Mitchell Lloyd Doucette

Introduction: Medical cannabis is increasingly used to manage post-traumatic stress disorder (PTSD), a condition frequently linked to high healthcare utilization, particularly for acute services. Methods: We conducted a retrospective cohort study using data from Leafwell among patients with PTSD who either used medical cannabis for at least one year (treated group) or were cannabis-naïve (untreated group). The primary outcomes were urgent care, emergency department (ED), or hospitalization visits in the past six months. We applied inverse probability weighting with regression adjustment (IPWRA) to estimate the average treatment effect (ATE) of medical cannabis exposure, adjusting for demographics, PTSD severity, and other health factors. Sensitivity analyses were performed to assess robustness. Results: Out of 1946 participants, 1261 were in the treated group and 685 in the untreated group. The treated group had a 35.6% lower probability of urgent care visits (coefficient = −0.024, SE = 0.0117) and a 35.1% lower probability of ED visits (coefficient = −0.027, SE = 0.0124). Although hospitalization rates were 26.3% lower, this difference was not statistically significant. Findings remained consistent across multiple ATE estimation methods, and adjusting the IPWRA model’s tolerance levels strengthened these associations. Fewer than 2% of the treated group reported adverse events. Conclusions: Medical cannabis use among patients with PTSD was associated with reduced urgent care and ED visits. These results were robust across analytical methods, supporting the potential role of medical cannabis in lowering acute healthcare needs. Further longitudinal research is warranted to assess causality and clarify effects on hospitalization.

Background Violence interruption programmes are a common type of community violence intervention (CVI), but there is no empirical evidence on programme impacts on youth violence specifically. This study evaluates the effectiveness of Safe Streets, a violence interruption CVI programme in Baltimore, Maryland, in reducing homicides and non-fatal shootings (NFS) among youth ages 15–24. Methods The synthetic control method was used to assess site level and programme level average treatment effects for 11 Safe Streets sites between 2007 and 2023. Models compared smoothed monthly rates of youth homicides and NFS in treated areas with their synthetic controls. Models were estimated using multiple inference approaches, treatment times and control pool eligibility definitions. Results Safe Streets overall was associated with a 42% reduction in youth homicides and a 21% reduction in youth NFS, though neither estimate was statistically significant. Uncensored site-specific models estimate large reductions in youth homicides in five sites and youth NFS in seven sites and large increases in youth homicides in two sites and youth NFS in two sites. No site-specific estimates were statistically significant using primary inference methods. Discussion The rarity of outcomes and sensitivity to modelling decisions warrants cautious interpretation of findings. Differences in programme effectiveness across sites suggest opportunities to strengthen youth engagement in some sites. Changing youth violence dynamics underscore a need to augment and adapt CVI models to match these cultural shifts. Continued work to integrate Safe Streets with other violence prevention approaches, support implementation fidelity and invest in structural change may improve programme outcomes further.

Introduction: Medical cannabis use has expanded rapidly, yet long-term real-world safety data remain limited. We evaluated adverse-event (AE) frequency, severity, and predictors in a US telehealth registry of medical cannabis patients over one year. Methods: We analyzed 14,313 adults who completed intake between June–August 2024. Patients reported any of 30 prespecified adverse events (AEs) and rated each on a 0–10 impact scale. Weekly exposure was estimated as (days/week) × (serving size) and categorized into quintiles. We computed AE rates per 100 patients with binomial 95% confidence intervals (CI) and tested linear trends. Univariate logistic regressions assessed 20 candidate predictors within chronic-pain and anxiety subgroups. We then applied LASSO to select multivariate predictors, combining these with age, sex, race/ethnicity, smoking, and unhealthy-weeks in final logistic models. Marginal predicted-probability curves were generated across exposure, stratified by subgroup, sex, race, and age. Results: Overall, 2.6% of patients reported ≥1 AE. The most common symptoms were increased appetite (23.8%), fatigue (20.3%), and anxiety (19.9%) with mean impact <4/10. In adjusted models, having been to the doctor because of their condition remained the sole AE predictor for patients with anxiety (OR 4.03, 95% CI: 2.44–6.87); age was a significant predictor for patients with chronic pain (OR 0.981, 95% CI: 0.97–0.99). Marginal curves remained flat (∼2–3% AE probability) across weekly cannabis exposure. Ad hoc analysis of non-missing-at-random data suggests possible AE rates are in line with current literature. Discussion: In this large cohort, AEs were infrequent and mild, and weekly cannabis frequency did not independently increase odds. Healthcare engagement likely reflects underlying health complexity driving AE reporting. These findings support the safety of medical cannabis.

