of PWMO during the study period, with important spatial and temporal variability. The model also provided county-level estimates of rates of treatment and opioid overdoses using the PWMO as denominators. This modeling approach can identify the size of hidden populations to guide public health efforts to confront the opioid overdose crisis across local areas.

State-Level History of Overdose Deaths Involving Stimulants in the United States, 1999‒2020

Objectives. To examine the state-level history of US overdose deaths involving stimulants with and without opioids from 1999 to 2020. Methods. We used death certificate data from the National Center for Health Statistics to categorize deaths into 4 groups of interest: cocaine with and without opioids, and psychostimulants with and without opioids. We used a Bayesian multiple change point model to describe the timing and magnitude of changes in overdose death rates involving stimulants for each state and year. Results. There was little change in the death rates of cocaine without opioids. Death rates involving cocaine and opioids sharply increased around 2015, particularly in the Northeast and Mid-Atlantic. We also observed steady increases in deaths involving psychostimulants without opioids just before 2010, particularly in states in the West and South. Deaths involving psychostimulants with opioids increased around 2015 with largest increases concentrated in Appalachian states. Conclusions. There is significant geographic heterogeneity in the co-involvement of stimulants in the US overdose crisis. Results can inform public health efforts to inform state-level overdose efforts such as naloxone distribution. (Am J Public Health. 2023;113(9):991-999. https://doi.org/10.2105/AJPH.2023.307337).

Changes in Opioid and Benzodiazepine Poisoning Deaths After Cannabis Legalization in the US: A County-level Analysis, 2002-2020

BACKGROUND

Cannabis legalization for medical and recreational purposes has been suggested as an effective strategy to reduce opioid and benzodiazepine use and deaths. We examined the county-level association between medical and recreational cannabis laws and poisoning deaths involving opioids and benzodiazepines in the US from 2002 to 2020.

METHODS

Our ecologic county-level, spatiotemporal study comprised 49 states. Exposures were state-level implementation of medical and recreational cannabis laws and state-level initiation of cannabis dispensary sales. Our main outcomes were poisoning deaths involving any opioid, any benzodiazepine, and opioids with benzodiazepines. Secondary analyses included overdoses involving natural and semi-synthetic opioids, synthetic opioids, and heroin.

RESULTS

Implementation of medical cannabis laws was associated with increased deaths involving opioids (rate ratio [RR] = 1.14; 95% credible interval [CrI] = 1.11, 1.18), benzodiazepines (RR = 1.19; 95% CrI = 1.12, 1.26), and opioids+benzodiazepines (RR = 1.22; 95% CrI = 1.15, 1.30). Medical cannabis legalizations allowing dispensaries was associated with fewer deaths involving opioids (RR = 0.88; 95% CrI = 0.85, 0.91) but not benzodiazepine deaths; results for recreational cannabis implementation and opioid deaths were similar (RR = 0.81; 95% CrI = 0.75, 0.88). Recreational cannabis laws allowing dispensary sales was associated with consistent reductions in opioid- (RR = 0.83; 95% CrI = 0.76, 0.91), benzodiazepine- (RR = 0.79; 95% CrI = 0.68, 0.92), and opioid+benzodiazepine-related poisonings (RR = 0.83; 95% CrI = 0.70, 0.98).

CONCLUSIONS

Implementation of medical cannabis laws was associated with higher rates of opioid- and benzodiazepine-related deaths, whereas laws permitting broader cannabis access, including implementation of recreational cannabis laws and medical and recreational dispensaries, were associated with lower rates. The estimated effects of the expanded availability of cannabis seem dependent on the type of law implemented and its provisions.

Does recreational cannabis legalization change cannabis use patterns? Evidence from secondary school students in Uruguay

BACKGROUND AND AIMS

In 2013, Uruguay became the first country to legalize and regulate the production and distribution of cannabis for recreational use. We measured whether Uruguay's non-commercial model of recreational cannabis legalization was associated with changes in the prevalence of risky and frequent cannabis use among secondary school students.

DESIGN

We used data from repeated cross-sectional surveys of secondary students in Uruguay and Chile (2007-2018). Using a difference-in-difference approach, we evaluated changes in the prevalence of past-year, past-month, any risky and frequent cannabis use following enactment (2014) and implementation (2016) of cannabis legalization among the full sample of secondary students and among students who reported past-year/month use. We examined changes separately for students ages 12 to 17, and students for whom cannabis became legally accessible, ages 18 to 21.

