Occupational and Personal Challenges During the Opioid Crisis: Understanding First Responders' Experiences and Viewpoints of Clients with Opioid Use Disorder.

OBJECTIVES: This study provides preliminary findings on the experiences of first responders during the opioid crisis and their viewpoints regarding whether clients with opioid use disorder deserve medical rehabilitation. Understanding associations between first responder experiences and viewpoints of client deservedness can help reduce stigma, improve compassionate care, and identify training gaps. METHODS: Analyses were run with data from a nationwide survey of Emergency Medical Services-providers and law enforcement workers collected from August to November 2022 (N = 3836). The study used univariate statistics and ordered logistic regression to understand first responders' experiences and viewpoints on client deservedness, as well as the relationship between the two. RESULTS: Results show a negative correlation between responding to overdose calls and perceiving clients with opioid use disorder as deserving of medical rehabilitation. Law enforcement, males, and conservatives also had negative viewpoints. Conversely, having a friend experience addiction and believing addiction has had a direct impact on respondents' lives predicted increases in client deservedness. CONCLUSIONS: Policy should focus on creating spaces where first responders can have positive interactions with people who use drugs or are in recovery. Better training is needed to help first responders manage on-the-job stressors and understand the complexities of addiction.

Firearm-Related Injuries and the US Opioid and Other Substance Use Epidemic: A Nationwide Evaluation of Emergency Department Encounters.

INTRODUCTION: There has been a sharp climb in the Unites States' death rate among opioid and other substance abuse patients, as well as an increased prevalence in gun violence. We aimed to investigate the association between substance abuse and gun violence in a national sample of patients presenting to US emergency departments (EDs). METHODS: We queried the 2018-2019 Nationwide Emergency Department Sample for patients ≥18 years with substance abuse disorders (opioid and other) using International Classification of Diseases, 10th Revision, Clinical Modification codes. Within this sample, we analyzed characteristics and outcomes of patients with firearm-related injuries. The primary outcome was mortality; secondary outcomes were ED charges and length of stay. RESULTS: Among the 25.2 million substance use disorder (SUD) patients in our analysis, 35,306 (0.14%) had a firearm-related diagnosis. Compared to other SUD patients, firearm-SUD patients were younger (33.3 versus 44.7 years, P < 0.001), primarily male (88.6% versus 54.2%, P < 0.001), of lower-income status (0-25th percentile income: 56.4% versus 40.5%, P < 0.001), and more likely to be insured by Medicaid or self-pay (71.6% versus 53.2%, P < 0.001). Firearm-SUD patients had higher mortality (1.4% versus 0.4%, P < 0.001), longer lengths of stay (6.5 versus 4.9 days, P < 0.001), and higher ED charges ($9269 versus $5,164, P < 0.001). Firearm-SUD patients had a 60.3% rate of psychiatric diagnoses. Firearm-SUD patients had 5.5 times greater odds of mortality in adjusted analyses (adjusted odds ratio: 5.5, P < 0.001). CONCLUSIONS: Opioid-substance abuse patients with firearm injuries have higher mortality rates and costs among these groups, with limited discharge to postacute care resources. All these factors together point to the urgent need for improved screening and treatment for this vulnerable group of patients.

Modeling Opioid Abuse: A Case Study of the Opioid Crisis in New England.

For the past two decades, the USA has been embroiled in a growing prescription drug epidemic. The ripples of this epidemic have been especially apparent in the state of Maine, which has fought hard to mitigate the damage caused by addiction to pharmaceutical and illicit opioids. In this study, we construct a mathematical model of the opioid epidemic incorporating novel features important to better understanding opioid abuse dynamics. These features include demographic differences in population susceptibility, general transmission expressions, and combined consideration of pharmaceutical opioid and heroin abuse. We demonstrate the usefulness of this model by calibrating it with data for the state of Maine. Model calibration is accompanied by sensitivity and uncertainty analysis to quantify potential error in parameter estimates and forecasts. The model is analyzed to determine the mechanisms most influential to the number of opioid abusers and to find effective ways of controlling opioid abuse prevalence. We found that the mechanisms most influential to the overall number of abusers in Maine are those involved in illicit pharmaceutical opioid abuse transmission. Consequently, preventative strategies that controlled for illicit transmission were more effective over alternative approaches, such as treatment. These results are presented with the hope of helping to inform public policy as to the most effective means of intervention.