Introduction: Chronic pain affects approximately 20% of U.S. adults, imposing significant burdens on individuals and healthcare systems. Medical cannabis has emerged as a potential therapy, yet its impact on healthcare utilization remains unclear. Methods: This retrospective cohort study analyzed administrative data from a telehealth platform providing medical cannabis certifications across 36 U.S. states. Patients were classified as cannabis-exposed if they had used cannabis in the past year, while unexposed patients had no prior cannabis use. Outcomes included self-reported urgent care visits, emergency department (ED) visits, hospitalizations, and quality of life (QoL), measured using the CDC’s Healthy Days measure. Targeted Maximum Likelihood Estimation with SuperLearner estimated causal effects, adjusting for numerous covariates. Results: Medical cannabis users exhibited significantly lower healthcare utilization. Specifically, exposure was associated with a 2.0 percentage point reduction in urgent care visits (95% CI: −0.036, −0.004), a 3.2 percentage point reduction in ED visits (95% CI: −0.051, −0.012) and fewer unhealthy days per month (−3.52 days, 95% CI: −4.28, −2.76). Hospitalization rates trended lower but were not statistically significant. Covariate balance and propensity score overlap indicated well-fitting models. Conclusions: Medical cannabis use was associated with reduced healthcare utilization and improved self-reported QoL among chronic pain patients.

Background: This study examined treatment outcomes for cannabis use disorder (CUD) among adolescents (12–17 years old) in the United States. Methods: Data from the 2018–2021 Treatment Episode Data Set-Discharges (TEDS-D) included 40,054 adolescents diagnosed with CUD. Descriptive statistics, Chi-square tests, and multivariable logistic regression assessed treatment outcomes and factors associated with treatment completion. Results: Only 36.8% of adolescents completed treatment. The most common reasons for not completing treatment were dropping out (28.4%) and transferring to another facility/program (17.0%). Males and Black non-Hispanic adolescents had lower odds of completing treatment (OR = 0.79, 95%CI: 0.75–0.84), while Hispanic (OR = 1.13, 95%CI: 1.08–1.18), Asian (OR = 1.56, 95%CI: 1.3–1.86) and Native Hawaiian/Pacific Islander adolescents (OR = 2.31, 95%CI: 2.04–2.61) had higher odds of completion compared to their White counterparts. Independent living arrangements, homelessness, arrests in the past 30 days and younger age (<15 years old) decreased the likelihood of treatment completion. Adolescents with co-occurring mental health and substance use disorders also had lower completion rates (OR = 0.79, 95%CI: 0.77–0.86). Referral from schools/employers and treatment settings were associated with a higher success, particularly with stays of 4–6 months and 7–12 months. Conclusion: This study highlights the need for targeted CUD treatment programs that support at-risk adolescents, especially those experiencing homelessness or facing legal issues. High dropout and transition rates suggest a need for continuity of care and program integration between facilities. Strengthening coordination among public health officials, community organizations, and stakeholders is essential to developing culturally responsive treatment interventions that address social determinants of health, substance use, and mental health in this vulnerable population.

