Opioid Overdose Research Articles

Payment-related barriers to medications for opioid use disorder: A critical review of the literature and real-world application

BackgroundThe national opioid crisis continues to intensify, despite the fact that opioid use disorder (OUD) is treatable and opioid overdose deaths are preventable through first-line treatment with medications for opioid use disorder (MOUD). This study identifies and categorizes payment-related barriers that impact MOUD access and retention from both the provider and patient perspectives and provides insight into how these barriers can be addressed. MethodsWe performed a critical review of the literature (peer-reviewed studies and relevant documents from the gray literature) to identify payment-related access and retention barriers to MOUD. We used the results of this review to develop an analytic framework to understand how payment impacts MOUD access and retention for both providers and patients. In addition, we reviewed action plans developed by Massachusetts communities that participated in the Healing Communities Study (HCS) to analyze which payment-related barriers were addressed through the study. ResultsWe identified 18 payment-related barriers that patients or providers face when initiating or continuing MOUD with either methadone or buprenorphine in Opioid Treatment Programs (OTP) and non-OTP settings. Patient-related barriers mainly relate to health insurance coverage or the design of health plans (e.g., cost sharing, covered benefits) resulting in direct (medical and non-medical) and indirect costs that can affect both access and retention, especially as they relate to services provided in OTPs. Provider-related barriers include low reimbursement and administrative burden and are most likely to impact access to MOUD. Evidence-based strategies to expand MOUD as part of the HCS in Massachusetts targeted about half of the patient and provider payment-related barriers identified. ConclusionPatients and providers face an array of payment-related barriers that impact access to and retention on MOUD, most of which relate to inadequate health insurance coverage, features of health plans, and key federal and state policies. As new regulatory policies are enacted that expand access to MOUD, such as greater flexibility in OTPs and MOUD delivered via telehealth, it will be important to align these delivery changes with payment reform involving payers, providers, and policymakers.

Development and validation of machine-learning algorithms predicting retention, overdoses, and all-cause mortality among US military veterans treated with buprenorphine for opioid use disorder

Background Buprenorphine for opioid use disorder (B-MOUD) is essential to improving patient outcomes; however, retention is essential. Objective To develop and validate machine-learning algorithms predicting retention, overdoses, and all-cause mortality among US military veterans initiating B-MOUD. Methods Veterans initiating B-MOUD from fiscal years 2006-2020 were identified. Veterans’ B-MOUD episodes were randomly divided into training (80%;n = 45,238) and testing samples (20%;n = 11,309). Candidate algorithms [multiple logistic regression, least absolute shrinkage and selection operator regression, random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN)] were used to build and validate classification models to predict six binary outcomes: 1) B-MOUD retention, 2) any overdose, 3) opioid-related overdose, 4) overdose death, 5) opioid overdose death, and 6) all-cause mortality. Model performance was assessed using standard classification statistics [e.g., area under the receiver operating characteristic curve (AUC-ROC)]. Results Episodes in the training sample were 93.0% male, 78.0% White, 72.3% unemployed, and 48.3% had a concurrent drug use disorder. The GBM model slightly outperformed others in predicting B-MOUD retention (AUC-ROC = 0.72). RF models outperformed others in predicting any overdose (AUC-ROC = 0.77) and opioid overdose (AUC-ROC = 0.77). RF and GBM outperformed other models for overdose death (AUC-ROC = 0.74 for both), and RF and DNN outperformed other models for opioid overdose death (RF AUC-ROC = 0.79; DNN AUC-ROC = 0.78). RF and GBM also outperformed other models for all-cause mortality (AUC-ROC = 0.76 for both). No single predictor accounted for >3% of the model’s variance. Conclusions Machine-learning algorithms can accurately predict OUD-related outcomes with moderate predictive performance; however, prediction of these outcomes is driven by many characteristics.

