Identification of Patterns and Factors Affecting the Health of Employees Based on Datamining of Occupational Examinations with the Purpose of Promoting Occupational Health

Background and Objective: Paying attention to the health of workers as a significant part of the population is important as they play an important role in the development of the society, which also has caught the attention of government officials and World Health Organization (WHO). Based on the rules and regulations of workers in different occupations, each year they must undergo certain medical tests and examinations to ensure they have sufficient health to perform their duties. This study aimed to predict the results of examinations, extraction of knowledge and identifying patterns and agents that affect workers' health. Methods: This was a descriptive-analytic study conducted in Tehran among 1267 employees of various occupations who participated in annual examinations of labor medicine in 2017 and 80 variables related to their health and occupational and family background were collected during the examinations. Due to the size and type of data, the C5.0 decision tree method was used to perform data mining and discovery process. Results: Using the C5.0 decision tree, a model with accuracy of 99.05% was introduced. According to this model, variables with the greatest impact on the health of the employees were identified. Hearing status, especially hearing loss at frequencies of 6000 and 4000 Hz, had the greatest impact on the results of employee health examinations. Conclusion: According to the extracted patterns and identification of determinants that had the greatest impact on the result of medical examinations, it is possible to control the specified factors to improve the health of workers.