The Opioid Epidemic: a Crisis Disproportionately Impacting Black Americans and Urban Communities.

The heroin epidemic has existed for decades, but a sharp rise in opioid overdose deaths (OODs) jolted the nation in the mid-twenty-teens and continues as a major health crisis to this day. Although the new wave of OODs was initially approached as a rural problem impacting a White/Caucasian demographic, surveillance records suggest severe impacts on African Americans and urban-dwelling individuals, which have been largely underreported. The focus of this report is on specific trends in OOD rates in Black and White residents in states with a significant Black urban population and declared as hotspots for OOD: (Maryland (MD), Illinois (IL), Michigan (MI), and Pennsylvania (PA)), and Washington District of Columbia (DC). We compare OODs by type of opioid, across ethnicities, across city/rural demographics, and to homicide rates using 2013-2020 data acquired from official Chief Medical Examiners' or Departments of Health (DOH) reports. With 2013 or 2014 as baseline, the OOD rate in major cities (Baltimore, Chicago, Detroit, Philadelphia) were elevated two-fold over all other regions of their respective state. In DC, Wards 7 and 8 OODs were consistently greater than other jurisdictions, until 2020 when the rate of change of OODs increased for the entire city. Ethnicity-wise, Black OOD rates exceeded White rates by four- to six-fold, with fentanyl and heroin having a disproportionate impact on Black opioid deaths. This disparity was aggravated by its intersection with the COVID-19 pandemic in 2020. African Americans and America's urban dwellers are vulnerable populations in need of social and political resources to address the ongoing opioid epidemic in under-resourced communities.

Clinical impact, costs, and cost-effectiveness of hospital-based strategies for addressing the US opioid epidemic: a modelling study.

BACKGROUND: The syndemic of injection drug use and serious injection-related infections is leading to increasing mortality in the USA. Although outpatient treatment with medications for opioid use disorder reduces overdose risk and recurrent infections, hospitalisation remains common. We evaluated the clinical impact, costs, and cost-effectiveness of hospital-based strategies to address the US opioid epidemic. METHODS: We developed a microsimulation model to compare the cost-effectiveness of: standard hospital care-detoxification for opioids, no addiction consult service (status quo); expanded inpatient prescribing of medications for opioid use disorder, including bridge prescriptions (ie, medication until they can see an outpatient provider) when possible (medications for opioid use disorder with bridge); implementation of addiction consult services within the hospital (addiction consult services alone); and a combined medication for opioid use disorder with addiction consult services strategy (combined). We used clinical trials and observational cohorts to inform model inputs. Outcomes were life-years, discounted costs, incremental cost-effectiveness ratios, hospitalisations, and deaths. We did deterministic sensitivity analyses on key model inputs related to costs and sequelae of drug use and probabilistic sensitivity analysis to further address uncertainty. FINDINGS: Among people who inject opioids in the USA, we estimated that expanding medications for opioid use disorder with bridge prescriptions would reduce hospitalisations and overdose deaths by 3·2% and 3·6%, respectively, and the combination of expanded medications with opioid use disorder along with addiction consult sevices would reduce hospitalisations and overdoses by 5·2% and 6·6%, respectively, compared with the status quo. Mean lifetime costs ranged from US$731 400 (95% credible interval 447 911-859 189 for the medications for opioid use disorder strategy) to $741 200 (470 930-868 551 for the combined strategy) per person. Assuming a willingness-to-pay threshold of $100 000 per life-year gained, medications for opioid use disorder with bridge and combined strategies were cost-effective ($7600 and $14 300, respectively). A scenario that assumed ideal access to harm reduction services came to the same conclusions as the base case and our results were robust in deterministic and probabilistic sensitivity analyses. INTERPRETATION: The combined interventions of expanding hospital-based prescribing of medications for opioid use disorder and implementing addiction consult services could improve life expectancy, be cost-effective, and could be the basis for a comprehensive hospital-based strategy for addressing the opioid epidemic in the USA and countries with similar opioid epidemics. FUNDING: National Institute on Drug Abuse and National Institute of Allergy and Infectious Diseases.