SETTING

Uruguay and Chile (2007-2018).

PARTICIPANTS

Secondary school students in 8th, 10th and 12th grade (n = 204 730).

MEASUREMENTS

Past-year and past-month cannabis use; any risky cannabis use measured with the Cannabis Abuse Screening Test (CAST); and frequent cannabis use (10+ days in the past-month).

FINDINGS

We found a decrease in past-year and past-month use following enactment or implementation. Among students ages 18 to 21, post-enactment, we observed a transitory increase in 2014 that decreased thereafter for: any risky use among those who reported past-year use (prevalence difference [PD] = 13.5%; 95% CI: 2.0, 24.9), frequent use in the full sample (PD = 4.5%; 95% CI: 1.0, 8.1), and frequent use among those who reported past-month use (PD = 16.8%; 95% CI: 1.9, 31.8).

CONCLUSION

The legalization of recreational cannabis in Uruguay was not associated with overall increases in either past-year/past-month cannabis use or with multi-year changes in any risky and frequent cannabis use among young people.

Trends in cannabis or cocaine-related dependence and alcohol/drug treatment in Argentina, Chile, and Uruguay

BACKGROUND

In the context of changing cannabis and other drug policy and regulation, concerns may arise regarding drug treatment access and use. We assessed cannabis/cocaine-related dependence and treatment in Argentina, Chile, and Uruguay.

METHODS

Nationally representative cross-sectional household surveys of people ages 15-64 in Argentina (4 surveys, 2006-2017), Chile (7 surveys, 2006-2018), and Uruguay (4 surveys, 2006-2018) were harmonized. We estimated weighted prevalences of cannabis or cocaine-related (cocaine or cocaine paste) dependence, based on meeting 3+ past-year ICD-10 dependence criteria. We estimated weighted prevalences of past-year alcohol/drug treatment use (Argentina, Chile) or use/seeking (Uruguay) among people with past-year cannabis/cocaine-related dependence. We tested model-based prevalence trends over time and described individual-level treatment correlates by country.

RESULTS

Cannabis/cocaine dependence prevalence increased in the region starting in 2010-2011, driven by cannabis dependence. Adjusted cannabis dependence prevalence increased from 0.7% in 2010 to 1.5% in 2017 in Argentina (aPD=0.8, 95% CI= 0.3, 1.2), from 0.8% in 2010 to 2.8% in 2018 in Chile (aPD=2.0, 95% CI= 1.4, 2.6), and from 1.4% in 2011 to 2.4% in 2018 in Uruguay (aPD=0.9, 95% CI= 0.2, 1.6). Cocaine-related dependence increased in Uruguay, decreased in Argentina, and remained stable in Chile. Among people with past-year cannabis/cocaine dependence, average alcohol/drug treatment use prevalence was 15.3% in Argentina and 6.0% in Chile, while treatment use/seeking was 14.7% in Uruguay. Alcohol/drug treatment prevalence was lower among people with cannabis dependence than cocaine-related dependence. Treatment correlates included older ages in all countries and male sex in Argentina only.

CONCLUSION

Alcohol/drug treatment use among people with cannabis/cocaine-related dependence remained low, signaling an ongoing treatment gap in the context of growing cannabis dependence prevalence in the region. Additional resources may be needed to increase treatment access and uptake. Future studies should assess contributors of low treatment use, including perceived need, stigma, and service availability.

Use of an Inverted Synthetic Control Method to Estimate Effects of Recent Drug Overdose Good Samaritan Laws, Overall and by Black/White Race/Ethnicity

Overdose Good Samaritan laws (GSLs) aim to reduce mortality by providing limited legal protections when a bystander to a possible drug overdose summons help. Most research into the impact of these laws is dated or potentially confounded by coenacted naloxone access laws. Lack of awareness and trust in GSL protections, as well as fear of police involvement and legal repercussions, remain key deterrents to help-seeking. These barriers may be unequally distributed by race/ethnicity due to racist policing and drug policies, potentially producing racial/ethnic disparities in the effectiveness of GSLs for reducing overdose mortality. We used 2015-2019 vital statistics data to estimate the effect of recent GSLs on overdose mortality, overall (8 states) and by Black/White race/ethnicity (4 states). Given GSLs' near ubiquity, few unexposed states were available for comparison. Therefore, we generated an "inverted" synthetic control method (SCM) to compare overdose mortality in new-GSL states with that in states that had GSLs throughout the analytical period. The estimated relationships between GSLs and overdose mortality, both overall and stratified by Black/White race/ethnicity, were consistent with chance. An absence of effect could result from insufficient protection provided by the laws, insufficient awareness of them, and/or reticence to summon help not addressable by legal protections. The inverted SCM may be useful for evaluating other widespread policies.