Iontophoresis-coupled rapidly dissolving polymeric microneedle patch of naloxone for its enhanced transdermal delivery

The transdermal delivery of naloxone for opioid overdose emergency purposes is a challenge due to its poor rate of diffusion through the layers of skin. This results in delayed delivery of an insufficient amount of the drug within minimal time as is desired to save lives. The ability of dissolving polymeric microneedles to shorten the lag time significantly has been explored and shown to have prospects in terms of the transdermal delivery of naloxone. This is an option that offers critical advantages to the ongoing opioid crisis, including ease of distribution and easy administration, with little to no need for intervention by clinicians. Nonetheless, this approach by itself needs augmentation to meet pharmacokinetic delivery attributes desired for a viable clinical alternative to existing market dosage forms. In this study, we report the success of an optimized iontophoresis-coupled naloxone loaded dissolving microneedle patch which had facilitated a 12- fold increase in average cumulative permeation and a 6-fold increase in drug flux over a conventional dissolving microneedle patch within 60 min of application (p < 0.05). This translates to a 30 % decrease in dose requirement in a mechanistically predicted microneedle patch established to be able to achieve the desired early plasma concentration time profile needed in an opioid overdose emergency. Applying a predictive mathematical model, we describe an iontophoresis-coupled microneedle patch design capable of meeting the desired pharmacokinetic profile for a viable naloxone delivery form through skin.

Overdose responses among rural people who use drugs: A multi-regional qualitative study

BackgroundEfforts to distribute naloxone have equipped more people with the ability to reverse opioid overdoses but people who use drugs are often reluctant to call 911 due to concerns for legal repercussions. Rural communities face unique challenges in reducing overdose deaths compared to urban communities, including limited access to harm reduction services as well as greater concerns about stigma and privacy.MethodsThe Rural Opioid Initiative was funded in 2017 to better understand the health-related harms associated with the opioid crisis in rural US communities and consists of eight studies spanning ten states and 65 counties. Each study conducted semi-structured qualitative interviews with people who use drugs to understand contextual factors influencing drug use and health behaviors. We analyzed qualitative data from seven studies with data available at the time of analysis to understand peer response to overdose.ResultsOf the 304 participants interviewed, 55% were men, 70% were white, 80% reported current injection drug use, and 60% reported methamphetamine use. Similar to what has been found in studies focused on urban settings, people who use drugs in rural communities use a range of strategies to reverse overdoses, including non-evidence-based approaches. Several reported that multiple doses of naloxone are needed to reverse overdose. Three themes emerged around the willingness to call 911, including (1) hesitancy to call 911 for fear of legal consequences, (2) negative perceptions or experiences with law enforcement officers, and (3) efforts to obtain medical intervention while avoiding identification/law enforcement involvement.ConclusionPeople who use drugs employ multiple strategies to attempt overdose reversal, including non-evidence-based approaches. Greater education about the most effective and least harmful strategies is needed. Reluctance to call 911 is rooted in concerns about potential legal consequences as well as perceptions about law enforcement officers, which may be heightened in rural communities where people who use drugs are more easily identified by law enforcement. People who use drugs will go to great strides to connect their peers to needed medical services, suggesting that comprehensive interventions to reduce interactions with law enforcement officers and eliminate legal consequences for reporting overdoses are critical.

Disparities in the accuracy of reporting opioid overdoses to 9-1-1 by race and sex of overdose victim, Marion County, Indiana, 2011–2020

ObjectivesTo assess the prevalence of emergency medical incidents wherein naloxone was administered but overdose was not described as the chief complaint during the 9-1-1 call, including differences by overdose victim race/ethnicity and sex.MethodsWe computed the percentage of 9-1-1 calls in Marion County, Indiana, from 2011 to 2020, wherein naloxone was administered but the caller did not describe overdose as the chief complaint. We estimated a logistic regression to examine the associations between reporting of overdose as the chief complaint and race and sex of the overdose victim.ResultsAlmost one-fifth of 9-1-1 calls preceding naloxone administration did not describe overdose as the chief complaint. 9-1-1 callers were more likely to describe a non-overdose as the chief complaint when the overdose victim was Black or female.Conclusion9-1-1 callers are less likely to use terminology describing overdose when the overdose victim is female or Black, than when the victim is male or White. Inaccurate terminology when calling 9-1-1 could delay naloxone administration, thereby increasing risk of overdose death and hypoxic brain injury. Some 9-1-1 callers may be avoiding overdose terminology to prevent a police response, or due to lack of knowledge about overdose identification, but further research is needed to determine the mechanisms underlying these findings.

