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Evidence-Based Decision-Making (Part II): Applications in Disaster Relief Operations

Published online by Cambridge University Press:  28 June 2012

David A. Bradt*
Affiliation:
Center for Refugee and Disaster Response, Johns Hopkins Medical Insitutions, Baltimore, Maryland USA
*
Center for Refugee and Disaster ResponseJohns Hopkins Medical InsitutionsMarburg B-187600 North Wolfe Street Baltimore, Maryland 21287-2080 USA E-mail: [email protected]

Abstract

Recognized limitations to data in disaster management have led to dozens of initiatives to strengthen data gathering and decision-making during disasters. These initiatives are complicated by fundamental problems of definitions of terms, ambiguity of concepts, lack of standardization in methods of data collection, and inadequate attempts to strengthen the analytic capability of field organizations. Cross-cutting issues in needs assessment, coordination, and evaluation illustrate additional recurring challenges in dealing with evidence in humanitarian assistance. These challenges include lack of agency expertise, dyscoordination at the field level, inappropriate reliance on indicators that measure process rather than outcome, flawed scientific inference, and erosion of the concept of minimum standards.

Decision-making in disaster management currently places a premium on expert or eminence-based decisions. By contrast, scientific advances in disaster medicine call for evidence-based decisions whose strength of evidence is established by the methods of data acquisition. At present, disaster relief operations may be data driven, but that does not mean that they are soundly evidence-based.

Options for strengthening evidence-based activities include rigorously adhering to evidenced-based interventions, using evidence-based tools to identify new approaches to problems of concern, studying model programs as well as failed ones to identify approaches that deserve replication, and improving standards for evidence of effectiveness in disaster science and services.

