Conceptual foundations of a corporate intelligent risk-based system for analysis, prediction and prevention of occupational and work-related health disorders of workers
Authors:   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Zaitseva N.V. ,   Department of Medical Sciences (Section of Preventive Medicine), Russian Academy of Sciences, 14 Leninskii Ave., Moscow, 119071, Russian Federation, Kiryanov D.A. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Zemlyanova M.A. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Goryaev D.V. ,   Krasnoyarsk Regional Office of the Federal Service for Surveillance over Consumer Rights Protection and Human Wellbeing, 21 Karatanova St., Krasnoyarsk, 660097, Russian Federation, Ustinova O.Yu. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation, Shur P.Z. ,   Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya St., Perm, 614045, Russian Federation
Published: January 2024

The relevance of the study is determined by the strategic interests of the Russian Federation dictating the need to achieve a national priority, which is the development of human potential. Given the ongoing reduction in labor force against a background of depopulation processes, finding a solution to the problem seems especially relevant. The purpose of this study is to develop a scientific conceptual framework for an intelligent risk-based innovative system for analysis, prediction and prevention of occupational and work-related health disorders of workers. This will help substantiate keynote sanitary-hygienic and medical-preventive measures aimed at reducing losses in healthy life expectancy and increasing occupational longevity. The main theoretical idea is based on a unique information-intellectual innovative system for analyzing and predicting cause-and-effect relationships between the effects of harmful and hazardous occupational factors and the resulting health problems of workers, occupational diseases included. The developed predictive digital neural network models, trained on retrospective or actual data on working conditions, health status, socioeconomic conditions and lifestyle factors, are the information and analytical basis for carrying out calculations and assessing the evolution of personal and group (occupation, age, and work records) health risks caused by occupational or work-related diseases in workers. This provides solid grounds for making a forecast of a prevented period of reduction in occupational working capacity associated with working conditions, specifically for each examined occupation, age, and work records. Such forecasts are an eligible information basis for developing and making well-grounded managerial decisions including those concerning sanitary, hygienic and medical preventive measures aimed at preserving occupational longevity. This will significantly increase effectiveness of corporate health-preserving policies.