Evaluation of Strategies to Enhance Community-Based Naloxone Distribution Supported by an Opioid Settlement

Many US states are substantially increasing community-based naloxone distribution, supported in part through settlements from opioid manufacturers and distributors. To evaluate the potential impact of increased naloxone availability on opioid overdose deaths (OODs) and explore strategies to enhance this impact by integrating interventions to address solitary drug use. This decision analytical modeling study used PROFOUND (Prevention and Rescue of Fentanyl and Other Opioid Overdoses Using Optimized Naloxone Distribution Strategies), a previously published simulation model, to forecast annual OODs between January 2023 and December 2025. The simulated study population included individuals from Rhode Island who misused opioids and stimulants and were at risk for opioid overdose. The study modeled expanded naloxone distribution supported by the state's opioid settlement (50 000 naloxone nasal spray kits each year). Two approaches to expanding naloxone distribution were evaluated: one based on historical spatial patterns of naloxone distribution (supply-based approach) and one based on the spatial distribution of individuals at risk (demand-based approach). In addition, hypothetical interventions to enhance the likelihood of witnessed overdoses in private or semiprivate settings were considered. Annual number of OODs and ratio of fatal to nonfatal opioid overdoses. Modeling results indicated that distributing more naloxone supported by the state's opioid settlement could reduce OODs by 6.3% (95% simulation interval [SI], 0.3%-13.7%) and 8.8% (95% SI, 1.8%-17.5%) in 2025 with the supply-based and demand-based approaches, respectively. However, increasing witnessed overdoses by 20% to 60% demonstrated greater potential for reducing OODs, ranging from 8.5% (95% SI, 0.0%-20.3%) to 24.1% (95% SI, 8.6%-39.3%). Notably, synergistic associations were observed when combining both interventions: increased naloxone distribution with the 2 approaches and a 60% increase in witnessed overdoses could reduce OODs in 2025 by 33.5% (95% SI, 17.1%-50.4%) and 37.4% (95% SI, 19.6%-56.3%), respectively. These findings suggest that interventions to address solitary drug use are needed to maximize the impact of continued efforts to increase community-based naloxone distribution, which may be particularly important for jurisdictions that have strong community-based naloxone distribution programs.

Identification of factors associated with opioid-related and hepatitis C virus-related hospitalisations at the ZIP code area level in the USA: an ecological and modelling study

Opioid overdose and related diseases remain a growing public health crisis in the USA. Identifying sociostructural and other contextual factors associated with adverse health outcomes is needed to improve prediction models to inform policy and interventions. We aimed to identify high-risk communities for targeted delivery of screening and prevention interventions for opioid use disorder and hepatitis C virus (HCV). In this ecological and modelling study, we fit mixed-effects negative binomial regression models to identify factors associated with, and predict, opioid-related and HCV-related hospitalisations for ZIP code tabulation areas (ZCTAs) in South Carolina, USA. All individuals aged 18 years or older living in South Carolina from Jan 1, 2016, to Dec 31, 2021, were included. Data on opioid-related and HCV-related hospitalisations, as well as data on additional individual-level variables, were collected from medical claims records, which were obtained from the South Carolina Revenue and Fiscal Affairs Office. Demographic and socioeconomic variables were obtained from the United States Census Bureau (American Community Survey, 2021) with additional structural health-care barrier data obtained from South Carolina's Center for Rural and Primary Health Care, and the American Hospital Directory. Between Jan 1, 2016, and Dec 31, 2021, 41 691 individuals were hospitalised for opioid misuse and 26 860 were hospitalised for HCV. There were a median of 80 (IQR 24-213) opioid-related hospitalisations and 61 (21-196) HCV-related hospitalisations per ZCTA. A standard deviation increase in ZCTA-level uninsured rate (relative risk 1·24 [95% CI 1·17-1·31]), poverty rate (1·24 [1·17-1·31]), mortality (1·18 [1·12-1·25]), and social vulnerability index (1·17 [1·10-1·24]) was significantly associated with increased combined opioid-related and HCV-related hospitalisation rates. A standard deviation increase in ZCTA-level income (0·79 [0·75-0·84]) and unemployment rate (0·87 [0·82-0·93]) was significantly associated with decreased combined opioid-related and HCV-related hospitalisations. Using 2016-20 hospitalisations as training data, our models predicted ZCTA-level opioid-related hospitalisations in 2021 with a median of 80·4% (IQR 66·8-91·1) accuracy and HCV-related hospitalisations in 2021 with a median of 75·2% (61·2-87·7) accuracy. Several underserved high-risk ZCTAs were identified for delivery of targeted interventions. Our results suggest that individuals from economically disadvantaged and medically under-resourced communities are more likely to have an opioid-related or HCV-related hospitalisation. In conjunction with hospitalisation forecasts, our results could be used to identify and prioritise high-risk, underserved communities for delivery of field-level interventions. South Carolina Center for Rural and Primary Healthcare, National Institute on Drug Abuse, and National Library of Medicine.