Cloud Computing Synthetic Syndromic Surveillance Systems: Opioid Epidemic in Illinois.

With an increasing number of overdose cases yearly, the city of Chicago is facing an opioid epidemic. Many of these overdose cases lead to 911 calls that necessitate timely response from our limited emergency medicine services. This paper demonstrates how data from these calls along with synthetic and geospatial data can help create a syndromic surveillance system to combat this opioid crisis. Chicago EMS data is obtained from the Illinois Department of Public Health with a database structure using the NEMSIS standard. This information is combined with information from the RTI U.S. Household Population database, before being transferred to an Azure Data Lake. Afterwards, the data is integrated with Azure Synapse before being refined in another data lake and filtered with ICD-10 codes. Afterwards, we moved the data to ArcGIS Enterprise to apply spatial statistics and geospatial analytics to create our surveillance system.

Is otologic surgery contributing to the opioid epidemic?

BACKGROUND: The opioid epidemic is a significant public health crisis challenging the lives of North Americans. Interestingly, this problem does not exist to the same extent in Europe. Surgeons play a significant role in prescribing opioids, especially in the context of post-operative pain management. The aim of this study was to compare the post-surgical prescribing patterns of otologists comparing Canada and Austria. METHODS: An online questionnaire was sent to 33 Canadian and 32 Austrian surgeons, who perform otologic surgery on a regular basis. Surgeons were asked to answer some questions about their background as well as typical prescribing patterns for postoperative pain medication for different ear surgeries (cochlear implant, stapedotomy, tympanoplasty). In addition, surgeons were asked about the typical use of local anesthetics for pain control at the end of a procedure. Otologists gave an estimate how confident they were that their therapy and prescriptions provide sufficient pain control to their patients. RESULTS: Analysis of the returned questionnaires showed that opioids are more commonly prescribed in Canada than in Austria. Nonsteroidal anti-inflammatory drugs are used for postoperative pain more regularly after ear surgery in Austria, as opposed to Canada. Some of the prescribed drugs by European otologists are not available in North America. The use of local anesthetics at the end of surgery is not common in Austria. Surgeons´ confidence that the prescribed pain medication was sufficient to control postoperative symptoms was higher in the group not prescribing opioids than in the group that did routinely prescribe opioids. CONCLUSION: Prescribing patterns differ substantially between the two evaluated countries. This data suggests an opportunity to reduce opioid prescriptions after otologic surgeries. Studies to evaluate pain after these operations as well as efficacy of analgesics following ear surgery are an important next step.

Opioid epidemic spread from Northern and Eastern Europe to Mediterranean Area.

ABSTRACT: The addiction to illicit opioid and the misuse of prescription synthetic opioids pain relievers and fentanyl analogs generated an opioid epidemic in North America over the last two decades that affected public health with a constantly rising number of overdoses deaths. This health treat moved to Europe with a significant increase starting from 2015 involving mainly norther and eastern countries and finally also the Mediterranean area. The "lock down" isolation and economic recession caused by COVID-19 pandemic showed a resurgence in opioid use and harms.

The rise of illicit fentanyls, stimulants and the fourth wave of the opioid overdose crisis.

