Assessing the agility of hospitals in disaster management: application of interval type-2 fuzzy Flowsort inference system

Abstract

Disaster management is one of the most important issues in service organizations, especially in healthcare sector. Due to the occurrences of natural or human-made incidents, requirements of assistance and rescue increase gradually. Hospitals have the vital role in addressing these requirements and therefore should enhance their skill to provide a punctual and appropriate response to these events. An important prerequisite for this level of responsiveness is agility. This study aims to introduce and implement a new approach in order to estimate the agility level of hospitals in disaster management. Founded on the four phases of disaster management, a hospital agility framework is established which showcases the relations between hospital agility factors and phases of disaster management. A new Flowsort-based approach is also introduced through the integration of the conventional Flowsort method with interval type-2 fuzzy sets. This approach is applied for a case study consisting of 30 hospitals seeking to improve their agility in disasters. We use upper and lower control limits (UCL and LCL) to define the categories of Flowsort method. The results show that 40% of the hospitals position in between the $$ \pm \,2\delta $$ and $$ \pm \,3\delta $$ limits, i.e., the best and the worst categories. Results also approve the ability of the proposed method in evaluation of hospitals based on their agility factors and represent a geographical observation on the hospitals. Some indications about required actions for hospitals of each category in order to increase or maintain their agility level in disaster management are also provided.