Introduction: Telehealth has the potential to improve health care access and reduce disparities. We examined whether the density of medical cannabis (MC) patients, stratified by those who were seen by a telemedicine provider or not, is associated with a concentrated disadvantage within Pennsylvania in 2022. Methods: This zip code-level analysis assessed associations between the concentrated disadvantage index (CDI) and counts of telemedicine-approved and all other MC patients. Total MC patient counts were obtained from Pennsylvania's Department of Health, counts of telemedicine-approved MC patients were obtained from a telehealth provider (Leafwell), and CDI data were obtained from the 2022 American Community Survey. Multivariable negative binomial regression models with population offsets and robust standard errors were used, accounting for spatial autocorrelation through spatial lag adjustments. Results: The CDI was not associated with the number of telemedicine-approved MC patients (incidence rate ratios [IRR] = 0.962; p = 0.355) but was significantly negatively associated with all other MC patients (IRR = 0.904; p = <0.001). The number of in-office MC providers was significantly associated with the count of all other MC patients but not with telemedicine-approved patients. Spatial factors significantly influenced the distribution of both patient groups. Discussion: These findings suggest that telemedicine may play a crucial role in reducing access disparities for MC in socioeconomically disadvantaged areas. The lack of a significant association between CDI and telemedicine-approved MC patients indicates that telehealth services can overcome barriers such as provider scarcity and transportation issues. By facilitating remote consultations and approvals, telemedicine expands access for patients who might otherwise be unable to obtain MC.

Introduction: Post-Traumatic Stress Disorder (PTSD) is a debilitating mental health condition commonly treated with medications like benzodiazepines (BZDs), despite their potential for negative long-term side effects. Medical cannabis has emerged as a possible adjunctive therapy for PTSD. However, the relationship between medical cannabis use, relief from PTSD symptoms, and the use of BZDs remains unclear. Thus, we sought to identify predictors of changes to BZD usage among medical cannabis patients with PTSD. Methods: This study utilized survey data from PTSD patients in the Leafwell patient database, collected in the fall of 2023. To assess the relationship between medical cannabis use, PTSD symptom relief, and the discontinuation of BZDs, we employed a multi-step analysis approach. First, we developed a decision tree model to identify key predictors of BZD discontinuation, including prior cannabis use and reported PTSD relief post-medical cannabis treatment initiation. The tree was pruned using the optimal complexity parameter to improve model interpretability. Following this, a secondary logistic regression analysis was performed to confirm the significance of key predictors identified by the decision tree. Results: In the pruned decision tree, not currently receiving psychiatric care for their PTSD was the strongest predictor of BZD discontinuation, followed by self-reported efficacy of medical cannabis in relieving PTSD symptoms, prior cannabis use, and history of traumatic brain injury (TBI) among medical cannabis patients. Age was also a significant factor, with younger individuals more likely to discontinue. Logistic regression analysis supported these findings, with receiving care, TBI, and cannabis use remaining key predictors. Interaction models suggest prior cannabis use moderates the relationship between those not receiving psychiatric care and BZD discontinuation odds. Discussion: These findings suggest that medical cannabis may offer a promising route for BZD discontinuation for long-term users with PTSD symptoms. The association between cannabis use and BZD discontinuation highlights the need for further exploration of cannabis as an adjunctive therapy in PTSD care. More research is necessary to confirm the long-term safety and effectiveness of medical cannabis in this context, ensuring that it can be integrated into care without unintended negative consequences. Individualized care approaches remain crucial given varying patient factors.

Introduction Research on the benefits of medical cannabis (MC) is emerging and supports its use as a treatment for post-traumatic stress disorder (PTSD). This study aimed to evaluate the cost effectiveness of MC as an adjunctive therapy for moderate PTSD under varying reimbursement scenarios. Methods A cost-utility analysis was conducted from the US payor perspective, using pricing data from the largest multi-state MC producer and established literature on standard PTSD treatments. We analyzed eight MC product types: dried flower, oral solutions, tablets, and edibles, each available in low/moderate (LM) and high-cost formulations. Incremental cost-utility ratios (ICURs) were calculated for these products across reimbursement levels of 100%, 75%, 50%, and 25%. Probabilistic sensitivity analyses with 10,000 Monte Carlo simulations were conducted to assess cost-effectiveness acceptability across willingness-to-pay (WTP) thresholds of $0–$100,000 per quality-adjusted life year (QALY) gained. Results Non-flower MC products (edibles, oral solutions, and tablets) consistently demonstrated cost-effectiveness under a WTP threshold of $50,000, even at 100% reimbursement. Dried flower products, while less cost effective due to higher costs, achieved cost effectiveness under 75% or lower reimbursement levels for LM cost formulations. Sensitivity analyses confirmed robust ICURs for non-flower products, with narrower variability compared to dried flower products. Conclusions Medical cannabis products, particularly non-flower formulations, represent a cost-effective adjunctive therapy for moderate PTSD under various reimbursement scenarios. This analysis underscores the importance of evidence-based reimbursement policies to improve patient access to cost-effective treatments while ensuring financial sustainability for payors.

