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.

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.

Cannabis legalization and cannabis-involved pregnancy hospitalizations in Colorado.

The primary objective of this study was to evaluate the association between presence of recreational cannabis dispensaries and prevalence of cannabis-involved pregnancy hospitalizations in Colorado. This was a retrospective cohort study of pregnancy-related hospitalizations co-coded with cannabis diagnosis codes in the Colorado Hospital Association from January 1, 2011, through December 31, 2018 (recreational cannabis began January 1, 2014). Our primary outcome was cannabis-involved pregnancy hospitalizations per 10 k live births per county. The primary exposure measure was county variation in the number of recreational dispensaries. We controlled for counties' baseline exposure to medical cannabis dispensaries and used Poisson regression to evaluate the association between exposure to recreational cannabis and hospitalizations. During the study period, cannabis-involved pregnancy hospitalizations increased from 429 to 1210. Mean hospitalizations per county (1.7 to 4.7) and per 10 k live births (13.2 to 55.7) increased. Overall, increasing recreational dispensaries were associated with increases in hospitalizations (1.02, CI: 1.00,1.04). When comparing counties with different densities of baseline medical cannabis market, low and high exposure counties had fewer hospitalizations than those counties with no exposure (low: IRR 0.97, CI: 0.96-0.99; high: 0.98, CI: 0.96-0.99). In Colorado, there was more than a two-fold increase in cannabis-involved pregnancy hospitalizations between 2011 and 2018. Counties with no baseline exposure to medical cannabis had a greater increase than other counties, suggesting the recreational market may influence cannabis use among pregnant individuals.

Spatial and temporal trends in the diagnosis of opioid-related problems in commercially-insured adolescents and young adults.

Little is known about the extent to which the prevalence of opioid-related problems (ORPs) varies among U.S. adolescents and young adults across geographic regions and over time, information that can help to guide policies that aim to curb the opioid epidemic. A retrospective, cross-sectional design was used to analyze longitudinal claims data from privately insured individuals aged 12-64 years who had an outpatient or inpatient diagnosis of an ORP in the years 2005-2018. The prevalence of opioid-related problem diagnoses (per 10,000) varied considerably across census divisions, both over time and between age groups. Knowledge of the origin of and variation in diagnosed opioid-related problems in terms of age group and census division is important so that interventions and policies can be more targeted and effective.

Comparison of hospital claims and poison center data to evaluate health impact of opioids, cannabis and synthetic cannabinoids.

INTRODUCTION: Over the past 10 years, opioids and cannabis have garnered significant attention due to misuse and legalization trends. Different datasets and surveillance mechanisms can lead to different conclusions the due to a variety of factors. The primary objective of this study was to compare and describe trends of opioid, cannabis, and synthetic cannabinoid-related healthcare encounters and poison center (PC) cases in Colorado, a state that has legalized cannabis. METHODS: This was a retrospective study comparing hospital claims data (Colorado Hospital Association (CHA)) and poison center cases to describe opioid, cannabis and synthetic cannabinoid-related healthcare encounters and exposures in Colorado from 2013 to 2017 using related genetic codes and International Statistical Classification of Disease codes. RESULTS: Both datasets observed increases in cannabis related encounters and exposures after recreational cannabis legalization in 2014. CHA reported an increase for cannabis-related ER visits from 14,109 in 2013 to 18,118 in 2017 while PC noted a 74.4% increase in cannabis-related cases (125 to 218). CHA inpatient visits associated with cannabis also increased (8311 in 2013 to 14,659 in 2017). On the other hand, Opioid-related exposures to the PC fell (1092 in 2013 to 971 in 2017) while both Opioid-related ER visits (8580 in 2013 to 12,928 in 2017) and inpatient visits in CHA increased (9084 in 2013 to 13,205). CONCLUSIONS: This study demonstrates the differences in surveillance methodology for concurrent drug abuse epidemics using hospital claims and PC data. Both systems provide incomplete reports, but in combination can provide a more complete picture.

Trends in Cannabis Involvement and Risk of Alcohol Involvement in Motor Vehicle Crash Fatalities in the United States, 2000‒2018.

