A National Epidemic of Unintentional Prescription Opioid Overdose Deaths: How Physicians Can Help Control It

2011 ◽  
Vol 72 (05) ◽  
pp. 589-592 ◽  
Author(s):  
Leonard J. Paulozzi ◽  
Richard H. Weisler ◽  
Ashwin A. Patkar
2019 ◽  
Vol 15 (5) ◽  
pp. 428-432
Author(s):  
Amer Raheemullah, MD ◽  
Neal Andruska, MD, PhD

Fentanyl overdoses are growing at an alarming rate. Fentanyl is often mixed into heroin and counterfeit prescription opioid pills without the customer’s knowledge and only detected upon laboratory analysis. This is problematic because fentanyl analogues like carfentanil are 10,000 times more potent than morphine and pose new challenges to opioid overdose management. A 62-year-old male with an overdose from a rare fentanyl analogue, acrylfentanyl, was given two doses of intranasal 2 mg naloxone with improvements in respiratory rate. In lieu of more naloxone, his trachea was intubated and he was admitted to the intensive care unit. He subsequently developed ventilator-associated pneumonia and then a pulmonary embolism. He did not receive any opioid use disorder treatment and returned back to the emergency department with an opioid overdose 21 days after discharge.We are encountering an unprecedented rise in synthetic opioid overdose deaths as we enter the third decade of the opioid epidemic. Thus, it is imperative to be aware of the features and management of overdoses from fentanyl and its analogues. This includes protecting against occupational exposure, administering adequate doses of naloxone, and working with public health departments to respond to fentanyl outbreaks. Additionally, fentanyl overdoses represent a critical opportunity to move beyond acute stabilization, start buprenorphine or methadone for opioid use disorder during hospitalization, link patients to ongoing addiction treatment, and distribute naloxone into the community to help curb the overdose epidemic.


2017 ◽  
Vol 76 (4) ◽  
pp. 462-477 ◽  
Author(s):  
Ezequiel Brown ◽  
George L. Wehby

We examine the effects of state-level economic conditions including unemployment rates, median house price, median household income, insurance coverage, and annual and weekly work time on deaths on drug overdose deaths including from opioids and prescription opioids between 1999 and 2014. We employ difference-in-differences estimation controlling for state and year fixed effects, state-specific time trends, and demographic characteristics. Drug overdose deaths significantly declined with higher house prices, an effect driven by reduction in prescription-opioid mortality, by nearly 0.17 deaths per 100,000 (~4%) with a $10,000 increase in median house price. House price effects were more pronounced and only significant among males, non-Hispanic Whites, and individuals younger 45 years. Other economic indicators had insignificant effects. Our findings suggest that economic downturns that substantially reduce house prices such as the Great Recession can increase opioid-related deaths, suggesting that efforts to control access to such drugs should especially intensify during these periods.


2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Sarah J. Nechuta ◽  
Jenna Moses ◽  
Molly Golladay ◽  
Adele Lewis ◽  
Julia Goodin ◽  
...  