Introduction: Telemedicine has the potential to improve healthcare access and reduce disparities. We examined whether the incidence rate of medical cannabis patients (MC) was associated with concentrated disadvantage in Pennsylvania in 2022, accounting for a population of patients approved through telemedicine. Methods: This zip code-level analysis examined associations between the Concentrated Disadvantage Index (CDI) and two outcomes: (1) the number of telemedicine-approved MC patients, as obtained from a specific telemedicine provider, and (2) the number of all other MC patients, calculated by subtracting the number of telemedicine-approved patients from the total number of MC patients at the zip code-level. Total counts of MC patients and in-office MC providers for Pennsylvania were sourced from the Pennsylvania Department of Health, while CDI data were derived from the 2022 American Community Survey. We used multivariate negative binomial regression models with population offsets and robust standard errors, adjusting for spatial autocorrelation through spatial lag adjustments. Results: The CDI was not associated with the incidence rate of telemedicine-approved MC patients (IRR = 0.962; p = 0.355), but it was significantly negatively associated with the incidence rate of all other MC patients (IRR = 0.904; p = 0.000). The density of in-office MC providers was significantly associated with the incidence rate of all other MC patients but not with telemedicine-approved patients. Spatial factors, including autocorrelation, significantly influenced the distribution of both groups of patients. Discussion: These findings suggest that telemedicine plays a crucial role in improving access to MC for socioeconomically disadvantaged areas. The lack of a significant association between the CDI and telemedicine-approved MC patients highlights the ability of telemedicine to bypass barriers such as provider scarcity and transportation challenges. By facilitating remote consultations and approvals, telemedicine ensures access for patients who might otherwise face difficulties obtaining MC.

Introduction: Medical cannabis is increasingly used as a therapy for managing post-traumatic stress disorder (PTSD). Patients with PTSD often have high healthcare utilization rates, particularly for acute services. This study examines the association between medical cannabis treatment and healthcare utilization among patients with PTSD. Methods: We conducted a retrospective cohort study using cross-sectional data with tem-poral elements, derived from administrative records provided by Leafwell, among patients with PTSD. The cohort was defined based on medical cannabis use: the treated group included patients who had used medical cannabis for at least one year (returning for medical card renewal), while the untreated group consisted of cannabis-naive patients reporting no prior cannabis use. The primary outcomes were healthcare utilization within the past six months, including at least one urgent care visit, emergency department (ED) visit, or hospitalization related to their primary medical condition. We used inverse probability weighting with regression adjustment (IPWRA) to estimate the average treatment effect (ATE) of medical cannabis use on healthcare utilization, controlling for key demographics and health factors, including PTSD severity. Sensitivity analyses were conducted to assess the robustness of our findings. Results: Among the 1,946 participants, the treated group (n = 1,261) had significantly lower healthcare utilization rates compared to the untreated group (n = 685). Using the doubly robust IPWRA model, medical cannabis treatment was associated with a significant 35.6% reduction in urgent care visits (coefficient = -0.024, Standard Error (SE) = 0.0117) and a 35.1% reduction in ED visits (coefficient = -0.027, SE = 0.0124). Hospitalization rates were 26.3% lower among the treated group but did not reach statistical significance. Sensitivity analyses utilizing alternative ATE estimation strategies displayed consistent reductions in urgent care and ED visits among cannabis users, though hospitalizations remained non-significant. Adjusting the IPWRA model’s tolerance levels strengthened the found associations while maintaining strong covariate balance. Fewer than 2% of the treated group reported an adverse event. Discussion: These findings suggest that medical cannabis treatment among patients with PTSD may be associated with reduced utilization of urgent care and ED services. This relationship remains robust across multiple statistical models and sensitivity analyses, underscoring the potential role of medical cannabis in reducing acute healthcare needs in this population. Further longitudinal research is warranted to explore causality and assess its impact on hospitalization rates.