MODERN APPROACHES TO OCCUPATIONAL RISK MANAGEMENT BASED ON DECISION-SUPPORT INFORMATION TECHNOLOGIES

The paper considers issues related to the dependence of morbidity on harmful factors in the workplace; proposes a method based on comparative analysis of binary samples. The method presupposes preliminary binarization of data; however, in our study preliminary binarization was not required because the data were already binary (presence or absence of a given diagnosis in a particular individual). The work shows that this method can improve medical diagnostics by using digital technologies and support correct managerial decision-making; substantiates the timeliness of applying this methodology to expand and combine data-processing methods that accumulate in medical information systems. Data from medical information systems contain empirical information on patients’ health, which can be used to model physiological processes and to construct models of the accumulation of functional impairments in the body in relation to occupational factors. Applying the method to real data reveals diagnoses that occur significantly more frequently in the studied groups, which makes it possible to analyze whether these diagnoses are associated with the presence of a harmful occupational factor. The proposed method is appropriate for analyzing the effectiveness of decisions taken. This methodology is recommended as a basis for a software system to determine the dependence of workers’ occupational morbidity on harmful working conditions.