A Case Report of Delayed Opioid Toxidrome After Administration of Naloxone.

Opioid use is an epidemic that plagues the United States. Patients frequently present to the emergency department (ED) after opioid toxicity, which can lead to respiratory failure, apnea, and death. Although there is an effective antidote, naloxone, the current guidelines surrounding post-naloxone administration monitoring are loosely defined. We present a case in which an individual was administered naloxone after an intentional opioid overdose and was monitored for four hours, as is standard in our institution. He remained in the ED for additional workup following this observation period and subsequently experienced signs of severe respiratory depression, requiring bag-valve-mask ventilation, naloxone, and admission. Had he been discharged, as is typical after a four-hour observation period, the consequences could have been fatal. We present multiple theories as to why his opioid toxidrome may have presented in a delayed manner, including ingestion of fentanyl analogues and variability in metabolization of both opioids and naloxone. We also explore alternative overdose antidote products approved by the US Food and Drug Administration, which may impact post overdose care. This case suggests that the correct amount of time to monitor patients after naloxone administration may be longer than originally thought. Our aim in this article was to further the discussion regarding the most appropriate observation period in cases of opioid toxicity.

Suicide deaths involving opioid poisoning in the United States, by sex, 1999-2021.

Suicide remains a leading cause of death in the United States, and recent data suggest suicide deaths involving opioids are increasing. Given unprecedented increases in drug-poisoning deaths, suicidality, and suicide deaths in recent years, an updated examination of the trends in suicide deaths involving opioids is warranted. In this descriptive epidemiologic analysis, we leverage final and provisional mortality data from the US Centers for Disease Control and Prevention's WONDER database to examine trends in suicide deaths involving opioid poisoning from 1999 to 2021 by biological sex. Results reveal complex changes over time: the number and age-adjusted rate of suicide deaths involving opioid poisoning among male and female residents tended to track together, and both increased through 2010, but then diverged, with the number and rate of suicide deaths involving opioid poisoning among female residents outpacing that of male residents. However, the number and rate of suicide deaths involving opioid poisoning among male residents then began to stabilize, while that of female residents declined, closing the sex-based gap. Across all years of data, the proportion of suicide deaths that involved opioid poisoning was consistently higher among female decedents (5.8%-11.0%) compared with male decedents (1.4%-2.8%). Findings have implications for improved suicide prevention and harm reduction efforts. This article is part of a Special Collection on Mental Health.

Nanotechnology-Enhanced Naloxone and Alternative Treatments for Opioid Addiction.

Opioids are commonly prescribed to address intense, ongoing pain associated with cancer, as well as long-lasting noncancer-related pain when alternative methods have proven ineffective. Individuals who exhibit both chronic pain and misuse of opioids face a significant danger of experiencing adverse health outcomes and the potential loss of life related to opioid use. Thus, there is a current movement to prescribe naloxone to those considered high-risk for opioid overdose. Naloxone has been explored as an antidote to reverse acute respiratory depression. Conversely, naloxone can give rise to other problems, including hypertension and cardiac arrhythmias. Thus, the importance of nanotechnology-enabled drug delivery strategies and their role in mitigating naloxone side-effects are significant. In this review, we explore the latest advancements in nanotechnology-enabled naloxone and alternative methods for addressing the opioid crisis through the utilization of non-opioid natural alternatives for chronic pain management.

