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Updated: May 17, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Development of a water-related disaster decision model for nurses in Thailand
Ann Jirapongsuwan1, Andrew J Englande, Peter J Fos
1Department of Public Health Nursing, Faculty of Public Health, Mahidol University, Bangkok, Thailand. ann.jir@mahidol.ac.th
Background:
Disasters, be they natural or manmade, are catastrophic events that confront nursing managers with the challenge of acting to reduce the impact of such events upon society as a whole.
Objective:
Provide nursing management personnel with a guide organized in such a fashion as to facilitate the decision making process in water related disasters. To develop a model to guide the decision-making process regarding water-related disaster management.
Material And Method:
The combination of the two-round of modified Delphi method and The Simple Multi-attribute Rating Technique (SMART) was used to develop a decision tool. Thirty-four experts, including nurses, physicians and manager from three hospitals situated in previous disaster zones participated in this project. Delphi consensus was reached when the mean score of agreement was above 4.0 and standard deviation was below 1.0. Kendall's Coefficient of Concordance and the Kruskal Wallis H-test were performed to determine the degree of agreement and association of criteria rankings.
Results:
The 36 variables were constructed with seven alternatives: policy, communications, materials, human resource management, operation effectiveness, health and stakeholder participation. An agreement in attribute ranking among the experts was found. The trade-off scores of model variables were presented to identify feasible arrays of disaster planning needs.
Conclusion:
The authors proposed a practical method to develop a decision model based on the input of key individuals in disaster management. The model can be used to guide the decision making for nurse managers resulting in the best practice for water-related disaster management.
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