An integrated experiment for identification of best decision styles and teamworks with respect to HSE and ergonomics program: The case of a large oil refinery

An integrated approach for evaluating and improving the performance of hospital ICUs based on ergonomic and work-motivational factors

The intensive care unit (ICU) holds significant importance in hospitals. Primarily concerned with monitoring and providing care to critically ill patients, the ICU has proven effective in reducing mortality rates and minimizing complications of diseases, thanks to the highly complex and specific measures taken within this department. Considering the unique contributions made by the staff in this unit, its performance assessment can help improve patient care and satisfaction. This study presents a framework that utilizes ergonomic and work-motivational factors (WMFs) to assess the performance of various ICUs. Upon the identification of these indicators, a standard questionnaire is developed to collect the required data. The mean efficiency score of the units is then determined using the data envelopment analysis (DEA). The model is validated using the principal component analysis (PCA). Ultimately, the SWOT (strengths, weaknesses, opportunities, and threats) matrix is employed to formulate an appropriate strategy and offer improvement measures to the managerial team to enhance their ICU performance. The proposed framework can be applied to evaluate the performance of other healthcare departments. Among the studied ICU centers, including general ICU, isolation ICU catering to individuals with infectious diseases, cardiac care unit (CCU), and neonatal ICU (NICU). NICU and general ICU have the best and worst performance in terms of macro- and micro-ergonomic and motivational indicators, which are on average 0.826% more elevated and 0.659% lower, respectively. According to the performed sensitivity analysis, the ICUs in question demonstrate the most appropriate and inappropriate performance about the indicators of "knowledge, situation assessment, and situation analysis" and "work stress", respectively.

A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area

Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries.