The Impact of Medicaid Institutions for Mental Disease Exclusion Waivers on the Availability of Substance Abuse Treatment Services and the Varying Effect by Ownership Type.

Policy Points The adoption of Medicaid institutions for mental disease (IMD) exclusion waivers increases the likelihood of substance abuse treatment facilities offering mental health and substance abuse treatment for co-occurring disorders, especially in residential facilities. There are differential responses to IMD waivers based on facility ownership. For-profit substance abuse treatment facilities are responsive to the adoption of IMD substance use disorder waivers, whereas private not-for-profit and public entities are not. The response of for-profit facilities suggests that integration of substance abuse and mental health treatment for individuals in residential facilities may be cost-effective. CONTEXT: Access to integrated care for those with co-occurring mental health (MH) and substance use disorders (SUDs) has been limited because of an exclusion in Medicaid on paying for SUD care for those in institutions for mental disease (IMDs). Starting in 2015, the federal government encouraged states to pursue waivers of this exclusion, and by the end of 2020, 28 states had done so. It is unclear what impact these waivers have had on the availability of care for co-occurring disorders and the characteristics of any facilities that expanded care because of them. METHODS: Using data from the National Survey of Substance Abuse Treatment Services, we estimate a two-stage residual inclusion model including time- and state-fixed effects to examine the effect of state IMD SUD waivers on the percentage of facilities offering co-occurring MH and SUD treatment, overall and for residential facilities specifically. Separate analyses are conducted by facility ownership type. FINDINGS: Results show that the adoption of an IMD SUD waiver is associated with 1.068 greater odds of that state having facilities offering co-occurring MH and substance abuse (SA) treatment a year or more later. The adoption of a waiver increases the odds of a state's residential treatment facility offering co-occurring MH and SA treatment by 1.129 a year or more later. Additionally, the results suggest 1.163 higher odds of offering co-occurring MH/SA treatment in private for-profit SA facilities in states that adopt an IMD SUD waiver while suggesting no significant impact on offered services by private not-for-profit or public facilities. CONCLUSIONS: Our study findings suggest that Medicaid IMD waivers are at least somewhat effective at impacting the population targeted by the policy. Importantly, we find that there are differential responses to these IMD waivers based on facility ownership, providing new evidence for the literature on the role of ownership in the provision of health care.

Expert Views on State Policies to Improve Engagement and Retention in Treatment for Opioid Use Disorder: A Qualitative Analysis of an Online Modified Delphi Process.

OBJECTIVES: The aim of this study was to examine expert views on the effectiveness and implementability of state policies to improve engagement and retention in treatment for opioid use disorder (OUD). METHODS: We conducted a 3-round modified Delphi process using the online ExpertLens platform. Participants included 66 experts on OUD treatment policies. Experts commented on 14 hypothetical state policies targeting treatment engagement and quality of care. Using the GRADE Evidence-to-Decision framework, we conducted reflexive thematic analysis to develop patterns of meaning from the dataset. RESULTS: Only policies for providing continued access to evidence-based treatment for highly at-risk populations, settings, and periods were seen as effective in meaningfully reducing population-level opioid-related overdose mortality. Experts commented that, although the general public increasingly supports policies expanding medications for OUD and evidence-based care, ongoing stigma about OUD encourages public acceptance of punitive and paternalistic policies. Experts viewed all policies as at least moderately feasible given the current infrastructure and resources, with affordability reliant on long-term cost savings from reduced opioid-related harms. Equitability depended on whether experts perceived a policy as inherently equitable in its design as well as concerns about the potential for inequitable implementation due to structural oppression and interpersonal biases in criminal-legal, healthcare, and other systems. CONCLUSIONS: Experts believe that supportive (rather than punitive) policies improve engagement and retention in OUD treatment. States could prioritize implementing supportive policies that are patient-centered and take a harm-reduction approach to enhance medications for OUD access and utilization. States could consider deimplementing punitive policies that are coercive, take an abstinence-only approach, and use punitive and restrictive measures.

Relationships Between Alcohol and Cannabis Policies in U.S. States, 1999-2019.