Objectives. To assess cannabis and alcohol involvement among motor vehicle crash (MVC) fatalities in the United States. Methods. In this repeated cross-sectional analysis, we used data from the Fatality Analysis Reporting System from 2000 to 2018. Fatalities were cannabis-involved if an involved driver tested positive for a cannabinoid and alcohol-involved based on the highest blood alcohol concentration (BAC) of an involved driver. Multinomial mixed-effects logistic regression models assessed cannabis as a risk factor for alcohol by BAC level. Results. While trends in fatalities involving alcohol have remained stable, the percentage of fatalities involving cannabis and cannabis and alcohol increased from 9.0% in 2000 to 21.5% in 2018, and 4.8% in 2000 to 10.3% in 2018, respectively. In adjusted analyses, fatalities involving cannabis had 1.56 (95% confidence interval [CI] = 1.48, 1.65), 1.62 (95% CI = 1.52, 1.72), and 1.46 (95% CI = 1.42, 1.50) times the odds of involving BACs of 0.01% to 0.049%, 0.05% to 0.079%, and 0.08% or higher, respectively. Conclusions. The percentage of fatalities involving cannabis and coinvolving cannabis and alcohol doubled from 2000 to 2018, and cannabis was associated with alcohol coinvolvement. Further research is warranted to understand cannabis- and alcohol-involved MVC fatalities. (Am J Public Health. 2021;111(11):1976-1985. https://doi.org/10.2105/AJPH.2021.306466).

Moving beyond the classic difference-in-differences model: a simulation study comparing statistical methods for estimating effectiveness of state-level policies.

BACKGROUND: Reliable evaluations of state-level policies are essential for identifying effective policies and informing policymakers' decisions. State-level policy evaluations commonly use a difference-in-differences (DID) study design; yet within this framework, statistical model specification varies notably across studies. More guidance is needed about which set of statistical models perform best when estimating how state-level policies affect outcomes. METHODS: Motivated by applied state-level opioid policy evaluations, we implemented an extensive simulation study to compare the statistical performance of multiple variations of the two-way fixed effect models traditionally used for DID under a range of simulation conditions. We also explored the performance of autoregressive (AR) and GEE models. We simulated policy effects on annual state-level opioid mortality rates and assessed statistical performance using various metrics, including directional bias, magnitude bias, and root mean squared error. We also reported Type I error rates and the rate of correctly rejecting the null hypothesis (e.g., power), given the prevalence of frequentist null hypothesis significance testing in the applied literature. RESULTS: Most linear models resulted in minimal bias. However, non-linear models and population-weighted versions of classic linear two-way fixed effect and linear GEE models yielded considerable bias (60 to 160%). Further, root mean square error was minimized by linear AR models when we examined crude mortality rates and by negative binomial models when we examined raw death counts. In the context of frequentist hypothesis testing, many models yielded high Type I error rates and very low rates of correctly rejecting the null hypothesis (< 10%), raising concerns of spurious conclusions about policy effectiveness in the opioid literature. When considering performance across models, the linear AR models were optimal in terms of directional bias, root mean squared error, Type I error, and correct rejection rates. CONCLUSIONS: The findings highlight notable limitations of commonly used statistical models for DID designs, which are widely used in opioid policy studies and in state policy evaluations more broadly. In contrast, the optimal model we identified--the AR model--is rarely used in state policy evaluation. We urge applied researchers to move beyond the classic DID paradigm and adopt use of AR models.

Trends in personal and family member opioid prescriptions prior to a diagnosis of an opioid-related problem among adolescents and young adults.

Background: Efforts to reduce the risk of opioid misuse are often focused on reducing unnecessary prescriptions for opioid medications or reducing the dose prescribed; however, not all misuse occurs in individuals with a personal prescription. This study examined trends in the proportion of adolescents and young adults (AYAs) who had an opioid-related problem (ORP) and who also had a personal opioid prescription drug claim or had a family member with an opioid prescription drug claim prior to the ORP diagnosis. Methods: A retrospective cohort design was used to analyze longitudinal claims data. We identified individuals aged 12 to 25 years who had a newly diagnosed ORP in the years 2006 to 2014. Trends over time in personal or family opioid prescription drug claims within 1 year prior to ORP diagnosis were examined. Results: We identified 53,560 AYAs with an ORP diagnosis. Over the entire study period, 40% of AYAs with an ORP diagnosis had a personal opioid prescription in the year prior to diagnosis, and 48% had a family member with an opioid prescription in the prior year. While the proportion of AYAs with a family prescription remained constant, the proportion with a personal prescription fell from 77.1% in 2006 to 27.3% in 2014. Conclusions: The number of AYAs with an ORP increased over time, yet the proportion with a personal opioid prescription claim prior to their diagnosis decreased over time. This suggests that providers are paying greater attention to prescribing opioids to AYAs directly, although prescriptions to family members may still remain a point of access.

