How are different leadership behaviours perceived and enacted in emergency medical departments in Saudi Arabian public hospitals?

Leadership behaviours play a key role in achieving organisational success. Leadership is commonly perceived as a world-wide concept throughout different countries; however, the way in which it is conceptualised and operationalised is viewed as culturally specific. Existing leadership research often overlooks the impact of context (Bryman et al. 1996; Denise and Yitzhak 2001; Osborn et al. 2002) and culture (Hofstede 2001; House et al. 2004) on leadership and its effectiveness. Leadership research is mainly the product of models and constructions developed in Western cultures, while little is understood about leadership in other cultures (Tsui 2004). Dickson et al. (2012) argue that most leadership models have a North-American bias, an orientation which has caused many academics to recognise the importance of investigating leadership approaches and characteristics in non-Western contexts. The current research aims to identify, characterise and explain the dynamics of leadership behaviours as these are understood and operationalised by the managers of hospital emergency departments in Saudi Arabia. A constructionist research philosophy is adopted in this research. This study employs qualitative research methods to investigate the leadership behaviours used by managers in hospital-based emergency departments. The research employed a purposive sampling method to recruit participants from five hospital emergency departments located in three urban cities in Saudi Arabia. A total of 30 participants were recruited for the study between May and September, 2015; data were gathered via semi-structured interviews. The participants were 15 managers and 15 medical staff. Managers included the heads of emergency departments, their deputies and head nurses. Medical staff included physicians and nursing staff. Data were analysed using thematic analysis techniques. The findings which emerge from this study are grounded in the data. The themes explored were: a) rewarding leadership, b) responsive leadership, c) role-modelling, d) democratic leadership, e) staff-development leadership, f) recognition leadership, g) supportive leadership, h) lenient leadership and i) strict leadership. Managers use these leadership behaviours to address several contextual factors in emergency departments, including pressure, stress, over-crowding, staff related conflicts, staff-patient-related conflicts, responding to unexpected situations and disciplining staff members who make mistakes that might harm staff or patients. It was found that these different leadership behaviours are mainly influenced by the context of the emergency department and the culture of Saudi Arabia, based on Islamic religion and social norms

Time-Series Analysis and Healthcare Implications of COVID-19 Pandemic in Saudi Arabia

The first case of coronavirus disease 2019 (COVID-19) in Saudi Arabia was reported on 2 March 2020. Since then, it has progressed rapidly and the number of cases has grown exponentially, reaching 788,294 cases on 22 June 2022. Accurately analyzing and predicting the spread of new COVID-19 cases is critical to develop a framework for universal pandemic preparedness as well as mitigating the disease’s spread. To this end, the main aim of this paper is first to analyze the historical data of the disease gathered from 2 March 2020 to 20 June 2022 and second to use the collected data for forecasting the trajectory of COVID-19 in order to construct robust and accurate models. To the best of our knowledge, this study is the first that analyzes the outbreak of COVID-19 in Saudi Arabia for a long period (more than two years). To achieve this study aim, two techniques from the data analytics field, namely the auto-regressive integrated moving average (ARIMA) statistical technique and Prophet Facebook machine learning technique were investigated for predicting daily new infections, recoveries and deaths. Based on forecasting performance metrics, both models were found to be accurate and robust in forecasting the time series of COVID-19 in Saudi Arabia for the considered period (the coefficient of determination for example was in all cases more than 0.96) with a small superiority of the ARIMA model in terms of the forecasting ability and of Prophet in terms of simplicity and a few hyper-parameters. The findings of this study have yielded a realistic picture of the disease direction and provide useful insights for decision makers so as to be prepared for the future evolution of the pandemic. In addition, the results of this study have shown positive healthcare implications of the Saudi experience in fighting the disease and the relative efficiency of the taken measures