Type
Applied Research
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2009

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References

1. UN Office for the Coordination of Humanitarian Affairs: Terms of Reference for Humanitarian Needs: building blocks toward a common approach to needs assessment and classification. October 17, 2007. Unpublished. Available from OCHA Policy Development and Studies Branch, New York, USA.Google Scholar
2. Mock, N, Garfield, R: Health tracking for improved humanitarian performance. Prehosp Disaster Med 2007;22(5):377383.CrossRefGoogle ScholarPubMed
3. Richardson, WS, Wilson, MC, Nishikawa, J, Hayward, RSA. The well-built clinical question: A key to evidence-based decisions. ACP Journal Club 1995;123:A12.CrossRefGoogle ScholarPubMed
4. Roundtable on Humanitarian-Military Sharing: Good Practices: Information Sharing in Complex Emergencies. Worldwide Civil Affairs Conference. United States Institute of Peace, 2001. Available at http://www.usip.org/virtualdiplomacy/publications/reports/11.html. Accessed April 2003.Google Scholar
5. Adinolfi, C, Bassiouni, D, Lauritzsen, HF, Williams, HR: Humanitarian Response Review. New York and Geneva: United Nations, 2005.Google Scholar
6. Office of UN Deputy Special Representative of the UN Secretary-General for Sudan, and the UN resident and Humanitarian coordinator. Darfur Humanitarian Profile No.7.October 1,2004. Available from the UN Office for the Coordination of Humanitarian Affairs or http://www.humanitarianinfo.org/darfur/infocentre/HumanitarianProfile/hp2004.asp. Accessed November 2007.Google Scholar
7. Medècins sans Frontières: Refugee Health—An Approach to Emergency Situations. Hong Kong: Macmillan Education, 1997.Google Scholar
8. El Sakka, H: Update on acute jaundice syndrome (AJS) cases. July 29, 2004. Unpublished. Available from World Health Organization, Geneva.Google Scholar
9. Sphere Project: Humanitarian Charter and Minimum Standards in Disaster Response. Geneva: The Sphere Project, 2004.Google Scholar
10. Darcy, J, Hofman, CA: According to need? Needs assessment and decisionmaking in the humanitarian sector. Humanitarian Policy Group Report 15, September 2003. London: Overseas Development Institute, 2003. Available at http://www.odi.org.uk/HPG/papers/hpgreport15.pdf. Accessed October 2007.Google Scholar
11. de Ville de Goyet, C, Moriniere, LC for the Tsunami Evaluation Coalition: The Role of Needs Assessment in the Tsunami Response. London: Tsunami Evaluation Coalition, 2006. Available from ALNAP c/o the Overseas Development Institute.Google Scholar
12. Willitts-King, B: Practical approaches to needs-based allocation of humanitarian aid—a review for Irish Aid on donor approaches. July 31, 2006. Unpublished. Available from Irish Aid or the author.Google Scholar
13. Bradt, DA, Drummond, CM: Rapid epidemiological assessment of health status in displaced populations—An evolution towards standardized minimum, essential data sets. Prehosp Disaster Med 2002;17(4)178185.CrossRefGoogle Scholar
14. Inter-Agency Standing Committee: Guidance note on using the cluster approach to strengthen humanitarian response.24 November 2006. Available at http://www.reliefweb.int/humanitarianreform/IASC%20GUIDANCE%20NOTE%20ON%20CLUSTER%20APPROACH.pdf. Accessed January 2007.Google Scholar
15. Bennett, J, Bertrand, W, Harkin, C, et al. : Coordination of International Humanitarian Assistance in Tsunami-Affected Countries. London: Tsunami Evaluation Coalition, 2006. Available from ALNAP c/o the Overseas Development Institute.Google Scholar
16. Tufte, ER: The Visual Display of Quantitative Information. 2d ed. Cheshire, CT: Graphics Press LLC, 2001.Google Scholar
17. Tufte, ER: Visual and Statistical Thinking: Displays of Evidence for Making Decisions. Cheshire, CT: Graphics Press LLC, 1997.Google Scholar
18. Birnbaum, ML: Professionalization and credentialing. Prehosp Disaster Med 2005;20(4):210211.CrossRefGoogle ScholarPubMed
19. Seynaeve, G, Archer, F, Fisher, J, et al. : International standards and guidelines on education and training for the multi-disciplinary health response to major events which threaten the health status of a community. Prehosp Disaster Med 2004;19(2, s2):s17–s30.Google ScholarPubMed
20. Hallam, A: Evaluating Humanitarian Assistance Programmes in Complex Emergencies. Good Practice Review 7. London: Overseas Development Institute, 1998.Google Scholar
21. World Bank Operations Evaluation Department: OED and impact evaluation— A discussion note. Available at http://www.worldbank.org/ieg/docs/world_bank_oed_impact_evaluations.pdf. Accessed December 2007.Google Scholar
22. Hofmann, CA, Roberts, L, Shoham, J, Harvey, P. Measuring the impact of humanitarian aid: a review of current practice. Humanitarian Policy Group Research Report 17, June 2004. London: Overseas Development Institute, 2004. Available at http://www.odi.org.uk/hpg/papers/HPGReport17.pdf. Accessed October 2007.Google Scholar
23. Burkle, FM: Complex humanitarian emergencies: III. Measures of effectiveness. Prehosp Disaster Med 1995;10(1):4856.CrossRefGoogle ScholarPubMed
24. Duflo, E, Kremer, M: Use of randomization in the evaluation of development effectiveness. Paper prepared for the World Bank Operations Evaluation Department Conference on Evaluation and Development Effectiveness, July 15-16, 2003. Unpublished. Available from the World Bank. Accessed December 2007.Google Scholar
25. Savedoff, WD, Levine, R, Birdsall, N for the Evaluation Gap Working Group: When Will We Ever Learn? Improving Lives through Impact Evaluation. Washington, DC: Center for Global Development, 2006.Google Scholar
26. Cosgrave, J for the Tsunami Evaluation Coalition: Synthesis report: Expanded summary. Joint evaluation of the international response to the Indian Ocean tsunami. London: Tsunami Evaluation Coalition, 2006. Available from ALNAP c/o the Overseas Development Institute.Google Scholar
27. Golden, M, Brennan, M, Kaiser, R, et al. : Measuring mortality, nutritional status and food security in crisis situations: SMART methodology version 1. June 2005. Available at http://www.smartindicators.org/. Accessed February 2007.Google Scholar
28. International Rescue Committee Health Unit: IRC Community Treatment Program Progress Report, September 2007. Unpublished. Available from the International Rescue Committee, New York, New York, USA.Google Scholar
29. Leaning, J: The dilemma of neutrality. Prehosp Disaster Med 2007;22(5):418421.CrossRefGoogle ScholarPubMed
30. Water and Sanitation for Health: Lessons Learned in Water, Sanitation, and Health: Thirteen Years of Experience in Developing Countries. Arlington, VA: Water and Sanitation for Health Project, 1993.Google Scholar
31. Laxminarayan, R, Mills, AJ, Breman, JG, et al. : Advancement of global health: key messages from the Disease Control Priorities Project. Lancet 2006;367:11931208.CrossRefGoogle ScholarPubMed
35. Aldis, W, Schouten, E: War and public health in the Democratic Republic of the Congo. Health in Emergencies December 2001;issue 11:4-5. Available from http://www.who.int/hac/about/7527.pdf. Accessed November 2007.Google Scholar
33. Rennie, D. Cost-effectiveness analyses: making a pseudoscience legitimate. JHealth Polit Policy Law 2001; 26:383386.CrossRefGoogle ScholarPubMed
34. World Health Organization: Humanitarian Health Assistance Component Summary, Yogyakarta Special District 08 June 2006. Adapted from Bradt DA: Ambon health situation report. August 2000. WHO Department of Emergency and Humanitarian Action Situation Reports for Indonesia (Maluku). Available at http://www.who.int/disasters/repo/5853.doc. Accessed November 2007.Google Scholar