Cannabis legalization and traffic injuries: exploring the role of supply mechanisms

BACKGROUND AND AIM

In Uruguay, residents age 18 and older seeking legal cannabis must register with the government and choose one of three supply mechanisms: self-cultivation, non-profit cannabis clubs or pharmacies. This is the first paper to measure the association between type of legal cannabis supply mechanism and traffic crashes involving injuries.

DESIGN

Ecological study using ordinary least squares regression to examine how department-level variation in registrations (overall and by type) is associated with traffic crashes involving injuries.

SETTING

Uruguay.

CASES

532 department-quarters.

MEASUREMENTS

Quarterly cannabis registration counts at the department level and incident-level traffic crash data were obtained from government agencies. The analyses controlled for department-level economic and demographic characteristics and, as a robustness check, we included traffic violations involving alcohol for departments reporting this information. Department-level data on crashes, registrations and alcohol violations were denominated by the number of residents ages 18 and older.

FINDINGS

From 2013 to 2019, the average number of registrations at the department-quarter level per 10 000 residents age 18 and older for self-cultivation, club membership and pharmacy purchasing were 17.7 (SD = 16.8), 3.6 (SD = 8.6), and 25.1 (SD = 50.4), respectively. In our multivariate regression analyses, we did not find a statistically significant association between the total number of registrations and traffic crashes with injuries (β = -0.007; P = 0.398; 95% CI = -0.023, 0.01). Analyses focused on the specific supply mechanisms found a consistent, positive and statistically significant association between the number of individuals registered as self-cultivators and the number of traffic crashes with injuries (β = 0.194; P = 0.008; 95% CI = 0.058, 0.329). Associations for other supply mechanisms were inconsistent across the various model specifications.

CONCLUSIONS

In Uruguay, the number of people allowed to self-cultivate cannabis is positively associated with traffic crashes involving injuries. Individual-level analyses are needed to assess better the factors underlying this association.

Racial/Ethnic and Geographic Trends in Combined Stimulant/Opioid Overdoses, 2007-2019

In the United States, combined stimulant/opioid overdose mortality has risen dramatically over the last decade. These increases may particularly affect non-Hispanic Black and Hispanic populations. We used death certificate data from the US National Center for Health Statistics (2007-2019) to compare state-level trends in overdose mortality due to opioids in combination with 1) cocaine and 2) methamphetamine and other stimulants (MOS) across racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian American/Pacific Islander). To avoid unstable estimates from small samples, we employed principles of small area estimation and a Bayesian hierarchical model, enabling information-sharing across groups. Black Americans experienced severe and worsening mortality due to opioids in combination with both cocaine and MOS, particularly in eastern states. Cocaine/opioid mortality increased 575% among Black people versus 184% in White people (Black, 0.60 to 4.05 per 100,000; White, 0.49 to 1.39 per 100,000). MOS/opioid mortality rose 16,200% in Black people versus 3,200% in White people (Black, 0.01 to 1.63 per 100,000; White, 0.09 to 2.97 per 100,000). Cocaine/opioid overdose mortality rose sharply among Hispanic and Asian Americans. State-group heterogeneity highlighted the importance of data disaggregation and methods to address small sample sizes. Research to understand the drivers of these trends and expanded efforts to address them are needed, particularly in minoritized groups.

Trends in the sequence of initiation of alcohol, tobacco, and marijuana use among adolescents in Argentina and Chile from 2001 to 2017

BACKGROUND

Variation in drug policies, norms, and substance use over time and across countries may affect the normative sequences of adolescent substance use initiation. We estimated relative and absolute time-varying associations between prior alcohol and tobacco use and adolescent marijuana initiation in Argentina and Chile. Relative measures quantify the magnitude of the associations, whereas absolute measures quantify excess risk.

