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This Author published in this journals
All Journal The Indonesian Journal of Community and Occupational Medicine
Eva Suarthana
Research Institute of the McGill University Health Centre, Montreal, Canada
Health Professions Medicine & Pharmacology

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Utilization of Predictive Models for Diagnosis of Occupational Diseases Eva Suarthana; Mikhael Yosia
The Indonesian Journal of Community and Occupational Medicine Vol. 1 No. 3 (2022): ijcom
Publisher : ILUNI MKK FKUI and PRODI MKK FKUI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53773/ijcom.v1i3.39.125-8

Abstract

Predictive models have long been used to assist clinical decision-making in medicine. Predictive models are made to estimate how likely a person is to have a disease (diagnostic model) or will experience a disease (prognostic model). In the field of occupational health, for example, diagnostic models can be used to increase the efficiency of surveillance programs by identifying groups of workers with occupational diseases without using complex and expensive diagnostic tests.Work-related asthma (WRA) is the most common occupational lung disease in industrialized countries and the second most common in developing countries. Around the world, especially in developing countries, diagnosing WRA is still difficult due to the limitations of available diagnostic tests. Specific inhalation challenge (SIC), the best test for diagnosing occupational asthma, is only available in several research centres worldwide.Several questionnaire-based models have been developed to diagnose work-related asthma at both the primary (general practitioner) and secondary (specialist) levels of care. A recent model for diagnosing occupational asthma was developed using data from Canada and has been validated using data from several European countries. A collaboration has been initiated to assess the application of this model among Indonesian workers.
Co-Authors Mikhael Yosia