OBJECTIVE: A crucial question regarding the public health impacts of cannabis legalization is its impact on alcohol consumption and alcohol-related harm. However, little is known about whether these changing cannabis policies are occurring in liberal or in restrictive alcohol policy environments, either of which likely affect public health outcomes. We constructed comprehensive state-level alcohol and cannabis policy indices and explored relationships between them. METHOD: We assessed relationships between the Alcohol Policy Scale (APS) and the Cannabis Policy Scale (CPS) from 1999 to 2019. The APS and CPS were based on 29 and 17 state-level policies, respectively, and each policy was weighted for its relative efficacy and degree of state-year implementation. RESULTS: From 1999 to 2019, average state APS scores increased modestly (became more restrictive) by 4.11 points (2019 M = 43.23, range: 24.44-66.31) and average CPS scores decreased (became less restrictive) by 15.33 points (2019 M = 76.40, range: 29.40-95.74) on a 100-point scale. In 2019, average APS scores were similar among states that prohibited (criminalized) possession of cannabis (42.00), decriminalized possession (41.33), legalized medical cannabis (44.36), and legalized recreational cannabis (43.32). Across states, there was no correlation between the restrictiveness of state-level alcohol and cannabis policies (r = .03, p = .37) in unadjusted models, although there was some variation by time, geographic region, and political party, with a weak negative correlation in state fixed-effects models. CONCLUSIONS: Although cannabis policies liberalized rapidly from 1999 to 2019, alcohol policies stayed relatively stable and did not differ by degree of cannabis policy liberalization. In general, there were weak associations between cannabis and alcohol policies among states; however, there was some temporal, regional, and political variation.

Changes in Cannabis-Attributable Hospitalizations Following Nonmedical Cannabis Legalization in Canada.

Importance: The impact of adult-use cannabis legalization and subsequent commercialization (ie, increasing store and product access) on hospitalizations in Canada is unclear. Objectives: To examine changes in overall and subtypes of hospitalizations due to cannabis and associated factors following legalization in Canada and to compare changes between provinces. Design, Setting, and Participants: This repeated cross-sectional analysis included all acute hospitalizations for individuals aged 15 to 105 years in Canada's 4 most populous provinces (Ontario, Quebec, Alberta and British Columbia, population 26.9 million individuals in 2018). Data were obtained from routinely collected health administrative databases. Immediate and gradual changes in the age- and sex-standardized rates of hospitalizations due to cannabis were compared using an interrupted time series design over 3 time periods: prelegalization (January 2015 to September 2018), legalization with product and store restrictions (October 2018 to February 2020), and commercialization, which overlapped with the COVID-19 pandemic (March 2020 to March 2021). Main Outcomes and Measures: Rates of hospitalizations due to cannabis per 100 000 individuals and per 1000 all-cause hospital admissions. Results: There were 105 203 hospitalizations due to cannabis over the 7-year study period, 69 192 of which (65.8%) were among male individuals, and 34 678 (33%) of which were among individuals aged 15 to 24 years. Overall, the age- and sex-standardized rate of hospitalizations increased 1.62 times between January 2015 (3.99 per 100 000 individuals) and March 2021 (6.46 per 100 000 individuals). The largest relative increase in hospitalizations was for cannabis-induced psychosis (rate ratio, 1.40; 95% CI, 1.34 to 1.47 during the commercialization period relative to the prelegalization period). Nationally, legalization with restrictions was associated with a gradual monthly decrease of -0.06 (95% CI -0.08 to -0.03) in hospitalizations due to cannabis per 100 000 individuals. Commercialization and the COVID-19 pandemic were associated with an immediate increase of 0.83 (95% CI, 0.30 to 1.30) hospitalizations due to cannabis per 100 000 individuals. There was provincial variation in changes, with provinces with less mature legal markets experiencing the greatest declines immediately following legalization. Conclusions and Relevance: This cross-sectional study found that legalization with restrictions was not associated with an increase in hospitalizations due to cannabis but commercialization was. The findings suggest that commercialization of cannabis may be associated with increases in cannabis-related health harms, including cannabis-induced psychosis.

America's Opioid Ecosystem: How Leveraging System Interactions Can Help Curb Addiction, Overdose, and Other Harms.

