Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-23T10:29:17.940Z Has data issue: false hasContentIssue false

Making Disaster Care Count: Consensus Formulation of Measures of Effectiveness for Natural Disaster Acute Phase Medical Response

Published online by Cambridge University Press:  16 September 2014

Rajesh K. Daftary*
Affiliation:
Baylor College of Medicine, Department of Pediatrics, Section of Emergency Medicine, Houston, TexasUSA The George Washington University School of Medicine and Health Sciences, Department of Pediatrics and Emergency Medicine, Washington, D.C.USA
Andrea T. Cruz
Affiliation:
Baylor College of Medicine, Department of Pediatrics, Section of Emergency Medicine, Houston, TexasUSA
Erik J. Reaves
Affiliation:
US Naval Medical Research Unit No. 6, Lima, Peru
Frederick M. Burkle Jr.
Affiliation:
Harvard Humanitarian Initiative, Harvard School of Public Health, Cambridge, MassachusettsUSA
Michael D. Christian
Affiliation:
Critical Care & Infectious Diseases Mount Sinai Hospital & University Health Network, Toronto, OntarioCanada Royal Canadian Air Force, National Defence, Canada Faculty of Medicine and Dalla Lana School of Public Health, University of Toronto, OntarioCanada
Daniel B. Fagbuyi
Affiliation:
The George Washington University School of Medicine and Health Sciences, Department of Pediatrics and Emergency Medicine, Washington, D.C.USA
Andrew L. Garrett
Affiliation:
Department of Health and Human Services, Office of the Assistant Secretary of Preparedness and Response, Washington, DCUSA
G. Bobby Kapur
Affiliation:
Baylor College of Medicine, Department of Emergency Medicine, Houston, TexasUSA
Paul E. Sirbaugh
Affiliation:
Baylor College of Medicine, Department of Pediatrics, Section of Emergency Medicine, Houston, TexasUSA City of Houston, Emergency Medical Services, TexasUSA
*
Correspondence: Rajesh K. Daftary, MD George Washington University School of Medicine Department of Pediatrics Division of Emergency Medicine 111 Michigan Ave, NW Washington, DC 20010 USA E-mail [email protected]

Abstract

Introduction

No standard exists for provision of care following catastrophic natural disasters. Host nations, funders, and overseeing agencies need a method to identify the most effective interventions when allocating finite resources. Measures of effectiveness are real-time indicators that can be used to link early action with downstream impact.

Hypothesis

Group consensus methods can be used to develop measures of effectiveness detailing the major functions of post natural disaster acute phase medical response.

Methods

A review of peer-reviewed disaster response publications (2001-2011) identified potential measures describing domestic and international medical response. A steering committee comprised of six persons with publications pertaining to disaster response, and those serving in leadership capacity for a disaster response organization, was assembled. The committee determined which measures identified in the literature review had the best potential to gauge effectiveness during post-disaster acute-phase medical response. Using a modified Delphi technique, a second, larger group (Expert Panel) evaluated these measures and novel measures suggested (or “free-texted”) by participants for importance, validity, usability, and feasibility. After three iterations, the highest rated measures were selected.

Results

The literature review identified 397 measures. The steering committee approved 116 (29.2%) of these measures for advancement to the Delphi process. In Round 1, 25 (22%) measures attained >75% approval and, accompanied by 77 free-text measures, graduated to Round 2. There, 56 (50%) measures achieved >75% approval. In Round 3, 37 (66%) measures achieved median scores of 4 or higher (on a 5-point ordinal scale). These selected measures describe major aspects of disaster response, including: Evaluation, Treatment, Disposition, Public Health, and Team Logistics. Of participants from the Expert Panel, 24/39 (63%) completed all rounds. Thirty-three percent of these experts represented international agencies; 42% represented US government agencies.

Conclusion

Experts identified response measures that reflect major functions of an acute medical response. Measures of effectiveness facilitate real-time assessment of performance and can signal where practices should be improved to better aid community preparedness and response. These measures can promote unification of medical assistance, allow for comparison of responses, and bring accountability to post-disaster acute-phase medical care. This is the first consensus-developed reporting tool constructed using objective measures to describe the functions of acute phase disaster medical response. It should be evaluated by agencies providing medical response during the next major natural disaster.

DaftaryRK, CruzAT, ReavesEJ, BurkleFMJr, ChristianMD, FagbuyiDB, GarrettAL, KapurGB, SirbaughPE. Making Disaster Care Count: Consensus Formulation of Measures of Effectiveness for Natural Disaster Acute Phase Medical Response. Prehosp Disaster Med. 2014;29(5):1-7.

Type
Original Research
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2014 

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.)

