Using decision tree models and comprehensive statewide data to predict opioid overdoses following prison release.

PURPOSE: Identifying predictors of opioid overdose following release from prison is critical for opioid overdose prevention. METHODS: We leveraged an individually linked, state-wide database from 2015-2020 to predict the risk of opioid overdose within 90 days of release from Massachusetts state prisons. We developed two decision tree modeling schemes: a model fit on all individuals with a single weight for those that experienced an opioid overdose and models stratified by race/ethnicity. We compared the performance of each model using several performance measures and identified factors that were most predictive of opioid overdose within racial/ethnic groups and across models. RESULTS: We found that out of 44,246 prison releases in Massachusetts between 2015-2020, 2237 (5.1%) resulted in opioid overdose in the 90 days following release. The performance of the two predictive models varied. The single weight model had high sensitivity (79%) and low specificity (56%) for predicting opioid overdose and was more sensitive for White non-Hispanic individuals (sensitivity = 84%) than for racial/ethnic minority individuals. CONCLUSIONS: Stratified models had better balanced performance metrics for both White non-Hispanic and racial/ethnic minority groups and identified different predictors of overdose between racial/ethnic groups. Across racial/ethnic groups and models, involuntary commitment (involuntary treatment for alcohol/substance use disorder) was an important predictor of opioid overdose.

Architecture and Development Framework for a Web-Based Risk Assessment and Management Platform Developed on WordPress to Address Opioid Overdose.

The number of overdose-related fatalities continues to reach historic levels across Canada, despite ongoing efforts by authorities. To reduce mortality, a clinical trajectory ranging from preventative measures to crisis intervention, skill training to treatment, and risk assessment to risk management needs to be supported. The web-based Risk Assessment and Management Platform (RAMP) was developed to realize this concept and to empower people who use drugs through an integrated tool that allows them to better understand and manage their risk of overdose. This paper outlines the architecture and development of RAMP, which is built on the WordPress platform. WordPress components are mapped onto a 3-tier architecture that consists of presentation, application, and database layers. The architecture facilitates the development of a modular software that includes several features that are independent in functionality but interact with each other in an integrated platform. The relatively low coupling and high coherence of the features may reduce the cost of maintenance and increase flexibility of future developments. RAMP's architecture comprises a user interface, conceptual framework, and backend layers. The RAMP front end effectively uses some of the WordPress' features such as HTML5, CSS, and JavaScript to create a mobile, friendly, and scalable user interface. The RAMP backend uses several standard and custom WordPress plug-ins to support risk assessment and monitoring, with the goal of mitigating the impacts and eliminating risks together. A rule-based decision support system has been hard-coded to suggest relevant modules and goals to complement each user's lifestyle and goals based on their risk assessment. Finally, the backend uses the MySQL database management system and communicates with the RAMP framework layer via the data access layer to facilitate a timely and secure handling of information. Overall, RAMP is a modular system developed to identify and manage the risk of opioid overdose in the population of people who use drugs. Its modular design uses the WordPress architecture to efficiently communicate between layers and provide a base for external plug-ins. There is potential for the current system to adopt and address other related fields such as suicide, anxiety, and trauma. Broader implementation will support this concept and lead to the next level of functionality.

Examining the association of rurality with opioid-related morbidity and mortality in Georgia: A geospatial analysis.

INTRODUCTION: The US opioid epidemic continues to escalate, with overdose deaths being the most-used metric to quantify its burden. There is significant geographic variation in opioid-related outcomes. Rural areas experience unique challenges, yet many studies oversimplify rurality characterizations. Contextual factors, such as area deprivation, are also important to consider when understanding a community's need for treatment services and prevention programming. This study aims to provide a geospatial snapshot of the opioid epidemic in Georgia using several metrics of opioid-related morbidity and mortality and explore differences by rurality across counties. METHODS: This was a spatial ecologic study. Negative binominal regression was used to model the relationship of county rurality with four opioid-related outcomes - overdose mortality, emergency department visits, inpatient hospitalizations, and overdose reversals - adjusting for county-level sex, racial/ethnic, and age distributions. Area Deprivation Index was also included. RESULTS: There was significant geographic variation across the state for all four opioid-related outcomes. Counts remained highest among the metro areas. For rates, counties in the top quartile of rates varied by outcome and were often rural areas. In the final models, rurality designation was largely unrelated to opioid outcomes, with the exception of medium metro areas (inversely related to hospitalizations and overdose reversals) and non-core areas (inversely related to hospitalizations), as compared to large central metro areas. Higher deprivation was significantly related to increased ED visits and hospitalizations, but not overdose mortality and reversals. CONCLUSIONS: When quantifying the burden of the opioid epidemic in a community, it is essential to consider multiple outcomes of morbidity and mortality. Understanding what outcomes are problematic for specific communities, in combination with their demographic and socioeconomic context, can provide insight into gaps in the treatment continuum and potential areas for intervention. Additionally, compared to demographic and socioeconomic factors, rurality may no longer be a salient predictor of the severity of the opioid epidemic in an area.

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors.

PURPOSE: To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type. METHODS: This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type. RESULTS: Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI 1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant. CONCLUSIONS: Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

"Naloxone? Not for me!" First cross-assessment by patients and healthcare professionals of the risk of opioid overdose.

BACKGROUND: Opioid-related mortality is a rising public health concern in France, where opioids were in 2021 implicated in 75% of overdose deaths. Opioid substitution treatment (OST) was implicated in almost half of deaths related to substance and drug abuse. Although naloxone could prevent 80% of these deaths, there are a number of barriers to the distribution of take-home naloxone (THN) among opioid users in France. This study is the first one which compares patients' self-assessment of the risk of future opioid overdose with the hetero-assessment provided by healthcare professionals in a population of individuals eligible for naloxone. METHODS: This was a multicenter descriptive observational study carried out in pharmacies across the Pays de la Loire region (France) during April and May 2022. All adult patients who visited a participating pharmacy for a prescription of OST and provided oral informed consent were enrolled in the study. Retrospective data were collected through cross-sectional interviews conducted by the pharmacist with the patient, utilizing an ad hoc questionnaire. The patient's self-assessment of overdose risk was evaluated using a Likert scale from 0 to 10. The pharmacist relied on the presence or absence of overdose risk situations defined by the French Health Authority (HAS). The need to hold THN was assessed using a composite criterion. RESULTS: A total of 34 patients were interviewed; near one third were aware of the existence of THN and a minority had THN in their possession. Out of the 34 participants, 29 assessed their own risk of future opioid overdose: 65.5% reported having zero risk, while 6.9% believed they had a high risk. Nevertheless, at least one risk situation of opioid overdose was identified according to HAS criteria in 73.5% of the participants (n = 25). Consequently, 55% of the participants underestimated their risk of experiencing a future opioid overdose. Yet, dispensing THN has been judged necessary for 88.2% of the participants. CONCLUSION: This study underscored the imperative need to inform not only healthcare professionals but also the patients and users themselves on the availability of THN and the risk situations of opioid overdose.