Early evidence of the impact of cannabis legalization on cannabis use, cannabis use disorder, and the use of other substances: Findings from state policy evaluations.

Background: The past decade has seen unprecedented shifts in the cannabis policy environment, and the public health impacts of these changes will hinge on how they affect patterns of cannabis use and the use and harms associated with other substances.Objectives: To review existing research on how state cannabis policy impacts substance use, emphasizing studies using methods for causal inference and highlighting gaps in our understanding of policy impacts on evolving cannabis markets.Methods: Narrative review of quasi-experimental studies for how medical cannabis laws (MCLs) and recreational cannabis laws (RCLs) affect cannabis use and use disorders, as well as the use of or harms from alcohol, opioids, and tobacco.Results: Research suggests MCLs increase adult but not adolescent cannabis use, and provisions of the laws associated with less regulated supply may increase adult cannabis use disorders. These laws may reduce some opioid-related harms, while their impacts on alcohol and tobacco use remain uncertain. Research on RCLs is just emerging, but findings suggest little impact on the prevalence of adolescent cannabis use, potential increases in college student use, and unknown effects on other substance use.Conclusions: Research on how MCLs influence cannabis use has advanced our understanding of the importance of heterogeneity in policies, populations, and market dynamics, but studies of how MCLs relate to other substance use often ignore these factors. Understanding effects of cannabis laws requires greater attention to differences in short- versus long-term effects of the laws, nuances of policies and patterns of consumption, and careful consideration of appropriate control groups.

A population-based examination of trends and disparities in medication treatment for opioid use disorders among Medicaid enrollees.

BACKGROUND: Medication treatment (MT) with methadone and buprenorphine are effective treatments for opioid use disorders, but little information is available regarding the extent to which buprenorphine's approval resulted in more individuals receiving MT nor to what extent receipt of such treatment was equitable across communities. METHODS: To examine changes in MT utilization and the association between MT utilization and county-level indicators of poverty, race/ethnicity, and urbanicity, we used Medicaid claims of non-dually eligible Medicaid enrollees aged 18-64 from 14 states for 2002-2009. We generated county-level aggregate counts of MT (methadone, buprenorphine, and any MT) by year (N = 7760 county-years). We estimated count data models to identify associations between MT and county characteristics, including levels of poverty and racial/ethnic concentration. RESULTS: The number of Medicaid enrollees receiving MT increased 62% from 2002 to 2009. The number of enrollees receiving methadone increased 20%, with the remaining increase resulting from buprenorphine. Urban county residents were significantly more likely to receive MT in both 2002 and 2009 than rural county residents. However, buprenorphine substantially increased MT in rural counties from 2002 to 2009. Receipt of MT increased at a much higher rate for residents of counties with lower poverty rates and lower concentrations of black and Hispanic individuals than for residents of counties without those characteristics. CONCLUSIONS: The increase in Medicaid enrollees receiving MT in the years following buprenorphine's approval is encouraging. However, it is concerning that MT trends varied so dramatically by characteristics of the county population and that increases in utilization were substantially lower in counties with populations that historically have been disadvantaged with respect to health care access and quality. Concerted efforts are needed to ensure that MT benefits are equitably distributed across society and reach disadvantaged individuals who may be at higher risk of experiencing opioid use disorders.

Medical Marijuana and Marijuana Legalization.

State-level marijuana liberalization policies have been evolving for the past five decades, and yet the overall scientific evidence of the impact of these policies is widely believed to be inconclusive. In this review we summarize some of the key limitations of the studies evaluating the effects of decriminalization and medical marijuana laws on marijuana use, highlighting their inconsistencies in terms of the heterogeneity of policies, the timing of the evaluations, and the measures of use being considered. We suggest that the heterogeneity in the responsiveness of different populations to particular laws is important for interpreting the mixed findings from the literature, and we highlight the limitations of the existing literature in providing clear insights into the probable effects of marijuana legalization.

Early Impacts of Marijuana Legalization: An Evaluation of Prices in Colorado and Washington.

Following the legalization and regulation of marijuana for recreational purposes in states with medical markets, policymakers and researchers seek empirical evidence on how, and how fast, supply and demand changed over time. Prices are an indication of how suppliers and consumers respond to policy changes, so this study uses a difference-in-difference approach to exploit the timing of policy implementation and identify the impacts on marijuana prices 4-5 months after markets opened. This study uses unique longitudinal survey data of prices paid by consumers and a web-scraped dataset of dispensary prices advertised online for three U.S. medical marijuana states that all eventually legalized recreational marijuana. Results indicate there were no impacts on the prices paid for medical or recreational marijuana by state-representative residents within the short 4- to 5-months window following legalization. However, there were differences in how much people paid if they obtained marijuana for recreational purposes from a recreational store. Further analysis of advertised prices confirms this result, but further demonstrates heterogeneous responses in prices across types of commonly advertised strains; prices either did not change or increased depending on the strain type. A key implication of our findings is that there are both supply and demand responses at work in the opening of legalized markets, suggesting that evaluations of immediate effects may not accurately reflect the long run impact of legalization on consumption.

