Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-28T05:25:52.859Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  03 May 2019

Anindita N. Issa*
Affiliation:
Centers for Disease Control and Prevention, Chamblee, Georgia, USA
Kelly Baker
Affiliation:
Oklahoma State Department of Health, Oklahoma City, Oklahoma, USA
Derek Pate
Affiliation:
Oklahoma State Department of Health, Oklahoma City, Oklahoma, USA
Royal Law
Affiliation:
Centers for Disease Control and Prevention, Chamblee, Georgia, USA
Tesfaye Bayleyegn
Affiliation:
Centers for Disease Control and Prevention, Chamblee, Georgia, USA
Rebecca S. Noe
Affiliation:
Centers for Disease Control and Prevention, Chamblee, Georgia, USA
*
Correspondence: Anindita N. Issa, MD, Centers for Disease Control and Prevention, National Center for Environmental Health, 4770 Buford Hwy, NE, MS F-60, Chamblee, Georgia 30341 USA E-mail: [email protected]

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

Type
Original Research
Copyright
© World Association for Disaster and Emergency Medicine 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Conflicts of interest: none

References

Brown, S, Archer, P, Krueger, E, Mallonee, S. Tornado-related deaths and injuries in Oklahoma due to the 3 May 1999 tornadoes. WAF. 2002;17(3):343353.Google Scholar
Centers for Disease Control and Prevention (CDC). Tornado-related fatalities — five states, Southeastern United States, April 25–28, 2011, 2012. MMWR. 2012;61(28):529533.Google Scholar
Morton, M, Levy, JL. Challenges in disaster data collection during recent disasters. Prehosp Disaster Med. 2011;26(3):196201.CrossRefGoogle ScholarPubMed
Heim, RT. Electronic Death Registration. PowerPoint presentation. August 2010. https://www.cdc.gov/nchs/ppt/nchs2010/26_trasatti.pdf. Accessed June 10, 2017.Google Scholar
Baker, K. Partnering to Enhance Electronic Death Registration for Disaster Related Deaths. PowerPoint presentation. May 2015. http://www.cste.org/resource/resmgr/DisasterEpi/Baker_Disaster_Epi_Conferenc.pdf. Accessed January 10, 2017.Google Scholar
Rocha, LA, Fromknecht, CQ, Redman, SD, Brady, JE, Hodge, SE, Noe, RS. Medicolegal death scene investigations after natural disaster- and weather-related events: a review of the literature. Acad Forensic Pathol. 2017;7(2):221239.CrossRefGoogle ScholarPubMed
Hanzlick, R, Combs, D. Medical examiner and coroner systems: history and trends. JAMA. 1998;279(11):870874.CrossRefGoogle ScholarPubMed
Hanzlick, R, Parrish, RG. The role of medical examiners and coroners in public health surveillance and epidemiologic research. Ann Rev Public Health. 1996;17:383409.CrossRefGoogle ScholarPubMed
Brunkard, J, Namulanda, G, Ratard, R. Hurricane Katrina deaths, Louisiana, 2005. Disaster Med Public Health Prep. 2009;2(4):215223.CrossRefGoogle Scholar
Choudhary, E, Zane, DF, Beasley, C, et al. Evaluation of active mortality surveillance system data for monitoring hurricane-related deaths - Texas, 2008. Prehosp Disaster Med. 2012;27(4):392397.CrossRefGoogle ScholarPubMed
Howland, RE, Li, W, Madsen, AM, et al. Evaluating the use of an electronic death registration system for mortality surveillance during and after Hurricane Sandy: New York City, 2012. Am J Public Health. 2015;105(11):5562.CrossRefGoogle ScholarPubMed
Johnson, MG, Brown, S, Archer, P, Wendelboe, A, Magzamen, S, Bradley, KK. Identifying heat-related deaths by using medical examiner and vital statistics data: surveillance analysis and descriptive epidemiology– Oklahoma, 1999–2011. Environ Res. 2016;150:3037.CrossRefGoogle Scholar
Olayinka, OO, Bayleyegn, TM, Noe, RS, Lewis, LS, Arrisi, V, Wolkin, AF. Evaluation of real-time mortality surveillance based on media reports. Disaster Med Public Health Prep. 2017;11(4):460466.CrossRefGoogle ScholarPubMed
Zane, DF, Bayleyegn, T, Hellsten, J, et al. Tracking deaths related to Hurricane Ike, Texas, 2008. Disaster Med Public Health Prep. 2011;5(1):2328.CrossRefGoogle Scholar
Personal communication with first author: Kelly Baker, MPH. Oklahoma City, Oklahoma USA: Centers for Disease Control and Prevention; September 19, 2016.Google Scholar
Centers for Disease Control and Prevention (CDC). Disaster Preparedness and Response Training: Complete Course. Participant workbook, 1st edition. Atlanta, Georgia USA: CDC; 2014.Google Scholar
Centers for Disease Control and Prevention (CDC). Death Scene Investigation After Natural Disaster or Other Weather-Related Events Toolkit. First edition. Atlanta, Georgia USA: CDC; 2017.Google Scholar
Coombs, DL, Quenemoen, LE, Parrish, RG, Davis, JH. Assessing disaster-attributed mortality: development and application of a definition and classification matrix. Int J Epidemiol. 1999;28(6):11241129.CrossRefGoogle Scholar
Centers for Disease Control and Prevention (CDC). National Center for Health Statistics. A Reference Guide for Certification of Deaths in the Event of a Natural, Human-Induced, or Chemical/Radiological Disaster. Hyattsville, Maryland USA: CDC; 2017.Google Scholar
Centers for Disease Control and Prevention (CDC). Updated Guidelines for Evaluating Public Health Surveillance Systems: Recommendations from the Guidelines Working Group. MMWR Recomm Rep. 2001;50(RR-13):135.Google Scholar