Opioids play an outsized role in America's drug problems, but they also play a critically important role in medicine. Thus, they deserve special attention. Illegally manufactured opioids (such as fentanyl) are involved in a majority of U.S. drug overdoses, but the problems are broader and deeper than drug fatalities. Depending on the drugs involved, there can be myriad physical and mental health consequences associated with having a substance use disorder. And it is not just those using drugs who suffer. Substance use and related behaviors can significantly affect individuals' families, friends, employers, and wider communities. Efforts to address problems related to opioids are insufficient and sometimes contradictory. Researchers provide a nuanced assessment of America's opioid ecosystem, highlighting how leveraging system interactions can reduce addiction, overdose, suffering, and other harms. At the core of the opioid ecosystem are the individuals who use opioids and their families. Researchers also include detail on ten major components of the opioid ecosystem: substance use disorder treatment, harm reduction, medical care, the criminal legal system, illegal supply and supply control, first responders, the child welfare system, income support and homeless services, employment, and education. The primary audience for this study is policymakers, but it should also be useful for foundations looking for opportunities to create change that have often been overlooked. This study can help researchers better consider the full consequences of policy changes and help members of the media identify the dynamics of interactions that deserve more attention.

Understanding the rise in overdose deaths involving opioids and non-opioid prescription drugs in the United States.

BACKGROUND: Previous studies demonstrate that the reformulation of OxyContin in the U.S. in 2010 induced substitution to illicit opioids, causing illicit opioid markets to grow disproportionately fast in states more exposed to the reformulation. In this paper, we examine if this shift to the illicit market also led to a rise in polysubstance overdose deaths involving non-opioid prescription drugs, including gabapentinoids and "Z-drugs" and, separately, benzodiazepines. METHODS: Using a difference-in-differences framework, the relationship between exposure to reformulation and overdose death rates including specific substances was studied in each year from 1999 to 2020 while accounting for fixed differences across states, common nationwide shocks, and state-level differences in pain reliever misuse prior to reformulation. Exposure to reformulation was measured as the pre-reformulation rate of OxyContin misuse. RESULTS: Exposure to reformulation predicted growth in overdose deaths involving gabapentinoids and Z-drugs. There is less evidence that it predicted growth in overdose deaths involving benzodiazepines. However, for all substances, there is strong evidence that pre-reformulation OxyContin misuse rates predicted post-reformulation growth in overdose deaths concurrently involving synthetic opioids. DISCUSSION: The opioid crisis has changed in radical ways. This study links a major supply-side intervention to the increase in polysubstance overdose deaths involving non-opioid prescription drugs, specifically gabapentinoids and Z-drugs.

Impact of Recreational Cannabis Legalization on Opioid Prescribing and Opioid-Related Hospital Visits in Colorado: an Observational Study.

BACKGROUND: Cannabis may be a substitute for opioids but previous studies have found conflicting results when using data from more recent years. Most studies have examined the relationship using state-level data, missing important sub-state variation in cannabis access. OBJECTIVE: To examine cannabis legalization on opioid use at the county level, using Colorado as a case study. Colorado allowed recreational cannabis stores in January 2014. Local communities could decide whether to allow dispensaries, creating variation in the level of exposure to cannabis outlets. DESIGN: Observational, quasi-experimental design exploiting county-level variation in allowance of recreational dispensaries. SUBJECTS: Colorado residents MEASURES: We use licensing information from the Colorado Department of Revenue to measure county-level exposure to cannabis outlets. We use the state's Prescription Drug Monitoring Program (2013-2018) to construct opioid-prescribing measures of number of 30-day fills and total morphine equivalents, both per county resident per quarter. We construct outcomes of opioid-related inpatient visits (2011-2018) and emergency department visits (2013-2018) with Colorado Hospital Association data. We use linear models in a differences-in-differences framework that accounts for the varying exposure to medical and recreational cannabis over time. There are 2048 county-quarter observations used in the analysis. RESULTS: We find mixed evidence of cannabis exposure on opioid-related outcomes at the county level. We find increasing exposure to recreational cannabis is associated with a statistically significant decrease in number of 30-day fills (coefficient: -117.6, p-value<0.01) and inpatient visits (coefficient: -0.8, p-value: 0.03), but not total MME nor ED visits. Counties with no medical exposure prior to recreational legalization experience greater reductions in the number of 30-day fills and MME than counties with prior medical exposure (p=0.02 for both). CONCLUSIONS: Our mixed findings suggest that further increases in cannabis beyond medical access may not always reduce opioid prescribing or opioid-related hospital visits at a population level.

