Return to drug use and overdose after release from prison: a qualitative study of risk and protective factors

BACKGROUND: Former inmates are at high risk for death from drug overdose, especially in the immediate post-release period. The purpose of the study is to understand the drug use experiences, perceptions of overdose risk, and experiences with overdose among former prisoners. METHODS: This qualitative study included former prison inmates (N = 29) who were recruited within two months after their release. Interviewers conducted in-person, semi-structured interviews which explored participants' experiences and perceptions. Transcripts were analyzed utilizing a team-based method of inductive analysis. RESULTS: The following themes emerged: 1) Relapse to drugs and alcohol occurred in a context of poor social support, medical co-morbidity and inadequate economic resources; 2) former inmates experienced ubiquitous exposure to drugs in their living environments; 3) intentional overdose was considered "a way out" given situational stressors, and accidental overdose was perceived as related to decreased tolerance; and 4) protective factors included structured drug treatment programs, spirituality/religion, community-based resources (including self-help groups), and family. CONCLUSIONS: Former inmates return to environments that strongly trigger relapse to drug use and put them at risk for overdose. Interventions to prevent overdose after release from prison may benefit from including structured treatment with gradual transition to the community, enhanced protective factors, and reductions of environmental triggers to use drugs

Prevalence Rates of Mental Disorders in Chilean Prisons

PMCID: PMC371883

Estimated Drug Overdose Deaths Averted by North America's First Medically-Supervised Safer Injection Facility

Illicit drug overdose remains a leading cause of premature mortality in urban settings worldwide. We sought to estimate the number of deaths potentially averted by the implementation of a medically supervised safer injection facility (SIF) in Vancouver, Canada.The number of potentially averted deaths was calculated using an estimate of the local ratio of non-fatal to fatal overdoses. Inputs were derived from counts of overdose deaths by the British Columbia Vital Statistics Agency and non-fatal overdose rates from published estimates. Potentially-fatal overdoses were defined as events within the SIF that required the provision of naloxone, a 911 call or an ambulance. Point estimates and 95% Confidence Intervals (95% CI) were calculated using a Monte Carlo simulation. Between March 1, 2004 and July 1, 2008 there were 1004 overdose events in the SIF of which 453 events matched our definition of potentially fatal. In 2004, 2005 and 2006 there were 32, 37 and 38 drug-induced deaths in the SIF's neighbourhood. Owing to the wide range of non-fatal overdose rates reported in the literature (between 5% and 30% per year) we performed sensitivity analyses using non-fatal overdose rates of 50, 200 and 300 per 1,000 person years. Using these model inputs, the number of averted deaths were, respectively: 50.9 (95% CI: 23.6–78.1); 12.6 (95% CI: 9.6–15.7); 8.4 (95% CI: 6.5–10.4) during the study period, equal to 1.9 to 11.7 averted deaths per annum.Based on a conservative estimate of the local ratio of non-fatal to fatal overdoses, the potentially fatal overdoses in the SIF during the study period could have resulted in between 8 and 51 deaths had they occurred outside the facility, or from 6% to 37% of the total overdose mortality burden in the neighborhood during the study period. These data should inform the ongoing debates over the future of the pilot project

Development and implementation of a prescription opioid registry across diverse health systems

Objective: Develop and implement a prescription opioid registry in 10 diverse health systems across the US and describe trends in prescribed opioids between 2012 and 2018. Materials and Methods: Using electronic health record and claims data, we identified patients who had an outpatient fill for any prescription opioid, and/or an opioid use disorder diagnosis, between January 1, 2012 and December 31, 2018. The registry contains distributed files of prescription opioids, benzodiazepines and other select medications, opioid antagonists, clinical diagnoses, procedures, health services utilization, and health plan membership. Rates of outpatient opioid fills over the study period, standardized to health system demographic distributions, are described by age, gender, and race/ethnicity among members without cancer. Results: The registry includes 6 249 710 patients and over 40 million outpatient opioid fills. For the combined registry population, opioid fills declined from a high of 0.718 per member-year in 2013 to 0.478 in 2018, and morphine milligram equivalents (MMEs) per fill declined from 985 MMEs per fill in 2012 to 758 MMEs in 2018. MMEs per member declined from 692 MMEs per member in 2012 to 362 MMEs per member in 2018. Conclusion: This study established a population-based opioid registry across 10 diverse health systems that can be used to address questions related to opioid use. Initial analyses showed large reductions in overall opioid use per member among the combined health systems. The registry will be used in future studies to answer a broad range of other critical public health issues relating to prescription opioid use

Liberalizing trade in environmental goods and services

We examine the effects of trade liberalization in environmental goods in a model with one domestic downstream polluting firm and two upstream firms (one domestic, one foreign). The upstream firms offer their technologies to the downstream firm at a flat fee. The domestic government sets the emission tax rate after the outcome of R&D is known. The effect of liberalization on the domestic upstream firm's R&D incentive is ambiguous. Liberalization usually results in cleaner production, which allows the country to reach higher welfare. However this increase in welfare is typically achieved at the expense of the environment (a backfire effect)

Receipt of medications for opioid use disorder among youth engaged in primary care: data from 6 health systems

PURPOSE: Little is known about prevalence and treatment of OUD among youth engaged in primary care (PC). Medications are the recommended treatment of opioid use disorder (OUD) for adolescents and young adults (youth). This study describes the prevalence of OUD, the prevalence of medication treatment for OUD, and patient characteristics associated with OUD treatment among youth engaged in PC. METHODS: This cross-sectional study includes youth aged 16-25 years engaged in PC. Eligible patients had ≥ 1 PC visit during fiscal years (FY) 2014-2016 in one of 6 health systems across 6 states. Data from electronic health records and insurance claims were used to identify OUD diagnoses, office-based OUD medication treatment, and patient demographic and clinical characteristics in the FY of the first PC visit during the study period. Descriptive analyses were conducted in all youth, and stratified by age (16-17, 18-21, 22-25 years). RESULTS: Among 303,262 eligible youth, 2131 (0.7%) had a documented OUD diagnosis. The prevalence of OUD increased by ascending age groups. About half of youth with OUD had documented depression or anxiety and one third had co-occurring substance use disorders. Receipt of medication for OUD was lowest among youth 16-17 years old (14%) and highest among those aged 22-25 (39%). CONCLUSIONS: In this study of youth engaged in 6 health systems across 6 states, there was low receipt of medication treatment, and high prevalence of other substance use disorders and mental health disorders. These findings indicate an urgent need to increase medication treatment for OUD and to integrate treatment for other substance use and mental health disorders

Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models