Background: Identification of the factors contributing to the errors of medical staff and examining the causal relationships among those factors can help better manage and design more effective policies and practices. Objectives: This study aimed to identify the causes and factors affecting medical error management and determine a model for better management of such errors. Methods: This descriptive-analytical study was conducted in two qualitative and quantitative phases. In the quantitative part of the study, the factors related to medical error management were identified and validated through reviewing previous studies and interviewing some specialists. Following that, the fuzzy decision-making trial and evaluation method was used for structural modeling of the factors and investigating the causal relationships among them in the quantitative part. Results: In this study, the results showed that the "education and learning from error" subfactor had the most significant impact on the system. The second highly effective subfactors in the management of medical errors were "organizational communication and improved information access", "safety culture and climate", and "policies, procedures, and guidelines". In addition, the "safety culture and climate" was the most important factor that had the most critical impact on the system. Moreover, the "handoff conversations and communication" subfactor was mostly influenced by the other factors, followed by the "incident reporting system", "error prevention and corrective measures", "safety culture and climate", and "individuals' participation". Conclusions: According to the results of this study, the health care industry should take into consideration both organizational and individual factors in error management. In order to achieve better planning and higher performance in error management, increase patient safety, and ultimately improve the quality of hospital services, it is suggested to consider the causes and factors affecting the system.

BACKGROUND: Environmental hazards in healthcare institutions affect the quality of patient care as well as personnel and patient safety. OBJECTIVE: The aim of this study was to develop and apply a semi-quantitative risk assessment method to calculate occupational health risk levels with regard to the sensitivities of healthcare institutions. METHODS: The present research was conducted in three phases. In phases 1 and 2, the model was developed using a review of different risk assessment methods, extracting expert opinions (N = 10) through semi-structured interviews, and using the fuzzy analytical hierarchy process (FAHP). In phase 3, in order to validate the proposed method, one of the five public hospitals was randomly selected and a case study comprising 6 sections was performed. RESULTS: A total of 43 health risks were identified and evaluated using the present method, 41.86% of which were at very high levels, 16.27% at high levels, 30.23% at substantial ones, 9.3% at medium and 2.32% at low levels. The highest health risks were found in paraclinical and operating room wards. CONCLUSION: To overcome the shortcomings of the proposed health risk assessment methods, a semi-quantitative method was used in the present study to more accurately calculate the risk levels in the healthcare institutions and also calculate the risk level of each hospital unit. The proposed semi-quantitative method can be used as a tool for assessing occupational health risks as a key element of risk management. In addition, by focusing on an appropriate framework for occupational health risk assessment, specialists in the organization will be able to take significant and effective steps to implement an efficient risk management system.