Medical marijuana access and prolonged opioid use among adolescents and young adults.

BACKGROUND AND OBJECTIVES: Laws liberalizing access to medical marijuana are associated with reduced opioid analgesic use among adults, but little is known about the impact of such policies on adolescents and young adults. METHODS: This retrospective cohort study used 2005 to 2014 claims from MarketScan® Commercial database, which covers all 50 states and Washington D.C. The sample included 195,204 adolescent and young adult patients (aged 12-25) who underwent one of 13 surgical procedures. RESULTS: Of the 195,204 patients, 4.8% had prolonged opioid use. Several factors were associated with a higher likelihood of prolonged opioid use, including being female (adjusted odds ratio [aOR], 1.27; 95% confidence interval [CI], 1.21-1.33), longer hospital stay (aOR, 1.04; 95% CI, 1.02-1.06), greater days of index opioid supply (8-14 days: aOR, 1.39, 95% CI, 1.33-1.45; greater than 14 days: aOR, 2.42, 95% CI, 2.26-2.59), rural residence (aOR, 1.07; 95% CI, 1.01-1.14), and cholecystectomy (aOR, 1.16; 95% CI, 1.08-1.25). There was not a significant association of medical marijuana dispensary laws on prolonged opioid use (aOR, 0.98; 95% CI, 0.81-1.18). CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Medical marijuana has been suggested as a substitute for opioids, but our results focusing on adolescents and young adults provide new evidence that this particularly vulnerable population does not exhibit reductions in prolonged use of opioids after surgery when they have legal access to medical marijuana. These findings are the first to demonstrate potentially important age differences in sustained use of opioids, and point to the need for prescriber oversight and management with this vulnerable population.

Regular Cannabis Use During the First Year of the Pandemic: Studying Trajectories Rather Than Prevalence.

INTRODUCTION: Cannabis use in the U.S. rose early in the COVID-19 pandemic, but it is unclear whether that rise was temporary or permanent. This study estimated the nature and sociodemographic correlates of U.S. adult subpopulations regularly using cannabis by examining weekly trajectories of use during the first year of the pandemic. METHODS: Data came from the Understanding America Study, a nationally representative panel of U.S. adults (N=8,397; March 10, 2020-March 29, 2021). A growth mixture model was deployed to identify subgroups with similar regular cannabis use. Sociodemographic correlates of subgroups were examined using multinomial logistic regression. RESULTS: Four cannabis-use groups were identified. Most participants did not regularly use cannabis (no regular use; 81.7%). The other groups increased regular use until April 2020 but then diverged. Some (7.1%) decreased thereafter, whereas others (3.4%) maintained their elevated use until October 26, 2020 before decreasing. The last group (7.7%) sustained their elevated use throughout. Individuals aged between 18 and 39 years, unmarried, living in poverty, without a college degree, and with longer unemployment or underemployment spells had higher odds of being in the other groups with more weekly use than in the no-regular-use group. CONCLUSIONS: The analyses revealed population subgroups with prolonged regular cannabis use and a disproportionate concentration of socioeconomically vulnerable members of society in these subgroups. These findings elucidate important heterogeneity in the subpopulations using cannabis, highlighting the urgent need to tailor public health programs for subgroups that may have unique service needs.

Prices and Purchase Sources for Dried Cannabis Flower in the United States, 2019-2020.

