Designing and Validating a Training Model for the Staff of the Incident Command System in the Hospitals

---

Extended Abstract
Background
Disasters are a part of human life and can disrupt people's lives all over the world. One of the disaster response programs tested in recent years is the hospital incident command system, which acts as a management system to increase the effectiveness and efficiency of incident management. Since manpower and expert personnel play an important role in this system, the most important influencing factor in the success of the crisis management process is the preparation of the personnel and the crisis management team. For this purpose, educational models are a tool to maintain the preparation of personnel, increase their ability to achieve certain goals, and help them acquire information, skills, and ways of thinking. The current research aimed to design and validate a training model for the staff of the hospital incident command system.
Methods
The present research was practical in terms of aim. Also, the research method was a qualitative-quantitative (mixed method) approach. The type of study in the qualitative part was content and theme analysis, and in the quantitative part, it was correlation type according to the structural equation modeling method. The data required for the quantitative stage was compiled based on the data of the qualitative stage. The statistical population in the qualitative part included experts in the field of incident command system, and in the quantitative part it included managers and employees of this in the hospitals of Guilan province in Iran. The sampling method in the qualitative part was the purposive model forecasting method. Also, the sampling method was cluster random in the quantitative part. According to the principle of data saturation, the sample size in the qualitative section was 15 people, and in the quantitative section, 226 people were selected based on Cochran's formula. The data collection tool in the qualitative part was a semi-structured interview, and we used a questionnaire extracted from the interview in the quantitative part. The questionnaire was distributed among ten professors to check the relative coefficient and content validity index. Also, the questionnaire was approved by the content validity ratio (CVR) of 0.86 and content validity index (CVI) of 0.92. Also, Cronbach's alpha coefficient and its combined reliability were estimated as 0.84 and 0.79, respectively. For data analysis, we used the MAXQDA2020 and SmartPls3 software in the qualitative part, and SPSS26 software in the quantitative part.
Results
In the process of open coding, out of the 285 primary codes obtained after removing the duplicates, 43 open codes were obtained. Then, we identified 12 indicators as follows: determination of the current situation, determination of prerequisites, feasibility study, determination of strategies, determination of educational content, organization of educational strategy, specialized measures, design and modeling, integration and implementation, support, learner evaluation, and feedback. Finally, in the selective coding stage, the key indicators were categorized as five main components: analysis, policymaking and determining strategies, design, implementation and support, and evaluation and feedback. The quantitative analysis showed that the dimension of policymaking and determining strategies with an impact factor (0.786) had a more significant impact on designing the training model. The analysis dimension had the highest average (4.004) and the lowest standard deviation (SD) (0.577) among the five dimensions. Also, the dimensions of policymaking and determining strategies with a mean (3.278) and SD (0.786), evaluation with a mean (3.308) and SD (0.782), design with a mean (3.732) and SD (0.772), implementation with a mean (4.0003) and SD (0.598) had an impact on pattern design. The results of examining the path coefficient and t index showed that the design dimension was related to the path coefficient (0.987) and t= (176.713) more than the other five dimensions in designing the training model. Then, the dimension of analysis, with the path coefficient (0.934) and t= (44.844), had the greatest impact among the dimensions. Evaluation and feedback, with path coefficient (0.914) and t= (32.058), policymaking and determining strategies, with path coefficient (33.719) and t= (0.913), and implementation and support dimension, with path coefficient (0.848) and t= (21.230), were also in the next ranks. Also, the results showed that all the components had a significant relationship in the pattern design; based on these results, the final pattern was designed in a standard and meaningful state. After designing the final model of the research, the fit of the model was checked with goodness of fit index and the results showed that the final model had a very good fit.
Conclusion
The model presented in this research aimed to provide a framework for developing the process of training the staff of the hospital incident command system. The primary stimulus of the current research was not paying attention to the necessity of providing a local educational model for the incident command system in the healthcare sector. Therefore, the model presented in this research can be used as a basis for identifying the needs related to the training of the staff of the incident command system, and also as a basis for compiling educational programs for the health department of medical sciences universities. It is suggested that a specialized working group be formed in the High Council of Medical Education of the country to train the staff of the incident command system to guarantee and improve the quality of education.