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Purpose: The aim was to critically appraise, synthesise and present the evidence of medication errors amongst hospitalised patients in Middle Eastern countries, specifically prevalence, nature, severity and contributory factors. Methods: CINAHL, Embase, Medline, Pubmed and Science Direct were searched for studies published in English from 2000 to March 2018, with no exclusions. Study selection, quality assessment (using adapted STROBE checklists) and data extraction were conducted independently by two reviewers. A narrative approach to data synthesis was adopted; data related to error causation were synthesised according to Reason's Accident Causation model. Results: Searching yielded 452 articles, which were reduced to 50 following removal of duplicates and screening of titles, abstracts and full-papers. Studies were largely from Iran, Saudi Arabia, Egypt and Jordan. Thirty-two studies quantified errors; definitions of 'medication error' were inconsistent as were approaches to data collection, severity assessment, outcome measures and analysis. Of 13 studies reporting medication errors per 'total number of medication orders'/ 'number of prescriptions', the median across all studies was 10% (IQR 2–35). Twenty-four studies reported contributory factors leading to errors. Synthesis according to Reason's model identified the most common being active failures, largely slips (10 studies); lapses (9) and mistakes (12); error-provoking conditions, particularly lack of knowledge (13) and insufficient staffing levels (13) and latent conditions, commonly heavy workload (9). Conclusion: There is a need to improve the quality and reporting of studies from Middle Eastern countries. A standardised approach to quantifying medication errors' prevalence, severity, outcomes and contributory factors is warranted. [ABSTRACT FROM AUTHOR]

This study investigated the correlation of thermodynamic parameters with the regional averaged lightning flash density in southwest Iran based on OTD/LIS observations and reanalysis datasets from 1996 to 2014. In addition, the most important parameters and their domains were identified for explaining the lightning density variance using a multiple linear regression model. The results showed that surface sensible heat flux over Syria and Jordan, CAPE over southwest Iran, sea surface temperature over the Arabian Sea, and latent heat flux over Northeastern Europe are the best parameters to predict the lightning density in winter. While in spring, CAPE over southwest Iran, the surface sensible heat flux over northeast Iran and the Arabian Sea, and air surface temperature over the Saudi Arabian Peninsula are the main factors for predicting lightning density. The regression models explain almost 90% and 93% of the lightning variability in winter and spring, respectively. The local effect of CAPE and low-level wind shear on lightning activity is more important in spring than in winter, indicating that the contribution of local lightning-generating convective activity is higher in spring. The correlation coefficient between humidity indices and lightning density showed that western moisture sources have a more important role in providing moisture to convection and lightning in winter than in spring. It is worth noting that the wind speed of jet streams at 300 hPa is positively correlated with lightning activity in winter, although their contribution to the multiple linear regression model is negligible. [ABSTRACT FROM AUTHOR]