Journal: JAMA Network Open, 2024, doi:10.1001/jamanetworkopen.2024.32021
Authors: Ashley C. Bradford, Felipe Lozano-Rojas, Hailemichael Bekele Shone, David Bradford, & Amanda J. Abraham
Abstract:
Importance: Mental health disorders are prevalent yet undertreated health conditions in the US. Given perceptions about the potential effect of cannabis on individuals with mental health disorders, there is a need to understand the association of cannabis laws with psychotropic use.
Objective: To investigate the association of medical and recreational cannabis laws and dispensary openings with the dispensing of psychotropic medications used to treat mental health disorders in the US.
Design, Setting, and Participants: This cross-sectional study of 10 013 948 commercially insured patients used a synthetic control method to examine the association of cannabis policies with prescribing. Data on all patients dispensed prescriptions for each of the 5 classes of psychotropic medications from January 1, 2007, to December 31, 2020, were extracted from Optum’s deidentified Clinformatics Data Mart Database. Statistical analysis was performed from September 2022 to November 2023.
Exposures: The 4 exposure variables measured were whether medical or recreational cannabis laws were in effect and whether medical or recreational cannabis dispensaries were open in each state and calendar quarter.
Main Outcome and Measures: One measure of the extensive margins of dispensing and 2 measures of the intensive margins of dispensing were constructed for 5 medication classes (benzodiazepines, antidepressants, antipsychotics, barbiturates, and sleep medications).
Results: The primary sample (the benzodiazepine sample) included 3 848 721 patients (mean [SD] age, 46.1 [11.4] years; 65.4% women; 53.7% aged 35-54 years). Medical cannabis laws were associated with a 12.4% reduction in the benzodiazepine fill rate (average treatment effect on the treated [ATT], –27.4; 95% CI, –14.7 to 12.0; P = .001), recreational cannabis laws were associated with a 15.2% reduction in the fill rate (ATT, −32.5; 95% CI, −24.4 to 20.1; P = .02), and medical cannabis laws were associated with a 1.3% reduction in the mean number of benzodiazepine fills per patient (ATT, –0.02; 95% CI, −0.02 to 0.02; P = .04). Medical dispensaries were associated with a 3.9% reduction in mean days’ supply per benzodiazepine fill (ATT, −1.7; 95% CI, −0.8 to 0.6; P = .001), while recreational dispensaries were associated with a 6.2% reduction (ATT, −2.4; 95% CI, −1.0 to 0.9; P < .001). Medical cannabis laws were associated with a 3.8% increase in antidepressant fills (ATT, 27.2; 95% CI, −33.5 to 26.9; P = .048), and medical dispensaries were associated with an 8.8% increase (ATT, 50.7; 95% CI, −32.3 to 28.4; P = .004). The mean number of antipsychotic medication fills per patient increased by 2.5% (ATT, 0.06; 95% CI, −0.04 to 0.05; P = .02) after medical cannabis laws and by 2.5% (ATT, 0.06; 95% CI, −0.04 to 0.04; P = .02) after medical dispensary openings. Findings for the other drug classes showed substantial heterogeneity by state and direction of association.
Conclusions and Relevance: This cross-sectional study of commercially insured patients suggests that there may have been meaningful heterogeneous associations between cannabis policy and state and between cannabis policy and drug class (eg, decreases in dispensing of benzodiazepines but increases in dispensing of antidepressants and antipsychotics). This finding suggests additional clinical research is needed to understand the association between cannabis use and mental health. The results have implications for patient substance use and mental health–related outcomes.
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Journal: Pharmacology Biochemistry & Behavior, 2024, doi: 10.1016/j.pbb.2024.173836
Authors: Christa Corley, Ashley Craig, Safiyah Sadek, Julie A. Marusich, Samar N. Chehimi, Ashley M. White, … Cassandra D. Gipson
Abstract:
Preclinical models of addictive drugs have been developed for decades to model aspects of the clinical experience in substance use disorders (SUDs). These include passive exposure as well as volitional intake models across addictive drugs and have been utilized to also measure withdrawal symptomatology and potential neurobehavioral mechanisms underlying relapse to drug seeking or taking. There are a number of Food and Drug Administration (FDA)-approved medications for SUDs, however, many demonstrate low clinical efficacy as well as potential sex differences, and we also note gaps in the continuum of care for certain aspects of clinical experiences in individuals who use drugs. In this review, we provide a comprehensive update on both frequently utilized and novel behavioral models of addiction with a focus on translational value to the clinical experience and highlight the need for preclinical research to follow epidemiological trends in drug use patterns to stay abreast of clinical treatment needs. We then note areas in which models could be improved to enhance the medications development pipeline through efforts to enhance translation of preclinical models. Next, we describe neuroscience efforts that can be leveraged to identify novel biological mechanisms to enhance medications development efforts for SUDs, focusing specifically on advances in brain transcriptomics approaches that can provide comprehensive screening and identification of novel targets. Together, the confluence of this review demonstrates the need for careful selection of behavioral models and methodological parameters that better approximate the clinical experience combined with cutting edge neuroscience techniques to advance the medications development pipeline for SUDs.