ObjectiveTo examine specific drugs present based on postmortem toxicology for prescription opioid, heroin, and fentanyl overdoses classified based on ICD-10 coding. To compare drugs identified from postmortem toxicology with those listed on the death certificate for opioid overdoses.IntroductionUsing death certificates alone to identify contributing substances in drug overdose deaths may result in misclassification and underestimation of the burden of illicit and prescription opioids and other drugs in drug-related deaths. To enable timely and targeted prevention in Tennessee (TN), the identification and monitoring of new drugs and trends in use should utilize toxicology and medicolegal death investigation data directly, as recommended by others 1-3. These data can inform mortality outcome definitions for improved surveillance and risk factor identification 4-7. To our knowledge, this is the first analysis to use statewide linked toxicology and death certificate data in TN.MethodsWe identified 615 opioid involved overdose deaths in TN of unintentional (underlying ICD-10 codes: X40-X44) or undetermined (underlying ICD-10 codes: Y10-Y14) intent during June 1st to December 31st 2017. Utilizing the Interim Medical Examiner Database (I-MED), we identified postmortem toxicology reports for 454 cases, which were from one of three national laboratories used by a state Regional Forensic Center. Toxicology data were abstracted and independently verified by two co-authors and linked to the TN death statistical file that included cause of death information (literal text and ICD-10 codes) and demographics. The analysis focuses on cases with an available toxicology report.ResultsWe identified 171 prescription opioid overdoses, 221 fentanyl overdoses, and 113 heroin overdoses. Table 1 displays postmortem toxicology profiles for major drugs/classes. For prescription opioid deaths (excluding fentanyl and heroin), positive toxicology results for prescription opioids were as follows: methadone (11%), buprenorphine (14%), hydrocodone (14%), oxycodone (36%) and oxymorphone (also a metabolite, 47%). Benzodiazepines were present in close to 58% of prescription opioid overdoses; stimulants (cocaine, amphetamines, methamphetamines) in about 25%. For fentanyl and heroin deaths, prescription opioids were detected in about 26% and 34%, respectively; stimulants in about 57.9% and 52.2%, respectively, and benzodiazepines 36-37%. Fentanyl was present on toxicology in about half of heroin overdoses, and 6–monoacetylmorphine in 72.6%.ConclusionsUsing medical examiners’ data, including toxicology data, improves estimation of contributing drugs involved in opioid deaths. This analysis provides jurisdiction-specific data on drugs that can help with monitoring trends and informs risk factor identification. Future work includes adding information on prescribed opioid and benzodiazepines using TN’s Prescription Drug Monitoring Database and evaluating demographic variation in contributing drugs between toxicology and DC data to identify susceptible populations.References1. Slavova S, O'Brien DB, Creppage K, Dao D, Fondario A, Haile E, Hume B, Largo TW, Nguyen C, Sabel JC, Wright D, Council of S, Territorial Epidemiologists Overdose S. Drug Overdose Deaths: Let's Get Specific. Public Health Rep.2. Horon IL, Singal P, Fowler DR, Sharfstein JM. Standard Death Certificates Versus Enhanced Surveillance to Identify Heroin Overdose-Related Deaths. Am J Public Health. 2018;108(6):777-81.3. Mertz KJ, Janssen JK, Williams KE. Underrepresentation of heroin involvement in unintentional drug overdose deaths in Allegheny County, PA. J Forensic Sci. 2014;59(6):1583-5.4. Landen MG, Castle S, Nolte KB, Gonzales M, Escobedo LG, Chatterjee BF, Johnson K, Sewell CM. Methodological issues in the surveillance of poisoning, illicit drug overdose, and heroin overdose deaths in new Mexico. Am J Epidemiol. 2003;157(3):273-8.5. Davis GG, National Association of Medical E, American College of Medical Toxicology Expert Panel on E, Reporting Opioid D. Complete republication: National Association of Medical Examiners position paper: Recommendations for the investigation, diagnosis, and certification of deaths related to opioid drugs. J Med Toxicol. 2014;10(1):100-6.6. Slavova S, Bunn TL, Hargrove SL, Corey T. Linking Death Certificates, Postmortem Toxicology, and Prescription History Data for Better Identification of Populations at Increased Risk for Drug Intoxication Deaths. Pharmaceutical Medicine. 2017;31(3):155-65.7. Hurstak E, Rowe C, Turner C, Behar E, Cabugao R, Lemos NP, Burke C, Coffin P. Using medical examiner case narratives to improve opioid overdose surveillance. Int J Drug Policy. 2018;54:35-42. 


2019 ◽  
Vol 57 (1) ◽  
pp. 106-110 ◽  
Author(s):  
Lewei (Allison) Lin ◽  
Talya Peltzman ◽  
John F. McCarthy ◽  
Elizabeth M. Oliva ◽  
Jodie A. Trafton ◽  
...  

2013 ◽  
Vol 28 (10) ◽  
pp. 1258-1259 ◽  
Author(s):  
Darius A. Rastegar ◽  
Alexander Y. Walley

2017 ◽  
Vol 178 ◽  
pp. 501-511 ◽  
Author(s):  
Denise B. Kandel ◽  
Mei-Chen Hu ◽  
Pamela Griesler ◽  
Melanie Wall

2018 ◽  
Vol 108 (4) ◽  
pp. 500-502 ◽  
Author(s):  
Puja Seth ◽  
Rose A. Rudd ◽  
Rita K. Noonan ◽  
Tamara M. Haegerich

Author(s):  
Jaynia Anderson ◽  
Natalie Demeter ◽  
Mar-y-sol Pasquires ◽  
Stephen Wirtz