Contemporary burden and trends of opioid-overdose mortality in New York State

BackgroundLimited research exists on contemporary opioid overdose mortality burden and trends in New York State, with most studies focusing on New York City. This study aimed to assess opioid overdose burden and death trends in New York State by age, sex, race/ethnicity, geographic area, opioid type, and overdose intent from 1999 to 2020. MethodsMortality data were obtained from the Centers for Disease Control and Prevention's WONDER database. Opioid overdose decedents were identified using relevant International Classification of Diseases, 10th Revision codes. Joinpoint regression analyzed trends, estimating annual and average annual percentage changes in age-adjusted mortality rates (AAMR). 95% confidence intervals were derived using the Parametric Method. ResultsFrom 1999 to 2020, New York State recorded 34,109 opioid overdose deaths (AAMR = 7.9 per 100,000 persons; 95% CI: 7.8–7.9). The overall trend increased by 12.6% per year (95% CI: 10.8, 14.4) from 2004 to 2020. Subgroups exhibited varying trends, with an 11.1% yearly increase among Non-Hispanic White persons from 2007 to 2020 (95% CI: 9.0, 13.2), a 24.6% annual rise among Non-Hispanic Black persons from 2012 to 2020 (95% CI: 17.7, 31.8), and an 18.3% increase yearly among Hispanic individuals from 2011 to 2020 (95% CI: 14.0, 22.9). Recent trends have worsened in both males and females, across all age groups, in both New York City (NYC) and areas outside NYC, and for heroin, natural and semisynthetic opioids, and synthetic opioids. ConclusionsOpioid overdose mortality in New York State has worsened significantly in the last two decades. Further research is essential to identify driving factors for targeted public health interventions.

Community-led approaches to making naloxone available in public settings: Implementation experiences in the HEALing communities study

BackgroundExpanding public naloxone access is a key strategy to reduce opioid overdose fatalities. We describe tailored community-engaged, data-driven approaches to install and maintain naloxone housing units (naloxone boxes) in New York State and estimate the cost of these approaches. MethodsGuided by the Consolidated Framework for Implementation Research, we collected data from administrative records and key informant interviews that documented the unique processes employed by four counties enrolled in the HEALing Communities Study to install and maintain naloxone housing units. We conducted a prospective micro-costing analysis to estimate the cost of each naloxone housing unit strategy from the community perspective. ResultsWhile all counties used a coalition to guide action planning for naloxone distribution, we identified unique approaches to implementing naloxone housing units: 1) County-led with technology expansion; 2) County-led grassroots; 3) Small-scale rural opioid overdose prevention program (OOPP) contract and 4) Comprehensive OOPP contract including overdose education and naloxone distribution (OEND) to individuals. The first two county-led approaches had lower cost per naloxone dose disbursed ($28–$38) compared to outsourcing to an OOPP ($183–$266); costs depended on services added to installing and maintaining units, such as OEND. Barriers included competing demands on public health resources (i.e., COVID-19) and stigma toward naloxone and opioid use disorder. Geographic access was a barrier in rural areas whereas existing infrastructure was a facilitator in urban counties. The policy landscape in New York State, which provides free naloxone kits and financial support to OOPPs, facilitated implementation in all counties. ConclusionsIf a community has the resources, installing and maintaining naloxone housing units in-house can be less expensive than contracting with an outside partner. However, contracts that include OEND may be more effective at reaching target populations. Financial support from health departments and legislative authorization are important facilitators to making naloxone available in public settings.

Predictive Modeling of Medical- and Orthopaedic-Related 90-Day Readmissions Following Primary Total Hip Arthroplasty