Where Is Buprenorphine Dispensed to Treat Opioid Use Disorders? The Role of Private Offices, Opioid Treatment Programs, and Substance Abuse Treatment Facilities in Urban and Rural Counties.

POLICY POINTS: Buprenorphine is an effective opioid dependence treatment that has expanded access to care since its 2002 approval, but it can only be prescribed by physicians waivered to treat a limited number of individuals. We examined the impact of 2006 legislation that increased waivered physician patient limits from 30 to 100 on buprenorphine use, and found that 100-patient-waivered physicians were significantly associated with growth in buprenorphine use, with no such relationship for 30-patient-waivered physicians. Policies relaxing patient limits may be more effective in increasing buprenorphine use than alternatives such as opening new substance abuse treatment facilities or increasing the overall number of waivered physicians. CONTEXT: Opioid use disorders are a significant public health problem. In 2002, the FDA approved buprenorphine as an opioid use disorder treatment when prescribed by waivered physicians who were limited to treating 30 patients at a time. In 2006, federal legislation raised this number to 100 patients. Although federal legislators are considering increasing these limits further and expanding prescribing privileges to nonphysicians, little information is available regarding the impact of such changes on buprenorphine use. We therefore examined the impact of the 2006 legislation-as well as the association between urban and rural waivered physicians, opioid treatment programs, and substance abuse treatment facilities-on buprenorphine distributed per capita over the past decade. METHODS: Using 2004-2011 state-level data on buprenorphine dispensed and county-level data on the number of buprenorphine-waivered physicians and substance abuse treatment facilities using buprenorphine, we estimated a multivariate ordinary least squares regression model with state fixed effects of a state's annual total buprenorphine dispensed per capita as a function of the state's number of buprenorphine providers. FINDINGS: The amount of buprenorphine dispensed has been increasing at a greater rate than the number of buprenorphine providers. The number of physicians waivered to treat 100 patients with buprenorphine in both rural and urban settings was significantly associated with increased amounts of buprenorphine dispensed per capita. There was no significant association in the growth of buprenorphine distributed and the number of physicians with 30-patient waivers. CONCLUSIONS: The greater amounts of buprenorphine dispensed are consistent with the potentially greater use of opioid agonists for opioid use disorder treatment, though they also make their misuse more likely. The changes after the 2006 legislation suggest that policies focused on increasing the number of patients that a single waivered physician could safely and effectively treat could be more effective in increasing buprenorphine use than would alternatives such as opening new substance abuse treatment facilities or raising the overall number of waivered physicians.

Developing public health regulations for marijuana: lessons from alcohol and tobacco.

Until November 2012, no modern jurisdiction had removed the prohibition on the commercial production, distribution, and sale of marijuana for nonmedical purposes-not even the Netherlands. Government agencies in Colorado and Washington are now charged with granting production and processing licenses and developing regulations for legal marijuana, and other states and countries may follow. Our goal is not to address whether marijuana legalization is a good or bad idea but, rather, to help policymakers understand the decisions they face and some lessons learned from research on public health approaches to regulating alcohol and tobacco over the past century.

Medical Cannabis Dosing Trajectories of Patients: Evidence From Sales Data.

PURPOSE: Medical cannabis use is rising with limited high-quality clinical trial data to guide dosing. This study relies on real-world, longitudinal medical cannabis purchase data to provide information on Δ-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) dosing trends for patients with qualifying medical conditions. METHODS: A retrospective study of purchases by 16,727 patients obtaining medical cannabis from dispensaries located in New York between 2016 and 2019, recorded in point-of-sale data. Group-based trajectory modeling was used to identify clusters of patients following similar progressions in dosing of THC and CBD over time. χ2 tests were performed to identify which patient characteristics and qualifying medical conditions were associated with membership in each trajectory group. FINDINGS: Six trajectory groups were identified that described different patterns in the THC and CBD doses that patients purchased over the whole time period. For THC, the majority of patients (62.6%) purchased a steady amount but at different levels: consistently low (4.1 mg) or moderate (7.4 mg). Three groups, representing 22.0% together, exhibited doses that either fluctuate or constantly increase over time (5-20 mg). A final group of patients (15.8%) exhibited constant decrease in dose from 11 to 5 mg. For CBD, the data show similar trajectories, but at the generally higher values (4-16 mg). Patients with chronic pain, neuropathy, and cancer were overrepresented in groups where higher doses of THC were purchased over time. Patients with epilepsy had a higher representation in groups with higher doses of CBD across time. IMPLICATIONS: Results suggest heterogeneous dosing patterns and trajectories in the use of medical cannabis by patients with different medical conditions.

