Literature DB >> 31046868

Evaluation of Oklahoma's Electronic Death Registration System and Event Fatality Markers for Disaster-Related Mortality Surveillance - Oklahoma USA, May 2013.

Anindita N Issa1, Kelly Baker2, Derek Pate2, Royal Law1, Tesfaye Bayleyegn1, Rebecca S Noe1.   

Abstract

INTRODUCTION: Official counts of deaths attributed to disasters are often under-reported, thus adversely affecting public health messaging designed to prevent further mortality. During the Oklahoma (USA) May 2013 tornadoes, Oklahoma State Health Department Division of Vital Records (VR; Oklahoma City, Oklahoma USA) piloted a flagging procedure to track tornado-attributed deaths within its Electronic Death Registration System (EDRS). To determine if the EDRS was capturing all tornado-attributed deaths, the Centers for Disease Control and Prevention (CDC; Atlanta, Georgia USA) evaluated three event fatality markers (EFM), which are used to collate information about deaths for immediate response and retrospective research efforts.
METHODS: Oklahoma identified 48 tornado-attributed deaths through a retrospective review of hospital morbidity and mortality records. The Centers for Disease Control and Prevention (CDC; Atlanta, Georgia USA) analyzed the sensitivity, timeliness, and validity for three EFMs, which included: (1) a tornado-specific flag on the death record; (2) a tornado-related term in the death certificate; and (3) X37, the International Classification of Diseases, 10th Revision (ICD-10) code in the death record for Victim of a Cataclysmic Storm, which includes tornadoes.
RESULTS: The flag was the most sensitive EFM (89.6%; 43/48), followed by the tornado term (75.0%; 36/48), and the X37 code (56.2%; 27/48). The most-timely EFM was the flag, which took 2.0 median days to report (range 0-10 days), followed by the tornado term (median 3.5 days; range 1-21), and the X37 code (median >10 days; range 2-122). Over one-half (52.1%; 25/48) of the tornado-attributed deaths were missing at least one EFM. Twenty-six percent (11/43) of flagged records had no tornado term, and 44.1% (19/43) had no X37 code. Eleven percent (4/36) of records with a tornado term did not have a flag.
CONCLUSION: The tornado-specific flag was the most sensitive and timely EFM. Using the flag to collate death records and identify additional deaths without the tornado term and X37 code may improve immediate response and retrospective investigations. Moreover, each of the EFMs can serve as quality controls for the others to maximize capture of all disaster-attributed deaths from vital statistics records in the EDRS.Issa AN, Baker K, Pate D, Law R, Bayleyegn T, Noe RS. Evaluation of Oklahoma's Electronic Death Registration System and event fatality markers for disaster-related mortality surveillance - Oklahoma USA, May 2013. Prehosp Disaster Med. 2019;34(2):125-131.

Entities:  

Keywords:  10th Revision; EDRS Electronic Death Registration System; EFM event fatality marker; EOC Emergency Operations Center; ICD-10 International Classification of Diseases; IPS Oklahoma State Department of Health Injury Prevention Service; ME medical examiner; NCHS National Center for Health Statistics; OCME Oklahoma Office of the Chief Medical Examiner; VR Oklahoma State Department of Health Division of Vital Records; EDRS; disaster; flag; mortality; tornado

Mesh:

Year:  2019        PMID: 31046868      PMCID: PMC6953479          DOI: 10.1017/S1049023X19000189

Source DB:  PubMed          Journal:  Prehosp Disaster Med        ISSN: 1049-023X            Impact factor:   2.040


  13 in total

1.  Assessing disaster-attributed mortality: development and application of a definition and classification matrix.

Authors:  D L Combs; L E Quenemoen; R G Parrish; J H Davis
Journal:  Int J Epidemiol       Date:  1999-12       Impact factor: 7.196

2.  Challenges in disaster data collection during recent disasters.

Authors:  Melinda Morton; J Lee Levy
Journal:  Prehosp Disaster Med       Date:  2011-06       Impact factor: 2.040

3.  Evaluating the Use of an Electronic Death Registration System for Mortality Surveillance During and After Hurricane Sandy: New York City, 2012.

Authors:  Renata E Howland; Wenhui Li; Ann M Madsen; Howard Wong; Tara Das; Flor M Betancourt; Leze Nicaj; Catherine Stayton; Thomas Matte; Elizabeth M Begier
Journal:  Am J Public Health       Date:  2015-09-17       Impact factor: 9.308

4.  Updated guidelines for evaluating public health surveillance systems: recommendations from the Guidelines Working Group.

Authors:  R R German; L M Lee; J M Horan; R L Milstein; C A Pertowski; M N Waller
Journal:  MMWR Recomm Rep       Date:  2001-07-27

5.  Tracking deaths related to Hurricane Ike, Texas, 2008.

Authors:  David F Zane; Tesfaye M Bayleyegn; John Hellsten; Ryan Beal; Crystal Beasley; Tracy Haywood; Dana Wiltz-Beckham; Amy F Wolkin
Journal:  Disaster Med Public Health Prep       Date:  2011-03       Impact factor: 1.385

6.  Medical examiner and coroner systems: history and trends.

Authors:  R Hanzlick; D Combs
Journal:  JAMA       Date:  1998-03-18       Impact factor: 56.272

7.  Evaluation of active mortality surveillance system data for monitoring hurricane-related deaths-Texas, 2008.

Authors:  Ekta Choudhary; David F Zane; Crystal Beasley; Russell Jones; Araceli Rey; Rebecca S Noe; Colleen Martin; Amy F Wolkin; Tesfaye M Bayleyegn
Journal:  Prehosp Disaster Med       Date:  2012-07-17       Impact factor: 2.040

8.  Medicolegal Death Scene Investigations After Natural Disaster- and Weather-Related Events: A Review of the Literature.

Authors:  Luciana A Rocha; Catharine Q Fromknecht; Sarah Davis Redman; Joanne E Brady; Sarah E Hodge; Rebecca S Noe
Journal:  Acad Forensic Pathol       Date:  2017-06-01

9.  Evaluation of Real-Time Mortality Surveillance Based on Media Reports.

Authors:  Olaniyi O Olayinka; Tesfaye M Bayleyegn; Rebecca S Noe; Lauren S Lewis; Vincent Arrisi; Amy F Wolkin
Journal:  Disaster Med Public Health Prep       Date:  2016-12-29       Impact factor: 1.385

10.  Hurricane Katrina deaths, Louisiana, 2005.

Authors:  Joan Brunkard; Gonza Namulanda; Raoult Ratard
Journal:  Disaster Med Public Health Prep       Date:  2008-12       Impact factor: 1.385

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.