BackgroundThe rate of unplanned hospital readmissions following total hip arthroplasty (THA) varies from 3 to 10%, representing a major economic burden. However, it is unknown if specific factors are associated with different types of complications (ie, medical or orthopaedic-related) that lead to readmissions. Therefore, this study aimed to: (1) determine the overall, medical-related, and orthopaedic-related 90-day readmission rate; and (2) develop a predictive model for risk factors affecting overall, medical-related, and orthopaedic-related 90-day readmissions following THA. MethodsA prospective cohort of primary unilateral THAs performed at a large tertiary academic center in the United States from 2016 to 2020 was included (n = 8,893 patients) using a validated institutional data collection system. Orthopaedic-related readmissions were specific complications affecting the prosthesis, joint, and surgical wound. Medical readmissions were due to any other cause requiring medical management. Multivariable logistic regression models were used to investigate associations between prespecified risk factors and 90-day readmissions, as well as medical and orthopaedic-related readmissions independently. ResultsOverall, the rate of 90-day readmissions was 5.6%. Medical readmissions (4.2%) were found to be more prevalent than orthopaedic-related readmissions (1.4%). The area under the curve for the 90-day readmission model was 0.71 (95% confidence interval: 0.69 to 0.74). Factors significantly associated with medical-related readmissions were advanced age, Black race, education, Charlson Comorbidity Index, surgical approach, opioid overdose risk score, and nonhome discharge. In contrast, risk factors linked to orthopaedic-related readmissions encompassed body mass index, patient-reported outcome measure phenotype, nonosteoarthritis indication, opioid overdose risk, and nonhome discharge. ConclusionsOf the overall 90-day readmissions following primary THA, 75% were due to medical-related complications. Our successful predictive model for complication-specific 90-day readmissions highlights how different risk factors may disproportionately influence medical versus orthopaedic-related readmissions, suggesting that patient-specific, tailored preventive measures could reduce postoperative readmissions in the current value-based health care setting.

Morphine-Driven m6A Epitranscriptomic Neuroadaptations in Primary Cortical Cultures.

Opioid overdose is the leading cause of accidental death in the United States and remains a major public health concern, despite significant resources aimed at combating opioid misuse. Neurobiological research to elucidate molecular and cellular consequences of opioid exposure is required to define avenues to explore for reversal of opioid-induced neuroadaptations. Opioids impart well-documented regulation of the transcriptome and epigenetic modifications in the brain, but opioid-induced epitranscriptomic posttranscriptional regulation of RNA is vastly understudied. N6-methyladenosine (m6A) RNA methylation is significantly enriched in the brain and involved in learning, memory, and reward. m6A modifications have not been studied in opioid use disorder, despite being the most common RNA modification. We detected significant regulation of m6A-modifying enzymes in rat primary cortical cultures following morphine treatment, including AlkB Homolog 5 (Alkbh5). The m6a demethylaseALKBH5 functions as an m6A eraser, removing m6A modifications from mRNA. We hypothesized that chronic opioid treatment regulates m6A modifications through modulation of Alkbh5 and profiled m6A modifications in primary cortical cultures following chronic morphine treatment and Alkbh5 knock-down. We observed differential regulation of m6A modifications for a common set of transcripts following morphine or Alkbh5 knock-down, and the two treatments elicited concordant m6A epitranscriptomic profiles, suggesting that a subset of morphine-driven m6A modifications may be mediated through downregulation of Alkbh5 in cortical cultures. Gene Ontology terms of commonly regulated transcripts included serotonin secretion, synapse disassembly, neuron remodeling, and immune response. Thus, we conclude that morphine can drive epitranscriptomic changes, a subset of which may occur in an Alkbh5-dependent manner.

Commentary: Presence of kratom in opioid overdose deaths: findings from coroner postmortem toxicological report

Commentary: Presence of kratom in opioid overdose deaths: findings from coroner postmortem toxicological report

Prescription Opioid Dose Change Prior to Fatal Opioid-Detected Overdose.

The opioid overdose crisis continues within the U.S., and the role of prescribed opioids and prescribing patterns in overdose deaths remains an important area of research. This study investigated patterns of prescription opioids dispensed in the 12 months prior to opioid-detected overdose death in Connecticut between May 8th, 2016 and January 2nd, 2018, considering differences by demographic characteristics. The sample included decedents who had an opioid dispensed within 30 days preceding death. Using multilevel modeling, we estimated the slope of change in mean morphine equivalent (MME) daily dose over 12 months prior to death, considering linear and quadratic effects of time. We estimated the main effects of age, sex, race, and ethnicity and their interactions with time on MME. A sensitivity analysis examined how excluding decedents who did not receive long-term (≥90 days) opioid therapy affected mean MME slopes. Secondary analysis explored differences by toxicology results. Among 1,580 opioid-detected deaths, 179 decedents had prescribed opioids dispensed within 30 days preceding death. Decedents' mean age was 47.3 years (±11.5), 65.5% were male, 81% White non-Hispanic, 9.5% Black non-Hispanic, and 9.5% Hispanic. In the time-only model, linear (β=6.25, p<0.01) and quadratic (β=0.49, p=0.02) effects of time were positive, indicating exponentially increasing dose prior to death. Linear change in MME was significantly attenuated in men compared to women (β=-4.87, p=0.03); however, men were more likely to have non-prescription opioids in their toxicology results (p=0.02). Sensitivity analysis results supported primary findings. Rapid dose increases in dispensed opioids may be associated with opioid-detected overdose deaths, especially among women.

