Good Practices in Social Security Good Practices in Social Security

The identification and sharing of good practices helps social security organizations and institutions to improve their operational and administrative efficiency.

In the context of the ISSA, a good practice is defined as any type of experience (e.g. an action, a measure, a process, a programme, a project, or a technology) implemented within a social security organization that fosters the improvement of its administrative and operational capacities, and/or the efficient and effective delivery of programmes. The good practices selected by the ISSA focus on topics related to the priorities as defined in the programme and budget of the Association. The good practices are from member institutions of the ISSA and are primarily collected through the work of the  ISSA Technical Commissions and the ISSA Good Practice Awards.

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National Health Alarm Services: Predict and prevent the outbreak of infectious diseases through the combination of various big data

National Health Alarm Services: Predict and prevent the outbreak of infectious diseases through the combination of various big data

National Health Insurance Service | Korea, Republic of
National Health Alarm Services: Predict and prevent the outbreak of infectious diseases through the combination of various big data

The National Health Alarm Services (NHAS) of Korea offers various health alarms to the public before the epidemic spreads out rapidly. They combine different data from diverse sources such as national health information from the National Health Insurance Service (NHIS), social networking sites (SNS) such as twitter, blogs, etc., data from Daumsoft Corporation, climate information from the Korea Meteorological Administration (KMA), air pollution information from the Ministry of Environment (MOE), and food poisoning information from the Ministry of Food and Drug Safety (MFDS). Five infectious diseases are continuously monitored, namely, colds, eye diseases, food poisoning, dermatitis and asthma. Data from each organization are merged into one to make this system successful. Data are then analysed for disease prediction using pre-defined formulas, the disease prediction accuracy of which is currently 90 per cent. People can access the alarm services through the Internet or television news easily. This method and system can be adapted by other countries if they have the appropriate data.

Implementation year2019
Topics: Service quality, Information and communication technology
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