Literature DB >> 24521559

Using textual cause-of-death data to study drug poisoning deaths.

Eric M Ossiander.   

Abstract

Death certificate data are often used to study the epidemiology of poisoning deaths, but the International Classification of Diseases (ICD) codes used to tabulate death data do not convey all of the available information about the drugs and other substances named on death certificates. In the United States and some other countries, the SuperMICAR computer system is used to assign ICD codes to deaths. The SuperMICAR system also stores a verbatim record of the text entered for the cause of death. We used the SuperMICAR text entries to study the 7,817 poisoning deaths that occurred among Washington State residents between 2003 and 2010. We tabulated the drugs named on death certificates and computed age-adjusted and age-specific death rates for the top-named drugs and for prescription and illicit drugs. Methadone was named on 2,149 death certificates and was the most frequently named substance, followed by alcohol, opiate, cocaine, oxycodone, and methamphetamine. For both men and women and at all ages, prescription drugs were involved in more deaths than were illicit drugs. Among the 25 drugs named most frequently, only 4 have unique ICD codes; the other 21 can be identified only by using the SuperMICAR data.

Entities:  

Keywords:  International Classification of Diseases; SuperMICAR; cause of death; death certificates; poisoning

Mesh:

Substances:

Year:  2014        PMID: 24521559     DOI: 10.1093/aje/kwt333

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  12 in total

1.  Emergency department utilization and subsequent prescription drug overdose death.

Authors:  Joanne E Brady; Charles J DiMaggio; Katherine M Keyes; John J Doyle; Lynne D Richardson; Guohua Li
Journal:  Ann Epidemiol       Date:  2015-04-02       Impact factor: 3.797

2.  Opioid Use Disorder and Pregnancy.

Authors:  Frederick T O'Donnell; Daniel L Jackson
Journal:  Mo Med       Date:  2017 May-Jun

3.  Harnessing information from injury narratives in the 'big data' era: understanding and applying machine learning for injury surveillance.

Authors:  Kirsten Vallmuur; Helen R Marucci-Wellman; Jennifer A Taylor; Mark Lehto; Helen L Corns; Gordon S Smith
Journal:  Inj Prev       Date:  2016-01-04       Impact factor: 2.399

4.  Cocaine use and overdose mortality in the United States: Evidence from two national data sources, 2002-2018.

Authors:  Manuel Cano; Sehun Oh; Christopher P Salas-Wright; Michael G Vaughn
Journal:  Drug Alcohol Depend       Date:  2020-07-15       Impact factor: 4.492

5.  Drug involvement in fatal overdoses.

Authors:  Christopher J Ruhm
Journal:  SSM Popul Health       Date:  2017-01-31

6.  Malignant Cerebellar Edema Subsequent to Accidental Prescription Opioid Intoxication in Children.

Authors:  Daniel Duran; Robert D Messina; Lauren A Beslow; Julio D Montejo; Jason K Karimy; Charuta Gavankar Furey; Alison D Sheridan; Gordon Sze; Yanki Yarman; Michael L DiLuna; Kristopher T Kahle
Journal:  Front Neurol       Date:  2017-07-25       Impact factor: 4.003

7.  Online Conversation Monitoring to Understand the Opioid Epidemic: Epidemiological Surveillance Study.

Authors:  Joshua C Black; Zachary R Margolin; Richard A Olson; Richard C Dart
Journal:  JMIR Public Health Surveill       Date:  2020-06-29

Review 8.  Methodological Complexities in Quantifying Rates of Fatal Opioid-Related Overdose.

Authors:  Svetla Slavova; Chris Delcher; Jeannine M Buchanich; Terry L Bunn; Bruce A Goldberger; Julia F Costich
Journal:  Curr Epidemiol Rep       Date:  2019-05-02

9.  Changes in Mortality Involving Extended-Release and Long-Acting Opioids After Implementation of a Risk Evaluation and Mitigation Strategy.

Authors:  Joshua C Black; Gabrielle E Bau; Travis Rosen; M Soledad Cepeda; Gregory P Wedin; Jody L Green; Richard C Dart
Journal:  Pain Med       Date:  2020-01-01       Impact factor: 3.750

10.  Poisoning-induced Out-of-Hospital Cardiac Arrest and Outcomes according to Poison Agent.

Authors:  Minjee Kim; Sang Do Shin; Seungmin Jeong; Young Ho Kwak; Gil Joon Suh
Journal:  J Korean Med Sci       Date:  2017-12       Impact factor: 2.153

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