ObjectiveDemonstrate the use of timely, actionable data from a data visualization tool, the California Opioid Overdose Surveillance Dashboard, which integrates statewide, geographic- and demographic-specific data, by describing the changes in opioid overdose deaths in California.IntroductionCalifornia continues to face a serious public health crisis with the opioid epidemic having substantial health and economic impacts. The epidemic is dynamic and rapidly changing, involving both prescription opioids influenced by prescribing and dispensing patterns as well as illicit opioids influenced by the availability of heroin and recently, the increased availability of fentanyl. The complexity of the issue necessitates data-informed actions through multi-sector, strategic collaboration at both the state and local levels to address the problem comprehensively. With nearly 2,000 opioid overdose deaths per year and wide variation of overdose rates across counties and demographic groups, there is a need for integrated, timely, actionable data for use by state policy makers, local opioid safety coalitions, media, community stakeholders, and the public to monitor and combat this dynamic epidemic at the state and local level. Using fatality data from the California Opioid Overdose Surveillance Dashboard1, the opioid overdose epidemic is described along with the differential geographic and demographic impacts.MethodsAs part of California Department of Public Health’s Prevention for States grant funded by the Centers for Disease Control and Prevention, the California Opioid Overdose Surveillance Dashboard was developed as a data tool to provide enhanced visualization and integration of non-fatal and fatal opioid-involved overdose data and opioid prescription data. The dashboard was built on an open source RStudio server using Shiny, an R package that provides a framework for building web applications. Data incorporated on the dashboard include emergency department visits, hospitalizations, fatalities, and prescriptions related to opioid overdoses among California residents, presented in raw counts, crude rates, and age-adjusted rates at the state, county, and zip code levels, as well as by sex, age, and race/ethnicity. Overdose deaths are identified using ICD-10 (International Classification of Diseases, 10th Revision) codes X40-X44, X60-X64, X85, Y10-Y14, and T40.0-T40.6, recorded in the underlying cause of death and multiple cause of death fields on death certificates. Fentanyl overdose deaths are identified using a text search on contributing cause of death fields on death certificates. Using data from the California Opioid Overdose Surveillance Dashboard, we present one perspective of the epidemic by using 2017 death data to describe the changing trend and geographic and demographic variation of prescription drug, heroin, and fentanyl overdose deaths.ResultsOverall trends from 2011-2017 show that deaths due to opioid overdoses have increased. Prescription drug overdose death rates have slightly decreased by 6% from 3.93/100,000 in 2011 to 3.7/100,000 in 2017. Heroin overdose death rates have increased by 89% from 0.90/100,000 in 2011 to 1.70/100,000 in 2017. Fentanyl overdose death rates have increased by 320% from 0.25/100,000 in 2011 to 1.05/100,000 in 2017. The highest rates of prescription opioid overdose deaths are primarily concentrated in northern rural counties, while the highest rates of heroin and fentanyl overdose deaths are more dispersed throughout the state with many coastal counties showing higher rates of overdose deaths (Figure 1). Prescription opioid overdose deaths are concentrated among older ages showing highest rates among 55 to 59 year olds (8.27/100,000). In contrast, heroin and fentanyl overdose death rates are concentrated among younger ages with the highest rates seen among 25 to 29 year olds, 4.54/100,000 and 2.78/100,000, respectively (Figure 2). Males died from prescription opioid, heroin, and fentanyl overdoses at significantly higher rates than females. Prescription opioid and fentanyl overdose death rates (11.5/100,000 and 4.80/100,000, respectively) are significantly higher among Native Americans compared to other races/ethnicities (Table 1). Non-Hispanic whites had significantly higher prescription opioid and heroin overdose death rates (6.90/100,000 and 2.96/100,000, respectively) compared to non-Hispanic black, Hispanic, and Asian residents of California.ConclusionsFatality data from 2017 show the characteristics of the opioid overdose epidemic in California are changing. While still high, overdose deaths from prescription opioids, seen primarily in older age groups and northern rural California, are slightly declining. Concurrently, we are seeing sharp rises in heroin and fentanyl overdose death rates among younger adults throughout the state. Regardless of any change in trend, there remain clear disparities in overdose death rates by race/ethnicity; with Native Americans having the highest rates for both prescription and illicit opioids, and non-Hispanic whites have higher rates of prescription opioid and heroin overdose deaths.Given the varying demographic and geographic impacts based on the type of opioid, as demonstrated with the use of death data, there needs to be targeted data-informed interventions to address and prevent prescription and illicit opioid overdoses. Death data is just one perspective on the epidemic, other data sources (emergency department visits, hospitalizations, and prescriptions) are needed complete the picture to truly provide a robust data-informed approach. The California Opioid Overdose Surveillance dashboard integrates these multiple data sources and serves as a valuable tool in providing specific and timely data to inform approaches and interventions at the state and local level in continuing to fight California’s opioid overdose epidemic. The enhanced visualization, geographic- and demographic-specific data, and increasingly timely data allow for state and local policy makers, local opioid safety coalitions, and community stakeholders to track the dynamics and impact of the epidemic and to identify those who are most vulnerable and differentially impacted.References1 California Opioid Overdose Surveillance Dashboard https://discovery.dev.cdph.ca.gov/CDIC/ODdash/ 


Sign in / Sign up

Export Citation Format

Share Document