Prediction of naloxone dose in opioids toxicity based on machine learning techniques (artificial intelligence).

Treatment management for opioid poisoning is critical and, at the same time, requires specialized knowledge and skills. This study was designed to develop and evaluate machine learning algorithms for predicting the maintenance dose and duration of hospital stay in opioid poisoning, in order to facilitate appropriate clinical decision-making. This study used artificial intelligence technology to predict the maintenance dose and duration of administration by selecting clinical and paraclinical features that were selected by Pearson correlation (filter method) (Stage 1) and then the (wrapper method) Recursive Feature Elimination Cross-Validated (RFECV) (Stage2). The duration of administration was divided into two categories: A (which includes a duration of less than or equal to 24 h of infusion) and B (more than 24 h of naloxone infusion). XGBoost algorithm model with an accuracy rate of 91.04%, a prediction rate of 91.34%, and a sensitivity rate of 91.04% and area under the Curve (AUC) 0.97 was best model for classification patients. Also, the best maintenance dose of naloxone was obtained with XGBoost algorithm with R2 = 0.678. Based on the selected algorithm, the most important features for classifying patients for the duration of treatment were bicarbonate, respiration rate, physical sign, The partial pressure of carbon dioxide (PCO2), diastolic blood pressure, pulse rate, naloxone bolus dose, Blood Creatinine(Cr), Body temperature (T). The most important characteristics for determining the maintenance dose of naloxone were physical signs, bolus dose of 4.5 mg/kg, Glasgow Coma Scale (GCS), Creatine Phosphokinase (CPK) and intensive care unit (ICU) add. A predictive model can significantly enhance the decision-making and clinical care provided by emergency physicians in hospitals and medical settings. XGBoost was found to be the superior model.

Bystanders Saving Lives with Naloxone: A Scoping Review on Methods to Estimate Overdose Reversals.

People who use drugs in community settings are at risk of a fatal overdose, which can be mitigated by naloxone administered via bystanders. In this study we sought to investigate methods of estimating and tracking opioid overdose reversals by community members with take-home naloxone (THN) to coalesce possible ways of characterizing THN reach with a metric that is useful for guiding both distribution of naloxone and advocacy of its benefits. We conducted a scoping review of published literature on PubMed on August 15, 2022, using PRISMA-ScR protocol, for articles discussing methods to estimate THN reversals in the community. The following search terms were used: naloxone AND ("take home" OR kit OR "community distribution" OR "naloxone distribution"). We used backwards citation searching to potentially find additional studies. Overdose education and naloxone distribution program-based studies that analyzed only single programs were excluded. The database search captured 614 studies, of which 14 studies were relevant. Backwards citation searching of 765 references did not reveal additional relevant studies. Of the 14 relevant studies, 11 were mathematical models. Ten used Markov models, and one used a system dynamics model. Of the remaining three articles, one was a meta-analysis, and two used spatial analysis. Studies ranged in year of publication from 2013-2022 with mathematical modeling increasing in use over time. Only spatial analysis was used with a focus on characterizing local naloxone use at the level of a specific city. Of existing methods to estimate bystander administration of THN, mathematical models are most common, particularly Markov models. System dynamics modeling, meta-analysis, and spatial analysis have also been used. All methods are heavily dependent upon overdose education and naloxone distribution program data published in the literature or available as ongoing surveillance data. Overall, there is a paucity of literature describing methods of estimation and even fewer with methods applied to a local focus that would allow for more targeted distribution of naloxone.

Attitudes, Beliefs, Barriers, and Facilitators of Emergency Department Nurses Toward Patients with Opioid Use Disorder and Naloxone Distribution.