References

1. Poyzner M. World Disasters Timeline. 2013. www.mapreport.com/subtopics/d.html. Accessed August 21, 2012.Google Scholar
2.James, JJ, Subbarao, I, Lanier, WL. Improving the art and science of disaster medicine and public health preparedness. Mayo Clin Proc. 2008;83(5):559-562.Google Scholar
3.Rosborough, S. A tale of two responses: Haiti earthquake highlights the need for training in international disaster response. Disaster Med Public Health Prep. 2010;4(1):21-23.CrossRefGoogle ScholarPubMed
4. Pavignani E, Colombo S. Analysing Disrupted Health Sectors: A Modular Manual. France: World Health Organization: Department of Recovery and Transition Programmes, Health Action in Crisis; 2009.Google Scholar
5.Reaves, EJ, Schor, KW, Burkle, FM Jr. Implementation of evidence-based humanitarian programs in military-led missions: part II. The impact assessment model. Disaster Med Public Health Prep. 2008;2(4):237-244.CrossRefGoogle ScholarPubMed
6.Bradt, DA. Evidence-based decision-making (part II): applications in disaster relief operations. Prehosp Disaster Med. 2009;24(6):479-492.Google Scholar
7.Waller, SG, Ward, JB, Montalvo, M, Cunliffe, C, Beadling, C, Riley, K. A new paradigm for military humanitarian medical operations: mission-generic metrics. Mil Med. 2011;176(8):845-851.Google Scholar
8.Stratton, SJ. The Utstein-style template for uniform data reporting of acute medical response in disasters. Prehosp Disaster Med. 2012;27(3):219.CrossRefGoogle ScholarPubMed
9.Bradt, DA, Aitken, P. Disaster medicine reporting: the need for new guidelines and the CONFIDE statement. Emerg Med Australas. 2010;22(6):483-487.CrossRefGoogle ScholarPubMed
10.Ciottone, G (ed). Disaster Medicine. 3rd ed. Philadelphia, Pennsylvania USA: Elsevier; 2006.Google Scholar
11.The Sphere Project. Humanitarian Charter and Minimum Standards in Humanitarian Response. 3rd ed. Northampton, United Kingdom: The Sphere Project; 2011.Google Scholar
12.Bradt, DA, Drummond, CM. Rapid epidemiological assessment of health status in displaced populations--an evolution toward standardized minimum, essential data sets. Prehosp Disaster Med. 2003;18(1):178-185.Google Scholar
13.Debacker, M, Hubloue, I, Dhondt, E, et al. Utstein-style template for uniform data reporting of acute medical response in disasters. PLoS Curr. 2012;4:e4f6cf3e8df15a.Google ScholarPubMed
14.Leiba, A, Schwartz, D, Eran, T, et al. DISAST-CIR: disastrous incidents systematic analysis through components, interactions and results: application to a large-scale train accident. J Emerg Med. 2009;37(1):46-50.CrossRefGoogle ScholarPubMed
15.Fink, A, Kosecoff, J, Chassin, M, Brook, RH. Consensus methods: characteristics and guidelines for use. Am J Public Health. 1984;74(9):979-983.Google Scholar
16.Chan, JL, Burkle, FM Jr. A framework and methodology for navigating disaster and global health in crisis literature. PLoS Curr. 2013;5:10.1371/currents.dis.9af6948e381dafdd3e877c441527cba0.Google Scholar
17.Kelen, G, Sauer, LM. Trend analysis of disaster health articles in peer-reviewed publications pre- and post-9/11. Am J Disaster Med. 2008;3(6):369-376.Google Scholar
18.Hsu, C, Sandford, B. The Delphi technique: making sense of consensus. PARE. 2007;12(10):1.Google Scholar
19.Powell, C. The Delphi technique: myths and realities. J Adv Nurs. 2003;41(4):376-382.CrossRefGoogle Scholar
20. National Quality Forum. Measure Evaluation Criteria. 2012. http://www.qualityforum.org/docs/measure_evaluation_criteria.aspx. Accessed May 28, 2013.Google Scholar
21.Williams, PL, Webb, C. The Delphi technique: a methodological discussion. J Adv Nurs. 1994;19(1):180-186.CrossRefGoogle ScholarPubMed
22.Jones, J, Hunter, D. Consensus methods for medical and health services research. BMJ. 1995;311(7001):376-380.Google Scholar
Supplementary material: File

Daftary Supplementary Material

Appendix A

Download Daftary Supplementary Material(File)
File 15.3 KB
Supplementary material: PDF

Daftary Supplementary Material

Supplementary Material

Download Daftary Supplementary Material(PDF)
PDF 215.8 KB
Supplementary material: PDF

Daftary Supplementary Material

Supplementary Material

Download Daftary Supplementary Material(PDF)
PDF 212.4 KB
Supplementary material: PDF

Daftary Supplementary Material

Supplementary Material

Download Daftary Supplementary Material(PDF)
PDF 197 KB
Supplementary material: File

Daftary Supplementary Material

Appendix B

Download Daftary Supplementary Material(File)
File 17.3 KB
Supplementary material: File

Daftary Supplementary Material

Appendix C

Download Daftary Supplementary Material(File)
File 17.1 KB