PURPOSE OF REVIEW: This review provides an update on recently published literature on the rise of illicit fentanyls, risks for overdose, combinations with other substances, e.g. stimulants, consequences, and treatment. RECENT FINDINGS: Overdose due to illicit synthetic opioids (e.g. fentanyl and fentanyl analogs) continues to rise in the US both preceding and during the COVID-19 pandemic. Fentanyl-related overdose is rising in new geographic areas e.g. the western USA. Stimulant-related overdose is also increasing nationwide driven by methamphetamine and cocaine. Polysubstance use, e.g. the use of a stimulant along with an opioid is driving stimulant-related overdose. Other medical consequences of injection drug use are rising including HIV and hepatitis C infections. Medication approaches to treating opioid use disorder remain the standard of care and there are new promising pharmacological approaches to treating methamphetamine use disorder. SUMMARY: A 'fourth wave' of high mortality involving methamphetamine and cocaine use has been gathering force in the USA. Availability and use of illicit fentanyls are still the major drivers of overdose deaths and the current rise in stimulant-related deaths appears entwined with the ongoing opioid epidemic.

Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action.

The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the "risk assessment," "detection" or "prediction" of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices.

The Influence of the Opioid Epidemic on Firearm Violence in Kentucky Counties.

BACKGROUND: The opioid crisis is a major public health emergency. Current data likely underestimate the full impact on mortality due to limitations in reporting and toxicology screening. We explored the relationship between opioid overdose and firearm-associated emergency department visits (ODED & FAED, respectively). METHODS: For the years 2010 to 2017, we analyzed county-level ODED and FAED visits in Kentucky using Office of Health Policy and US Census Bureau data. Firearm death certificate data were analyzed along with high-dose prescriptions from the Kentucky All Schedule Prescription Electronic Reporting records. Socioeconomic variables analyzed included health insurance coverage, race, median household earnings, unemployment rate, and high-school graduation rate. RESULTS: ODED and FAED visits were correlated (Rho = 0.29, P< 0.01) and both increased over the study period, remarkably so after 2013 (P < 0.001). FAED visits were higher in rural compared to metro counties (P < 0.001), while ODED visits were not. In multivariable analysis, FAED visits were associated with ODED visits (Std. B = 0.24, P= 0.001), high-dose prescriptions (0.21, P = 0.008), rural status (0.19, P = 0.012), percentage white race (-0.28, P = 0.012), and percentage high school graduates (-0.68, P < 0.001). Unemployment and earnings were bivariate correlates with FAED visits (Rho = 0.42, P < 0.001 and -0.32, P < 0.001, respectively) but were not significant in the multivariable model. CONCLUSIONS: In addition to recognized nonfatal consequences of the opioid crisis, firearm violence appears to be a corollary impact, particularly in rural counties. Firearm injury prevention efforts should consider the contribution of opioid use and abuse.

Assessing opioid overdose risk: a review of clinical prediction models utilizing patient-level data.

Drug, and specifically opioid-related, overdoses remain a major public health problem in the United States. Multiple studies have examined individual risk factors associated with overdose risk, but research developing clinical risk prediction tools for overdose has only emerged in the last few years. We conducted a comprehensive review of the literature on patient-level factors associated with opioid-related overdose risk, with an emphasis on clinical risk prediction models for opioid-related overdose in the United States. Studies that developed and/or validated clinical prediction models were closely reviewed and evaluated to determine the state of the field. We identified 12 studies that reported risk prediction models for opioid-related overdose risk. Published models were developed from a variety of data sources, including Veterans Health Administration data, Medicare data, commercial insurance data, and statewide linked datasets. Studies reported model performance using measures of discrimination, usually at good-to-excellent levels, though they did not always assess calibration. C-statistics were better for models that included clinical predictors (c-statistics: 0.75-0.95) compared to models without them (c-statistics: 0.69-0.82). External validation of models was rare, and we found no studies evaluating implementation of models or risk prediction tools into clinical practice. A common feature of these models was a high rate of false positives, largely because opioid-related overdose is rare in the general population. Thus, efforts to implement prediction models into practice should take into account that published models overestimate overdose risk for many low-risk patients. Future prediction models assessing overdose risk should employ external validation and address model calibration. In order to translate findings from prediction models into clinical public health benefit, future studies should focus on developing clinical prediction tools based on prediction models, implementing these tools into clinical practice, and evaluating the impact of these models on treatment decisions, patient outcomes, and, ultimately, opioid overdose rates.

