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Background: The COVID-19 pandemic's impact on utilization of medications for opioid use disorder (MOUD) among patients with opioid use disorder (OUD) and chronic pain is unclear., Methods: We analyzed New York State (NYS) Medicaid claims from pre-pandemic (August 2019-February 2020) and pandemic (March 2020-December 2020) periods for beneficiaries with and without chronic pain. We calculated monthly proportions of patients with OUD diagnoses in 6-month-lookback windows utilizing MOUD and proportions of treatment-naïve patients initiating MOUD. We used interrupted time series to assess changes in MOUD utilization and initiation rates by medication type and by race/ethnicity., Results: Among 20,785 patients with OUD and chronic pain, 49.3% utilized MOUD (versus 60.3% without chronic pain). The pandemic did not affect utilization in either group but briefly disrupted initiation among patients with chronic pain (β=-0.009; 95% CI [-0.015, -0.002]). Overall MOUD utilization was not affected by the pandemic for any race/ethnicity but opioid treatment program (OTP) utilization was briefly disrupted for non-Hispanic Black individuals (β=-0.007 [-0.013, -0.001]). The pandemic disrupted overall MOUD initiation in non-Hispanic Black (β=-0.007 [-0.012, -0.002]) and Hispanic individuals (β=-0.010 [-0.019, -0.001])., Conclusions: Adults with chronic pain who were enrolled in NYS Medicaid before the COVID-19 pandemic had lower MOUD utilization than those without chronic pain. MOUD initiation was briefly disrupted, with disparities especially in racial/ethnic minority groups. Flexible MOUD policy initiatives may have maintained overall treatment utilization, but disparities in initiation and care continuity remain for patients with chronic pain, and particularly for racial/ethnic minoritized subgroups., Competing Interests: Declaration of Competing Interest The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the New York State Department of Health. Examples of analysis performed within this article are only examples. They should not be utilized in real-world analytic products. AP reports no conflicts of interest. KWM reports no conflicts of interest. DSH reports payments made to their institution for unrelated project work for Syneos Health on measurement of addiction in patients with chronic pain. KT reports no conflicts of interest. ZLM reports no conflicts of interest. VJ reports no conflicts of interest. TNT reports no conflicts of interest. JRP reports no conflicts of interest. SC reports no conflicts of interest. SSM reports no conflicts of interest. MC reports no conflicts of interest. NK receives compensation for expert testimony in ongoing opioid litigation., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Naloxone distribution is central to ongoing efforts to address the opioid overdose crisis. Some critics contend that naloxone expansion may inadvertently promote high-risk substance use behaviors among adolescents, but this question has not been directly investigated., Methods: We examined relationships between naloxone access laws and pharmacy naloxone distribution with lifetime heroin and injection drug use (IDU), 2007-2019. Models generating adjusted odds ratios (aOR) and 95% confidence intervals (CI) included year and state fixed effects, controlled for demographics and sources of variation in opioid environments (e.g., fentanyl penetration), as well as additional policies expected to impact substance use (e.g., prescription drug monitoring). Exploratory and sensitivity analyses further examined naloxone law provisions (e.g., third-party prescribing) and applied e-value testing to assess vulnerability to unmeasured confounding., Results: Adoption of any naloxone law was not associated with changes in adolescent lifetime heroin or IDU. For pharmacy dispensing, we observed a small decrease in heroin use (aOR: 0.95 [CI: 0.92, 0.99]) and a small increase in IDU (aOR: 1.07 [CI: 1.02, 1.11]). Exploratory analyses of law provisions suggested that third-party prescribing (aOR: 0.80, [CI: 0.66, 0.96]) and non-patient-specific dispensing models (aOR: 0.78, [CI: 0.61, 0.99]) were associated with decreased heroin use but not decreased IDU. Small e-values associated with the pharmacy dispensing and provision estimates indicate that unmeasured confounding may explain observed findings., Conclusion: Naloxone access laws and pharmacy naloxone distribution were more consistently associated with decreases rather than increases in lifetime heroin and IDU among adolescents. Our findings therefore do not support concerns that naloxone access promotes high-risk adolescent substance use behaviors. As of 2019, all US states have adopted legislation to improve naloxone access and facilitate use. However, further removal of adolescent naloxone access barriers is an important priority given that the opioid epidemic continues to affect people of all ages., Competing Interests: Declarations of Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: D. Hasin has received funding from Syneos Health for an unrelated project. K. Keyes has received personal fees related to expert work in litigation. H. Samples has received consulting fees from the American Society of Addiction Medicine., (Copyright © 2023. Published by Elsevier B.V.)

Background: States have enacted multiple types of laws, with a variety of constituent provisions, in response to the opioid epidemic, often simultaneously. This temporal proximity and variation in state-to-state operationalization has resulted in significant challenges for empirical research on their effects. Thus, expert consensus can be helpful to classify laws and their provisions by their degree of helpfulness and impact., Methods: We conducted a four-stage modified policy Delphi process to identify the top 10 most helpful and 5 most harmful provisions from eight opioid-related laws. This iterative consultation with six types of opioid experts included a preliminary focus group (n=12), two consecutive surveys (n=56 and n=40, respectively), and a final focus group feedback session (n=5)., Results: On a scale of very harmful (0) to very helpful (4), overdose Good Samaritan laws received the highest average helpfulness rating (3.62, 95% CI: 3.48-3.75), followed by naloxone access laws (3.37, 95% CI: 3.22-3.51), and pain management clinic laws (3.08, 95% CI: 2.89-3.26). Drug-induced homicide (DIH) laws were rated the most harmful (0.88, 95% CI: 0.66-1.11). Impact ratings aligned similarly, although Medicaid laws received the second highest overall impact rating (3.71, 95% CI: 3.45, 3.97). The two most helpful provisions were naloxone standing orders (3.94, 95% CI: 3.86-4.02) and Medicaid coverage of medications for opioid use disorder (MOUD) (3.89, 95% CI: 3.82). Mandatory minimum DIH laws were the most harmful provision (0.73, 95% CI 0.53-0.93); followed by requiring prior authorization for Medicaid coverage of MOUD (1.00 95% CI: 0.72-1.27)., Conclusion: Overall, experts rated laws and provisions that facilitated harm reduction efforts and access to MOUD as most helpful. Laws and provisions rated as most harmful criminalized substance use and placed restrictions on access to MOUD. These ratings provide a foundation for evaluating the overall overdose policy environment for each state., Competing Interests: Declarations of Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Samples has received consulting fees from the American Society of Addiction Medicine., (Copyright © 2022. Published by Elsevier B.V.)

This report presents a new implementation of the Besag-York-Mollié (BYM) model in Stan, a probabilistic programming platform which does full Bayesian inference using Hamiltonian Monte Carlo (HMC). We review the spatial auto-correlation models used for areal data and disease risk mapping, and describe the corresponding Stan implementations. We also present a case study using Stan to fit a BYM model for motor vehicle crashes injuring school-age pedestrians in New York City from 2005 to 2014 localized to census tracts. Stan efficiently fit our multivariable BYM model having a large number of observations (n=2095 census tracts) with small outcome counts < 10 in the majority of tracts. Our findings reinforced that neighborhood income and social fragmentation are significant correlates of school-age pedestrian injuries. We also observed that nationally-available census tract estimates of commuting methods may serve as a useful indicator of underlying pedestrian densities., (Copyright © 2019 Elsevier Ltd. All rights reserved.)