Benchmarking rate of members of the crisis and disaster management committee in Iranian public hospitals

Pirhossein Kolivand | Mohammad esmaeil Motlagh | Hasan Ashrafian Amiri | Seyed Farzad Jalali | Homa Yousefi Khoshsabegheh | Seiyed Davoud Nasrollahpour Shirvani | Nafise Beigom Mirkatooli | mostafa javanian

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=158988
Date :  2021/01/02
Publish in :    مديريت سلامت=Journal of Health Administration
DOI :  https://doi.org/10.29252/jha.23.4.9
Link :  http://dx.doi.org/10.29252/jha.23.4.9
Keywords : Benchmarking, Modeling, Facing disasters, Crisis Management Committee, Disaster Management Committee

Abstract :

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Introduction: Benchmarking is one of the superior methods and processes for performance and organizational improvement. This study was conducted to determine benchmarking rate of disaster management committee members in Iranian public hospitals in effective disaster response. Methods: This cross-sectional study was conducted in 2018. The research community was Iranian public hospitals that were randomly selected based on spatial planning. The data were collected using a researcher-made questionnaire including two parts of individual variables, and amount and technique of benchmarking using 14 open-ended and closed-ended questions. The data were analyzed by SPSS-23 software. Results: Out of 410 members available from the hospital crisis and disaster management committee who were studied, 103 persons (25.1) had from 1 to 8 benchmarking cases during the period of cooperation with this committee, and a total of 237 cases of benchmarking were recorded. Thus, the mean number of benchmarking cases was 0.58±1.2. Thus, the mean score of benchmarking was 0.58±1.2. There was a significant relationship among the number of benchmarking cases and the duration of cooperation in the Disaster Management Committee (P=0.001 & r=+0.177), the number of active beds in the hospital (P=0.024 & r=+0.117), educational level (P=0.029 & r=+0.109), and the city of hospital (28.4 in metropolitan areas and 15.9 in non-metropolitan areas) (P=0.010). Conclusion: This study showed that benchmarking rate per capita among the studied members was in a lower level compared to other similar studies. Therefore, it is suggested that appropriate intervention programs be designed and implemented.