METHODS

We analyzed repeated, cross-sectional survey data from the National Surveys on Drug Use Among Secondary School Students in Argentina (2001-2014) and Chile (2001-2017). Participants included 8th, 10th, and 12th grade students (N = 680,156). Linear regression models described trends over time in the average age of first use of alcohol, tobacco, and marijuana. Logistic regression models were used to estimate time-varying risk ratios and risk differences of the associations between prior alcohol and tobacco use and current-year marijuana initiation.

RESULTS

Average age of marijuana initiation increased and then decreased in Argentina and declined in Chile. In both countries, the relative associations between prior tobacco use and marijuana initiation weakened amid declining rates of tobacco use; e.g., in Argentina, the risk ratio was 19.9 (95% CI: 9.0-30.8) in 2001 and 11.6 (95% CI: 9.0-13.2) in 2014. The relative association between prior alcohol use and marijuana initiation weakened Chile, but not in Argentina. On the contrary, risk differences (RD) increased substantially across both relationships and countries, e.g., in Argentina, the RD for tobacco was 3% (95% CI: 0.02-0.03) in 2001 and 12% (95% CI: 0.11-0.13) in 2014.

CONCLUSION

Diverging trends in risk ratios and risk differences highlight the utility of examining multiple measures of association. Variation in the strength of the associations over time and place suggests the influence of environmental factors. Increasing risk differences indicate alcohol and tobacco use may be important targets for interventions to reduce adolescent marijuana use.

Assessment of the impact of implementation of a zero blood alcohol concentration law in Uruguay on moderate/severe injury and fatal crashes: a quasi-experimental study

BACKGROUND AND AIMS

Debates regarding lowering the blood alcohol concentration (BAC) limit for drivers are intensifying in the United States and other countries, and the World Health Organization recommends that the limit for adults should be 0.05%. In January 2016, Uruguay implemented a law setting a zero BAC limit for all drivers. This study aimed to assess the effect of this policy on the frequency of moderate/severe injury and fatal traffic crashes.

DESIGN

A quasi-experimental study in which a synthetic control model was used with controls consisting of local areas in Chile as the counterfactual for outcomes in Uruguay, matched across population counts and pre-intervention period outcomes. Sensitivity analyses were also conducted.

SETTING

Uruguay and Chile.

CASES

Panel data with crash counts by outcome per locality-month (2013-2017).

INTERVENTION AND COMPARATOR

A zero blood alcohol concentration law implemented on 9 January 2016 in Uruguay, alongside a continued 0.03 g/dl BAC threshold in Chile.

MEASUREMENTS

Per-capita moderate/severe injury (i.e. moderate or severe), severe injury and fatal crashes (2013-2017).

FINDINGS

Our base synthetic control model results suggested a reduction in fatal crashes at 12 months [20.9%; P-value = 0.018, 95% confidence interval (CI) = -0.340, -0.061]. Moderate/severe injury crashes did not decrease significantly (10.2%, P = 0.312, 95% CI = -0.282, 0.075). The estimated effect at 24 months was smaller and with larger confidence intervals for fatal crashes (14%; P = 0.048, 95% CI = -0.246, -0.026) and largely unchanged for moderate/severe injury crashes (-9.4%, P = 0.302, 95% CI = -0.248, 0.058). Difference-in-differences analyses yielded similar results. As a sensitivity test, a synthetic control model relying on an inferior treatment-control match pre-intervention (measured by mean squared error) yielded similar-sized differences that were not statistically significant.

CONCLUSIONS

Implementation of a law setting a zero blood alcohol concentration threshold for all drivers in Uruguay appears to have resulted in a reduction in fatal crashes during the following 12 and 24 months.

Trends in marijuana use in two Latin American countries: an age, period and cohort study

BACKGROUND AND AIMS

Uruguay and Chile have the highest levels of marijuana use in Latin America, and have experienced consistent increases during the last two decades. We aim to calculate separate age-period-cohort (APC) effects for past-year marijuana use in Uruguay and Chile, which have similar epidemiologica, and demographic profiles but diverging paths in cannabis regulation.

DESIGN

APC study in which period and cohort effects were estimated as first derivative deviations from their linear age trend, separately by country and gender.

SETTING

Uruguay and Chile.

PARTICIPANTS

General population between 15 and 64 years.

MEASUREMENTS

Past-year marijuana use from household surveys with five repeated cross-sections between 2001 and 2018 in Uruguay (median n = 4616) and 13 between 1994 and 2018 in Chile (median n = 15 895).