Introduction: The price of cannabis has major implications for public health, public safety, social equity, and government revenues. This article examines prices and sources of purchased dried cannabis flower among consumers facing different state laws in the United States. Methods: Repeat cross-sectional survey data were collected from the International Cannabis Policy Study in 2019 and 2020. U.S. respondents were recruited through online commercial panels, ages 16-65, and purchased dried flower in the past year (n=9766). Weighted binary logistic regression models examined legal purchasing in states that had legalized recreational cannabis. Results: Compared with respondents in states with recreational stores, respondents living in "illegal," "medical," and "recreational" states without stores were associated with paying a higher unit price of dried flower (+20.5%, +23.6%, +27.4%, respectively; all p<0.05). The majority of respondents in states with recreational stores last purchased from stores/dispensaries (2019: 66.6%; 2020: 62.0%) and the odds of purchasing legally was greater with each additional year after stores opened (adjusted odds ratio=1.48, 95% confidence interval: 1.37, 1.60). Conclusions: Cannabis prices and purchase behaviors are strongly influenced by its legal status and presence of stores. After states legalize for recreational purposes, it takes multiple years for the legal market to become established as the number of retail stores increase and prices decrease. The findings demonstrate that consumers use sources that they are legally allowed to access, suggesting an increased number of physical retail stores and online delivery services could expand uptake of legal sources in states with recreational cannabis laws.

The Cannabis Policy Scale: A New Research and Surveillance Tool for U.S. States.

OBJECTIVE: Rapid shifts toward cannabis liberalization in the United States have created immense policy variability that is challenging to measure. We developed composite measures to characterize the restrictiveness of U.S. state cannabis policy environments. METHOD: Nine panelists, consisting of four research team members and five expert policy consultants, nominated distinct cannabis policies pertaining to cannabis prohibition, medicalization, and legalization for recreational use. For each of the 17 nominated policies, panelists developed implementation ratings and rated each policy's relative efficacy for reducing excessive cannabis use by adults, youth use, and impaired driving. Cannabis Policy Scale scores were then calculated for each state-year for all 50 states from 1999 to 2019 by weighting policies by their efficacy and implementation ratings, and then summing over policies. RESULTS: Median Cannabis Policy Scale scores remained stable until 2008, when they started declining (representing policy liberalization), with steeper declines after 2012. In 2019, state Cannabis Policy Scale scores targeting excessive use among the general population ranged from 29.6 to 66.7 for recreational cannabis legalization states, and from 72.4 to 93.4 for medical cannabis legalization states. Cannabis Policy Scale scores using youth-specific and driving-specific efficacy ratings showed similar trends. CONCLUSIONS: The Cannabis Policy Scale reflects trends toward liberalization of cannabis policy in many U.S. states. Even within crude policy phenotypes (e.g., medical cannabis programs), Cannabis Policy Scale scores varied considerably between states and over time. The Cannabis Policy Scale is a new measure that can add nuance to cannabis policy research and help assess cannabis policy-outcome relationships.

Trends in Out-of-Pocket Costs for Naloxone by Drug Brand and Payer in the US, 2010-2018.

Importance: Improving access to naloxone is a critical component of the nation's strategy to curb fatal overdoses in the opioid crisis. Standing or protocol orders, prescriptive authority laws, and immunity provisions have been passed by states to expand access, but less attention has been given to potential financial barriers to naloxone access. Objective: To assess trends in out-of-pocket (OOP) costs for naloxone and examine variation in OOP costs by drug brand and payer. Design, Setting, and Participants: This observational study analyzed US naloxone claims data from Symphony Health and associated OOP costs for individuals filling naloxone prescriptions by drug brand and payer between January 1, 2010, to December 31, 2018. The data were analyzed from March 31, 2021, to April 12, 2022. Main Outcomes and Measures: The main measures were trends in annual number of naloxone claims (overall, by payer, and by drug brand) and mean annual OOP costs per claim (overall, by payer, and by drug brand). Results: Of 719 612 naloxone claims (172 894 generic naloxone, 501 568 Narcan, and 45 150 Evzio) for 2010 through 2018, the number of naloxone claims among insured patients began rapidly increasing after 2014; at the same time, the mean OOP cost of naloxone increased dramatically among the uninsured population. Comparing 2014 with 2018, the mean OOP cost of naloxone decreased by 26% among those with insurance but increased by 506% among uninsured patients. For the uninsured population, the impediment of cost was even larger for certain brands of the drug. In 2016, the mean OOP cost for Evzio among uninsured patients rose to $2136.37 (a 2429% increase relative to 2015) compared with the mean cost of generic naloxone, $72.88, and the cost of Narcan in its first year, $87.95. Throughout the period, the mean OOP costs paid by uninsured patients were higher for Evzio at $1089.17 (95% CI, $884.17-$1294.17) compared with $73.62 (95% CI, $69.24-$78.00) for Narcan and $67.99 (95% CI, $61.42-$74.56) for generic naloxone. Conclusions and Relevance: In this observational study, the findings indicated that the OOP cost of naloxone had been an increasingly substantial barrier to naloxone access for uninsured patients, potentially limiting use among this population, which constituted approximately 20% of adults with opioid use disorder.

