فهرست مطالب mohsen shanoofi

Industrial and occupational accidents mostly have adverse consequences. Analyzing the accidents to identify how and why they happened has been one of the key subjects in safety engineering. Tripod-Beta model is one of the most widely-used models for accidents investigation, which step by step identifies the causes of accidents occurrence. However, the role of human factors, as one of the most important causes of accidents, has not noticeably been addressed in this model. Therefore, the aim of the present study was to enhance Tripod-Beta model based on human factors engineering.

In this research, Tripod-Beta model has been enhanced applying TRACEr in a way that the improved model is able to identify and analyze the human errors involved in accidents occurrence in terms of four elements: external error modes, internal error modes, psychological error mechanisms and performance shaping factors. The new model was then applied to investigate some of the accidents happened in Esfahan’s Mobarakeh Steel Company.

In the enhanced model, two tables of “external-based human error” including 5 preconditions and 11 underlying causes, and “internal-based human error” including 7 preconditions and 11 underlying causes have been added to the primary model. Also, one group named “human factors” has been incorporated into the basic risk factors of the old model.

Considering the applicability of the new model to investigate the selected accidents, the meaningfulness of the results of the accidents analyses, and also the capability of the model in identifying the accidents causes related to human factors, this can be inferred that the enhanced model has the appropriate validity.

Human error has been identified as a main cause of most of the major accidents in the world. In order to reduce human errors in the risk assessment and management, it is necessary to assess the risks resulting from human errors which can be guaranteed by conducting human reliability analysis. In the healthcare industry, each year many patients are losing their lives because of clinical errors. Clinical errors, as a global problem, have recently been turned into a challenging issue in various healthcare sector cares. Thissurvey is an analytical-descriptive study, where SHERPA method was used for analyzing human errors in CCU unit of Tehran's Naft hospital. In total, 450 errors were identified in CCU unit, from which 242 errors (45%) were related to nursing actions, 43 errors (9%) belonged to general practitioners, and 165 errors (37%) were for medical specialists. Also, according to the results of the risk analysis, 12.45% of errors were unacceptable, 30.22% had undesirable risk level, 43.11% were identified with acceptable risk level requiring revision, and 14.22% had acceptable risk level without a need for revision. In the end, it can be concluded that SHERPA method is an appropriate method to be used in the healthcare industry as it is very effective in identifying and analyzing human errors.

Numerous studies have shown that human error is the main factor in the occurrence of occupational accidents. Diversity of a job’s different aspects, nature of the job and its complexity, can negatively affect a worker’s performance and behavior, thus leading to unsafe acts in a working environment. This also causes workers to intentionally or unintentionally make errors, which itself can be a reason of occupational accidents.
This study is an analytical- descriptive research, where Barrier Analysis (BA) technique has been applied to identify and analyze the nurses’ human errors in the CCU ward of NIOC Tehran hospital.
The results of the BA checklists presented 57 barriers classified in 8 groups: administrative barriers (14%), procedural actions (18%), human actins (10%), supervisory and co-working barriers (20%), training (10%), natural barriers (0%), physical barriers (10%) and environmental design (18%). Also, 38 barrier breakers and 32 corrective actions were identified.
It can be concluded that BA technique is an appropriate technique to be used in the healthcare and therapy industry as it is helpful in the identification of human error protection layers.