Lesson learned in the development of health datasets on the issue of PM2.5

Abstract

Currently, the health database needs to be more developed to link public health data with air pollution and fine particles or PM_2.5 in Thailand. Unlink data is resulting in delays in analyzing health effects associated with PM_2.5 and managing the early implementation of health promotion interventions. Therefore, the health dataset on the issue of PM_2.5 is an important tool for collecting health information on the population, especially in high-risk group populations, including children, older adults, pregnant women, and people with underlying diseases, as well as air pollution problems, particularly PM_2.5. This dataset will be analyzed to identify the relationship between PM_2.5 ​and illness in 4 different disease groups, including respiratory diseases, cardiovascular diseases, eye and skin inflammation which will be used to promote knowledge and behavior in preventing PM_2.5, plan for health services, and health policy recommendation in accordance with the trends in health problems. Lesson learned is one method of managing knowledge. It is the process of extracting the knowledge gained and using it for knowledge development to improve the working strategies in developing health datasets. The lessons learned in developing health datasets will result in helpful knowledge that can be used as a model for health operations and services in other areas.