Expert Panel Consensus on State-Level Policies to Improve Engagement and Retention in Treatment for Opioid Use Disorder.

Importance: In the US, recent legislation and regulations have been considered, proposed, and implemented to improve the quality of treatment for opioid use disorder (OUD). However, insufficient empirical evidence exists to identify which policies are feasible to implement and successfully improve patient and population-level outcomes. Objective: To examine expert consensus on the effectiveness and the ability to implement state-level OUD treatment policies. Evidence Review: This qualitative study used the ExpertLens online platform to conduct a 3-round modified Delphi process to convene 66 stakeholders (health care clinicians, social service practitioners, addiction researchers, health policy decision-makers, policy advocates, and persons with lived experience). Stakeholders participated in 1 of 2 expert panels on 14 hypothetical state-level policies targeting treatment engagement and linkage, evidence-based and integrated care, treatment flexibility, and monitoring or support services. Participants rated policies in round 1, discussed results in round 2, and provided final ratings in round 3. Participants used 4 criteria associated with either the effectiveness or implementability to rate and discuss each policy. The effectiveness panel (n = 29) considered policy effects on treatment engagement, treatment retention, OUD remission, and opioid overdose mortality. The implementation panel (n = 34) considered the acceptability, feasibility, affordability, and equitability of each policy. We measured consensus using the interpercentile range adjusted for symmetry analysis technique from the RAND/UCLA appropriateness method. Findings: Both panels reached consensus on all items. Experts viewed 2 policies (facilitated access to medications for OUD and automatic Medicaid enrollment for citizens returning from correctional settings) as highly implementable and highly effective in improving patient and population-level outcomes. Participants rated hub-and-spoke-type policies and provision of financial incentives to emergency departments for treatment linkage as effective; however, they also rated these policies as facing implementation barriers associated with feasibility and affordability. Coercive policies and policies levying additional requirements on individuals with OUD receiving treatment (eg, drug toxicology testing, counseling requirements) were viewed as low-value policies (ie, decreasing treatment engagement and retention, increasing overdose mortality, and increasing health inequities). Conclusions and Relevance: The findings of this study may provide urgently needed consensus on policies for states to consider either adopting or deimplementing in their efforts to address the opioid overdose crisis.

Most recent, modal, or median heroin purchase: Does it matter when estimating market size?

BACKGROUND: Assessing the size of illicit drug markets is an important activity of many government agencies; however, the expenditure-based method for estimating market size relies on the relatively untested assumption that the cash value of the most recent purchase is representative of the average purchase amount. Using panel data, we test the representativeness of the most recent, modal and median purchase compared to the average purchase amount. METHODS: Data were drawn from a prior study that collected daily transaction-level purchase data from a sample of 120 people who were using heroin regularly. The same study participants completed two distinct two-week waves of data collection, separated by six months. T-tests and bootstrapping were used to detect differences within each wave between the average cash value of participant heroin purchases and the cash value of their most recent, modal and median heroin purchases. RESULTS: In both waves, we found (a) no evidence that the expected value of the most recent purchase differs from the expected value of the average purchase, and (b) the expected values of the modal and median purchases are smaller than the expected value of the average purchase. These results imply that estimates of total market size based on the modal or median purchase will suffer from a significant downward bias, but that estimates based on the most recent purchase will be unbiased. CONCLUSIONS: We provide evidence in support of using the most recent (but not the modal or the median) purchase to estimate market size for heroin.