FINDINGS

Marijuana use prevalence in both countries peaked at 20-24 years of age and increased consistently across calendar years. Period effects were strong and positive, indicating that increases in use were evident across age groups. Relative to 2006 (reference year), Chilean period effects were approximately 48% lower in 1994 and approximately four times higher in 2018; in Uruguay, these effects were approximately 56% lower in 2001 and almost quadrupled in 2018. We observed non-linear cohort effects in Chile and similar patterns in Uruguay for the overall sample and women. In both countries, marijuana use increased for cohorts born between the mid-1970s and early 1990s, even in the context of rising period effects. Prevalence was consistently larger for men, but period increases were stronger in women.

CONCLUSIONS

Age-period-cohort effects on past-year marijuana use appear to have been similar in Chile and Uruguay, decreasing with age and increasing over time at heterogeneous growth rates depending on gender and cohort. Current levels of marijuana use, including age and gender disparities, seem to be associated with recent common historical events in these two countries.

The impact of cannabis legalization in Uruguay on adolescent cannabis use

BACKGROUND

In 2013, Uruguay became the first country in the world to legalize recreational cannabis, instituting a non-commercial state regulatory model of production and supply. This study provides the first empirical evidence on its impacts on adolescent use of cannabis and related risks.

METHODS

We use a generalization of the synthetic control method (SCM) to estimate the impact of legalization in Uruguay on adolescent past year and month cannabis use, perceived availability of cannabis and perceived risk of cannabis use. We compare biennial high school student self-reported survey data from Montevideo and regions in the interior of Uruguay post-legalization (2014-2018) and post initial implementation (2015-2018) to a synthetic counterfactual constructed using a weighted combination of 15 control regions in Chile.

RESULTS

We find no evidence of an impact on cannabis use or the perceived risk of use. We find an increase in student perception of cannabis availability (58% observed vs. 51% synthetic control) following legalization.

CONCLUSION

Our findings provide some support for the thesis that Uruguay's state regulatory approach to cannabis supply may minimize the impact of legalization on adolescent cannabis use. At the same time, our study period represents a period of transition: pharmacy access, by far the most popular means of access, was not available until the summer of 2017. Additional study will be important to assess the longer-term impacts of the fully implemented legalization regime on substance use outcomes.

Association of Medicaid Expansion With Opioid Overdose Mortality in the United States

IMPORTANCE

The Patient Protection and Affordable Care Act (ACA) permits states to expand Medicaid coverage for most low-income adults to 138% of the federal poverty level and requires the provision of mental health and substance use disorder services on parity with other medical and surgical services. Uptake of substance use disorder services with medications for opioid use disorder has increased more in Medicaid expansion states than in nonexpansion states, but whether ACA-related Medicaid expansion is associated with county-level opioid overdose mortality has not been examined.

OBJECTIVE

To examine whether Medicaid expansion is associated with county × year counts of opioid overdose deaths overall and by class of opioid.

DESIGN, SETTING, AND PARTICIPANTS

This serial cross-sectional study used data from 3109 counties within 49 states and the District of Columbia from January 1, 2001, to December 31, 2017 (N = 3109 counties × 17 years = 52 853 county-years). Overdose deaths were modeled using hierarchical Bayesian Poisson models. Analyses were performed from April 1, 2018, to July 31, 2019.

EXPOSURES

The primary exposure was state adoption of Medicaid expansion under the ACA, measured as the proportion of each calendar year during which a given state had Medicaid expansion in effect. By the end of study observation in 2017, a total of 32 states and the District of Columbia had expanded Medicaid eligibility.

MAIN OUTCOMES AND MEASURES

The outcomes of interest were annual county-level mortality from overdoses involving any opioid, natural and semisynthetic opioids, methadone, heroin, and synthetic opioids other than methadone, derived from the National Vital Statistics System multiple-cause-of-death files. A secondary analysis examined fatal overdoses involving all drugs.