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.

Investigating the complexity of naloxone distribution: Which policies matter for pharmacies and potential recipients.

Despite efforts to expand naloxone access, opioid-related overdoses remain a significant contributor to mortality. We study state efforts to expand naloxone distribution through pharmacies by reducing the non-monetary costs to prescribers, dispensers, and/or potential recipients of naloxone. We find that laws that only address liability costs have small and insignificant effects on the volume of naloxone dispensed through pharmacies. In contrast, we estimate large effects of laws removing the need for patients to obtain prescriptions from traditional prescribers (e.g., primary care physicians): laws authorizing non-patient-specific prescription distribution and laws granting pharmacists prescriptive authority. We test whether areas designated as primary care shortage areas-where it would be costlier to obtain a prescription-were disproportionately impacted. Shortage areas experienced sharper growth in pharmacy naloxone dispensing in states adopting prescriptive authority policies. These gains were primarily due to those facing low out-of-pocket costs, suggesting that price barriers also must be addressed to increase naloxone purchases.

Association of Daily Doses of Buprenorphine With Urgent Health Care Utilization.

Importance: Higher buprenorphine doses may benefit the increasing number of individuals using fentanyl and other synthetic opioids, but there is little empirical evidence on the efficacy of such higher doses. Objective: To examine the association between higher buprenorphine doses (above 16 mg and 24 mg) and subsequent emergency department (ED) or inpatient service use among patients diagnosed with opioid use disorder. Design, Setting, and Participants: This cross-sectional study was a retrospective analysis of health data from Optum's deidentified Clinformatics Data Mart Database from 2016 to 2021 for commercially insured individuals aged 18 years or older diagnosed with opioid use disorder (OUD). Eligible participants initiated buprenorphine after at least 90 days of enrollment and were dispensed at least a 14-day supply of buprenorphine. Data were analyzed from September 2023 through February 2024. Exposures: Maximum buprenorphine dose received by a patient for 14 or more days: more than 24 mg, more than 16 mg to 24 mg, more than 8 mg to 16 mg, or 1 mg to 8 mg. Main Outcomes and Measures: Days from initiation of the maximum buprenorphine dose to an ED or inpatient visit for a behavioral health diagnosis, controlling for patient demographics, comorbid conditions, time to reaching maximum dose, buprenorphine discontinuation, and pre-buprenorphine health care utilization. Results: A total of 35 451 individuals with an OUD diagnosis who began buprenorphine treatment were identified (mean [SD] age, 46.2 [15.1] years; 20 983 male [59.2%]; 3326 Black [9.4%], 2411 Hispanic [6.8%], 26 712 White [75.3%]). The most common dose was more than 8 mg to 16 mg daily (14 802 patients [42.9%]), with 9669 patients (27.3%) in the 1 mg to 8 mg tier, 10 329 patients (29.1%) in the 8 mg to 16 mg tier, and 651 patients (1.8%) in the tier receiving more than 24 mg. Among all patients receiving buprenorphine, 12.5% experienced an ED or inpatient visit. Survival analysis shows patients receiving doses more than 24 mg and between 16 mg to 24 mg had longer times to ED or inpatient use than patients receiving from 8 mg to 16 mg (time ratio [TR], 1.11; 95% CI, 1.02 to 1.20) and more than 24 mg (TR, 1.37; 95% CI, 1.04 to 1.81). Findings for doses above 16 mg daily were consistent for observation windows as short as 365 days (more than 24 mg: TR, 1.48; 95% CI, 1.01-2.18; more than 16 mg to 24 mg: TR, 1.19; 95% CI, 1.06-1.32). Conclusions and Relevance: These findings contribute to the sparse empirical research regarding potential benefits of higher-dose buprenorphine treatment of individuals with OUD. Clinicians should be aware of the potential effects of higher buprenorphine doses on health care utilization while policymakers work to ensure equitable access to individuals who could potentially benefit from higher doses.