As opioid overdose deaths continue to rise, the emergency department (ED) remains an important point of contact for many at risk for overdose. In this study our purpose was to better understand the attitudes, beliefs, and knowledge of ED nurses in caring for patients with opioid use disorder (OUD). We hypothesized a difference in training received and attitudes toward caring for patients with OUD between nurses with <5years and ≥6years of clinical experience. We conducted a survey among ED nurses in a large academic medical center from May-July 2022. All ED staff nurses were surveyed. Data entry instruments for the nursing surveys were programmed in Qualtrics, and we analyzed results R using a chi-square test or Fisher exact test to compare nurses with <5years and ≥6years of clinical experience. A P-value of < 0.05 was considered statistically significant. We distributed 74 surveys, and 69 were completed (93%). Attitudes toward naloxone distribution from the ED were positive, with 72% of respondents reporting they were "very" or "extremely" supportive of distributing naloxone kits to individuals at risk of overdose. While attitudes were positive, barriers included limited time, lack of system support, and cost. Level of comfort in caring for patients with OUD was high, with 78% of respondents "very" or "extremely" comfortable. More education is needed on overdose education and naloxone distribution (OEND) with respondents 38% and 45% "a little" or "somewhat" comfortable, respectively. Nurses with <5years of experience reported receiving more training on OEND in nursing school compared to those with ≥6years of experience (P = 0.03). There were no significant differences in reported attitudes, knowledge, or comfort in caring for patients with OUD. In this single-center survey, we found ED nurses were supportive of overdose education and naloxone distribution. There are opportunities for targeted education and addressing systemic barriers to OEND. All interventions should be evaluated to gauge impact on knowledge, attitudes, and behaviors.

Evaluation of medications used for opioid use disorder in emergency departments: A cross-sectional analysis of the 2020 National Hospital Ambulatory Medical Care Survey

IntroductionOpioid use disorder (OUD) is a significant health issue impacting millions in the United States (US). Medications used for OUD (MOUD) (e.g., buprenorphine, methadone, naltrexone) and medications for overdose and symptom management (e.g., naloxone, clonidine) have been shown to be safe and effective tools in clinical management. MOUD therapy in Emergency Departments (EDs) improves patient outcomes and enhances engagement with formal addiction treatment; however, provider factors and institutional barriers have created hurdles to ED-based MOUD treatment and heterogeneity in ED based OUD care. We used a nationally representative dataset, the National Hospital Ambulatory Medical Care Survey (NHAMCS) to characterize MOUD prescribing practices across patient demographics, geographic regions, payers, providers, and comorbidities in EDs. MethodsNHAMCS is a survey conducted by the US Census Bureau assessing utilization of ambulatory healthcare services nationally. Survey staff compile encounter records from a nationally representative sample of EDs. We conducted a cross-sectional study using this data to assess visits in 2020 among patients aged 18–64 presenting with an opioid overdose or OUD. We estimated the proportion of patients who had any MOUD, clonidine, or naloxone treatment and 95% confidence intervals (CI). We modeled the association between patient demographic, location, comorbidities, and provider characteristics with receipt of MOUD treatment as unadjusted odds ratios (OR) and 95% CI. ResultsThere was a weighted frequency of 469,434 patients who were discharged from EDs after being seen for OUD or overdose. Naloxone, clonidine, and buprenorphine were the most frequent treatments administered and/or prescribed for OUDs or overdose. Overall, 54,123 (11.5%, 95%CI 0–128,977) patients who were discharged from the ED for OUDs or overdose received at least one type of MOUD. Hispanic race, (OR 17.9, 95%CI 1.33–241.90) and Western region (OR43.77, 95%CI 2.97–645.27) were associated with increased odds of receiving MOUDs, while arrival by ambulance was associated with decreased odds of receiving MOUDs (OR0.01, 95%CI 0.001–0.19). Being seen by an APP or physician assistant was associated with MOUD treatment (OR 16.68, 95%CI: 1.41–152.33; OR: 13.84, 95%CI: 3.58–53.51, respectively). ConclusionOur study findings suggest that MOUD and other medications for opioid overdose are infrequently used in the ED setting. This finding was especially notable in race, geographic region, mode of arrival, and those seen by APP, underscoring the need for further study into the root causes of these disparities. Our study provides a foundational understanding of MOUD patterns, guiding future research as the landscape of OUD treatment continues to shift.