RESULTS

There were 383 091 opioid overdose fatalities across observed US counties during the study period, with a mean (SD) of 7.25 (27.45) deaths per county (range, 0-1145 deaths per county). Adoption of Medicaid expansion was associated with a 6% lower rate of total opioid overdose deaths compared with the rate in nonexpansion states (relative rate [RR], 0.94; 95% credible interval [CrI], 0.91-0.98). Counties in expansion states had an 11% lower rate of death involving heroin (RR, 0.89; 95% CrI, 0.84-0.94) and a 10% lower rate of death involving synthetic opioids other than methadone (RR, 0.90; 95% CrI, 0.84-0.96) compared with counties in nonexpansion states. An 11% increase was observed in methadone-related overdose mortality in expansion states (RR, 1.11; 95% CrI, 1.04-1.19). An association between Medicaid expansion and deaths involving natural and semisynthetic opioids was not well supported (RR, 1.03; 95% CrI, 0.98-1.08).

CONCLUSIONS AND RELEVANCE

Medicaid expansion was associated with reductions in total opioid overdose deaths, particularly deaths involving heroin and synthetic opioids other than methadone, but increases in methadone-related mortality. As states invest more resources in addressing the opioid overdose epidemic, attention should be paid to the role that Medicaid expansion may play in reducing opioid overdose mortality, in part through greater access to medications for opioid use disorder.

Prescription drug monitoring programs operational characteristics and fatal heroin poisoning

BACKGROUND

Prescription drug monitoring programs (PDMP), by reducing access to prescribed opioids (POs), may contribute to a policy environment in which some people with opioid dependence are at increased risk for transitioning from POs to heroin/other illegal opioids. This study examines how PDMP adoption and changes in the characteristics of PDMPs over time contribute to changes in fatal heroin poisoning in counties within states from 2002 to 2016.

METHODS

Latent transition analysis to classify PDMPs into latent classes (Cooperative, Proactive, and Weak) for each state and year, across three intervals (1999-2004, 2005-2009, 2010-2016). We examined the association between probability of PDMP latent class membership and the rate of county-level heroin poisoning death.

RESULTS

After adjustment for potential county-level confounders and co-occurring policy changes, adoption of a PDMP was significantly associated with increased heroin poisoning rates (22% increase by third year post-adoption). Findings varied by PDMP type. From 2010-2016, states with Cooperative PDMPs (those more likely to share data with other states, to require more frequent reporting, and include more drug schedules) had 19% higher heroin poisoning rates than states with Weak PDMPs (adjusted rate ratio [ARR] = 1.19; 95% CI = 1.14, 1.25). States with Proactive PDMPs (those more likely to report outlying prescribing and dispensing and provide broader access to law enforcement) had 6% lower heroin poisoning rates than states with No/Weak PDMPs (ARR = 0.94; 95% CI = 0.90, 0.98).

CONCLUSION

There is a consistent, positive association between state PDMP adoption and heroin poisoning mortality. However, this varies by PDMP type, with Proactive PDMPs associated with a small reduction in heroin poisoning deaths. This raises questions about the potential for PDMPs to support efforts to decrease heroin overdose risk, particularly by using proactive alerts to identify patients in need of treatment for opioid use disorder. Future research on mechanisms explaining the reduction in heroin poisonings after enactment of Proactive PDMPs is merited.

Prescription Drug Monitoring Programs and Opioid Overdoses: Exploring Sources of Heterogeneity

BACKGROUND

Prescription drug monitoring program are designed to reduce harms from prescription opioids; however, little is known about what populations benefit the most from these programs. We investigated how the relation between implementation of online prescription drug monitoring programs and rates of hospitalizations related to prescription opioids and heroin overdose changed over time, and varied across county levels of poverty and unemployment, and levels of medical access to opioids.

METHODS

Ecologic county-level, spatiotemporal study, including 990 counties within 16 states, in 2001-2014. We modeled overdose counts using Bayesian hierarchical Poisson models. We defined medical access to opioids as the county-level rate of hospital discharges for noncancer pain conditions.

RESULTS

In 2010-2014, online prescription drug monitoring programs were associated with lower rates of prescription opioid-related hospitalizations (rate ratio 2014 = 0.74; 95% credible interval = 0.69, 0.80). The association between online prescription drug monitoring programs and heroin-related hospitalization was also negative but tended to increase in later years. Counties with lower rates of noncancer pain conditions experienced a lower decrease in prescription opioid overdose and a faster increase in heroin overdoses. No differences were observed across different county levels of poverty and unemployment.

CONCLUSIONS

Areas with lower levels of noncancer pain conditions experienced the smallest decrease in prescription opioid overdose and the faster increase in heroin overdose following implementation of online prescription drug monitoring programs. Our results are consistent with the hypothesis that prescription drug monitoring programs are most effective in areas where people are likely to access opioids through medical providers.

