Assessment the Resilience of the Healthcare Network in Accidents and Chemical Crises

Healthcare networks in industrial areas are the main pillars of preventing and coping with chemical accidents and crises, which are of great importance in improving their level of resilience. In order to achieve this goal, it is necessary to apply a precise method for assessing and empowering these centers. The purpose of this study was to provide a resiliency pattern for these centers in accidents and chemical crises.

The present research is a combined study (quantitative - qualitative) study of the applied type. In the first phase, the indicators of resilience assessment were extracted from internal and international literature and confirmed by content validity. Then, in the next phase, the questionnaire was designed and computed based on the extracted indicators and was approved by the experts. Finally, by designing quantitative criteria for analyzing the results of healthcare networks assessment in disasters and crises, a model for assessment and empowerment of the health system in disasters and crises was presented.

Based on the literature review and the methodology, 12 indicators were extracted for assessing healthcare networks in chemical accidents and crises. Content validity (CVI = 0.85 and CVR = 1) of all indicators was confirmed, then using the questionnaire on the weight of each indicator was identified in the score of the total score (100 points). The quantification methods of the 12 indicators developed by the expert group were confirmed. Finally, an evaluation and capability model for these networks were developed.

According to the results, the pattern of healthcare networkschr('39') resilience in chemical disasters and crises was divided into three stages before, during and after the crisis in 12 indicators of chemical hazards, structure status, documentation analysis, capacity and facilities, training, exercises, human capital, management systems, crisis management, communications, accident analysis, and audit and monitoring with relevant sub-groups.