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Journal: JAMA Network Open, 2024, doi: 10.1001/jamanetworkopen.2024.31594
Authors: Haiden A. Huskamp, Lori Uscher-Pines, Pushpa Raja, Sharon-Lise T. Normand, Ateev Mehrotra, & Alisa B. Busch
Abstract:
Alcohol use disorder (AUD) is the most prevalent substance use disorder (SUD) in the US, affecting 29.5 million people, and deaths from excessive alcohol use are increasing.1,2 While medications for alcohol use disorder (MAUD) are efficacious3 and can be prescribed in primary care or specialty behavioral health settings, only 2.2% of individuals with AUD in 2022 received MAUD in the past year.1 Barriers to MAUD initiation include clinician shortages, cost, stigma and/or privacy concerns, and lack of transportation4; however, telemedicine could reduce some of these barriers.5 We examined telemedicine initiation of MAUD and compared the characteristics of US adults who initiate via telemedicine vs in-person care.
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Journal: Chronic Stress, 2024, doi: 10.1177/24705470241279335
Authors: Grace Hindmarch, Lisa S. Meredith, Colleen M. McCullough, Beth Ann Griffin, & Katherine E. Watkins
Abstract:
Interpersonal violence is a common type of trauma experienced by people with opioid use disorder (OUD), especially for people with co-occurring OUD and mental illness (COD). However, little is known about demographic and clinical characteristics of individuals with COD who have experienced an interpersonal violence traumatic event compared to those who have experienced a non-violent trauma, and how experiences of interpersonal violence are associated with treatment utilization. Data presented are from a randomized clinical trial testing collaborative care for COD in primary care. Of the 797 patients enrolled in the larger study, 733 (92%) were included in this analysis because they reported a traumatic event. In this sample, 301 (41%) participants experienced a traumatic event involving interpersonal violence. Participants who experienced interpersonal violence were more likely to be younger and female. Among the 301 people who experienced interpersonal violence, 30% experienced child sexual abuse, 23% experienced physical violence, 19% experienced domestic violence, and 28% experienced sexual assault. Those who experienced physical violence were significantly less likely to be female (28.6% vs 74.2% to 88.2% in other groups). Those who reported domestic violence had significantly fewer days of drug use (4.1 days vs 9.0 to 11.5 in the other groups) and lower opioid use severity scores (mean = 13.0 vs 16.6 to 19.5 in the other groups). Multivariable regression results examining the associations between interpersonal violence experiences on treatment utilization revealed no statistically significant differences. Rates of receipt were high for medication for opioid use disorder (∼80%) in this sample while rates of mental health counseling were around 35% and rates of receiving mental health medication around 48%. These findings make an important contribution to understanding the associations between patient characteristics and traumatic experiences, and receipt of treatment for OUD and mental health problems among a sample of patients with COD.
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Journal: Journal of Primary Care & Community Health, 2024, doi: 10.1177/21501319241276817
Authors: Benjamin Lai, Jonathan Good, Gagandeep Singh, Meghan Deyo, Rachel Marshall, & Tyler Oesterle
Abstract:
Objective: Fatal overdoses are the third leading cause of death in the pediatric population. Substance use disorders (SUD) screening is not routinely done in primary care practices. Early screening and intervention for adolescent SUD could mitigate future harm.
Methods: We conducted a 3-month pilot adapting universal screening using the CRAFFT tool in patients aged 12 to 17 presenting to an urban and a rural primary care practice during well-child and acute/sick-child visits. We collaborated with our pediatric addiction service to ensure access availability for further assessment and treatment for all positively screened patients; this was broadly communicated to primary care providers.
Results: There was a higher CRAFFT completion rate in the urban site (90%, vs 52.6% in our rural site). The majority of CRAFFT questionnaires were completed during acute/sick-child visits in both study sites. Moreover, we found a higher positive screen rate in our rural practice (14.6%, vs 2.4% in our urban practice). Only 27% of positively screened patients had substance use addressed by their providers. No pediatric addiction referrals were made.
Conclusions: Findings suggest provider-level barriers exist despite having adequate specialty referral sources and institutional encouragement. Future work is needed to explore these barriers.
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