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.

A typology of prescription drug monitoring programs: a latent transition analysis of the evolution of programs from 1999 to 2016

BACKGROUND AND AIMS

Prescription drug monitoring programs (PDMP), defined as state-level databases used in the United States that collect prescribing information when controlled substances are dispensed, have varied substantially between states and over time. Little is known about the combinations of PDMP features that, collectively, may produce the greatest impact on prescribing and overdose. We aimed to (1) identify the types of PDMP models that have developed from 1999 to 2016, (2) estimate whether states have transitioned across PDMP models over time and (3) examine whether states have adopted different types of PDMP models in response to the burden of opioid overdose.

METHODS

A latent transition analysis of PDMP models based on an adaptation of nine PDMP characteristics classified by prescription opioid policy experts as potentially important determinants of prescribing practices and prescription opioid overdose events.

RESULTS

We divided the time-period into three intervals (1999-2004, 2005-09, 2010-16), and found three distinct PDMP classes in each interval. The classes in the first and second interval can be characterized as 'no/weak', 'proactive' and 'reactive' types of PDMPs, and in the third interval as 'weak', 'cooperative' and 'proactive'. The meaning of these classes changed over time: until 2009, states in the 'no/weak' class had no active PDMP, whereas states in the 'proactive' class were more likely to proactively provide unsolicited information to PDMP users, provide open access to law enforcement, and require more frequent data reporting than states in the 'reactive' class. In 2010-16, the 'weak' class resembled the 'reactive' class in previous intervals. States in the 'cooperative' class in 2010-16 were less likely than states in the 'proactive' class to provide unsolicited reports proactively or to provide open access to law enforcement; however, they were more likely than those in the 'proactive' class to share PDMP data with other states and to report more federal drug schedules.

CONCLUSIONS

Since 1999, US states have tended to transition to more robust classes of prescription drug monitoring programs. Opioid overdose deaths in prior years predicted the state's prescription drug monitoring program class but did not predict transitions between prescription drug monitoring program classes over time.

Association of Pharmaceutical Industry Marketing of Opioid Products With Mortality From Opioid-Related Overdoses

IMPORTANCE

Prescription opioids are involved in 40% of all deaths from opioid overdose in the United States and are commonly the first opioids encountered by individuals with opioid use disorder. It is unclear whether the pharmaceutical industry marketing of opioids to physicians is associated with mortality from overdoses.

OBJECTIVE

To identify the association between direct-to-physician marketing of opioid products by pharmaceutical companies and mortality from prescription opioid overdoses across US counties.

DESIGN, SETTING, AND PARTICIPANTS

This population-based, county-level analysis of industry marketing information used data from the Centers for Medicare & Medicaid Services Open Payments database linked with data from the Centers for Disease Control and Prevention on opioid prescribing and mortality from overdoses. All US counties were included, with data on overdoses from August 1, 2014, to December 31, 2016, linked to marketing data from August 1, 2013, to December 31, 2015, using a 1-year lag. Statistical analyses were conducted between February 1 and June 1, 2018.

MAIN OUTCOMES AND MEASURES

County-level mortality from prescription opioid overdoses, total cost of marketing of opioid products to physicians, number of marketing interactions, opioid prescribing rates, and sociodemographic factors.

RESULTS

Between August 1, 2013, and December 31, 2015, there were 434 754 payments totaling $39.7 million in nonresearch-based opioid marketing distributed to 67 507 physicians across 2208 US counties. After adjustment for county-level sociodemographic factors, mortality from opioid overdoses increased with each 1-SD increase in marketing value in dollars per capita (adjusted relative risk, 1.09; 95% CI, 1.05-1.12), number of payments to physicians per capita (adjusted relative risk, 1.18; 95% CI, 1.14-1.21, and number of physicians receiving marketing per capita (adjusted relative risk, 1.12; 95% CI, 1.08-1.16). Opioid prescribing rates also increased with marketing and partially mediated the association between marketing and mortality.

CONCLUSIONS AND RELEVANCE

In this study, across US counties, marketing of opioid products to physicians was associated with increased opioid prescribing and, subsequently, with elevated mortality from overdoses. Amid a national opioid overdose crisis, reexamining the influence of the pharmaceutical industry may be warranted.