"Doctor and pharmacy shopping": A fading signal for prescription opioid use monitoring?

BACKGROUND: The term "doctor and pharmacy shopping" colloquially describes patients with high multiple provider episodes (MPEs)-a threshold count of distinct prescribers and/or pharmacies involved in prescription fulfillment. Opioid-related MPEs are implicated in the global opioid crisis and heavily monitored by government databases such as U.S. state prescription drug monitoring programs (PDMPs). We applied a widely-used MPE definition to examine U.S. trends from a large, commercially-insured population from 2010 to 2017. Further, we examined the proportion of enrollees identified as "doctor shoppers" with evidence of a cancer diagnosis to examine the risk of false positives. METHODS: Using a large, commercially-insured population, we identified patients with opioid-related MPEs: opioid prescriptions (Schedule II-V, no buprenorphine) filled from ≥5 prescribers AND ≥ 5 pharmacies within the past 90 days ("5x5x90d"). Quarterly rates per 100,000 enrollees (two specifications) were calculated between 2010 and 2017. We examined the trend in a recently published all-payer, 7 state cohort from the U.S. Centers for Disease Control and Prevention for comparison. Cancer-related ICD-9/10-CM codes were used. RESULTS: Quarterly MPE rates declined by approximately 73 % from 18.2-4.9 per 100,000 enrollee population with controlled substance prescriptions. In 2017, nearly one fifth of these commercially-insured enrollees identified by the 5x5x90d algorithm were diagnosed with cancer. Approximately 8% of this sample included patients with ≥ 1 buprenorphine prescriptions. CONCLUSIONS: Opioid "shopping" flags are a long-standing but rapidly fading PDMP signal. To avoid unintended consequences, such as identifying legitimate medical encounters requiring high healthcare utilization or opioid treatment, while maintaining vigilance, more nuanced and sophisticated approaches are needed.

A dynamic model of the opioid drug epidemic with implications for policy.

Background: The U.S. opioid epidemic has caused substantial harm for over 20 years. Policy interventions have had limited impact and sometimes backfired. Experts recommend a systems modeling approach to address the complexities of opioid policymaking.Objectives: Develop a system dynamics simulation model that reflects the complexities and can anticipate intended and unintended intervention effects.Methods: The model was developed from literature review and data gathering. Its outputs, starting in 1990, were compared against 12 historical time series. Four illustrative interventions were simulated for 2020-2030: reducing prescription dosage by 20%, cutting diversion by 30%, increasing addiction treatment from 45% to 65%, and increasing lay naloxone use from 4% to 20%. Sensitivity testing was performed to determine effects of uncertainties. No human subjects were studied.Results: The model fits historical data well with error percentage averaging 9% across 201 data points. Interventions to reduce dosage and diversion reduce the number of persons with opioid use disorder (PWOUD) by 11% and 16%, respectively, but each of these interventions reduces overdoses by only 1%. Boosting treatment reduces overdoses by 3% but increases PWOUD by 1%. Expanding naloxone reduces overdose deaths by 12% but increases PWOUD by 2% and overdoses by 3%. Combining all four interventions reduces PWOUD by 24%, overdoses by 4%, and deaths by 18%. Uncertainties may affect these numerical results, but policy findings are unchanged.Conclusion: No single intervention significantly reduces both PWOUD and overdose deaths, but a combination strategy can do so. Entering the 2020s, only protective measures like naloxone expansion could significantly reduce overdose deaths.