scholarly journals Existing Data Sources in Clinical Epidemiology: The Taiwan National Health Insurance Laboratory Databases

2021 ◽  
Vol Volume 13 ◽  
pp. 175-181
Author(s):  
Po-Chang Lee ◽  
Feng-Yu Kao ◽  
Fu-Wen Liang ◽  
Yi-Chan Lee ◽  
Sheng-Tun Li ◽  
...  
Keyword(s):  
Health Insurance ◽  
National Health Insurance ◽  
National Health ◽  
Clinical Epidemiology ◽  
Data Sources ◽  
Taiwan National Health Insurance ◽  
Existing Data

Non-Traditional Data Mining Applications in Taiwan National Health Insurance (NHI) Databases

2017 ◽  
Vol 12 (4) ◽  
pp. 31-51
Author(s):  
Joseph Tan ◽  
Fuchung Wang
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Health Insurance ◽  
Decision Support ◽  
National Health Insurance ◽  
National Health ◽  
Domain Knowledge ◽  
Lessons Learned ◽  
Application Systems ◽  
Taiwan National Health Insurance

This study examines time-sensitive applications of data mining methods to facilitate claims review processing and provide policy information for insurance decision-making vis-à-vis the Taiwan National Health Insurance (NHI) databases. In order to obtain the best payment management, a hybrid mining (HM) approach, which has been grounded on the extant knowledge of data mining projects and health insurance domain knowledge, is proposed. Through the integration of data warehousing, online analytic processing, data mining techniques and traditional data analysis in the healthcare field, an easy-to-use decision support platform, which will assist in directing the health insurance decision-making process, is built. Drawing from lessons learned within a case study setting, results showed that not only is HM approach a reliable, powerful, and user-friendly platform for diversified payment decision support, but that it also has great relevance for the practice and acceptance of evidence-based medicine. Essentially, HM approach can provide a critical boost to health insurance decision support; hence, future researchers should develop and improve the approach combined with their own application systems.

Non-Traditional Data Mining Applications in Taiwan National Health Insurance (NHI) Databases

2017 ◽  
pp. 666-688
Author(s):  
Joseph Tan ◽  
Fuchung Wang
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Health Insurance ◽  
Decision Support ◽  
National Health Insurance ◽  
National Health ◽  
Lessons Learned ◽  
Policy Information ◽  
Taiwan National Health Insurance ◽  
Mining Projects

This study examines time-sensitive applications of data mining methods to facilitate claims review processing and provide policy information for insurance decision-making vis-à-vis the Taiwan National Health Insurance (NHI) databases. In order to obtain the best payment management, a hybrid mining (HM) approach, which has been grounded on the extant knowledge of data mining projects and health insurance domain knowledge, is proposed. Through the integration of data warehousing, online analytic processing, data mining techniques and traditional data analysis in the healthcare field, an easy-to-use decision support platform, which will assist in directing the health insurance decision-making process, is built. Drawing from lessons learned within a case study setting, results showed that not only is HM approach a reliable, powerful, and user-friendly platform for diversified payment decision support, but that it also has great relevance for the practice and acceptance of evidence-based medicine. Essentially, HM approach can provide a critical boost to health insurance decision support; hence, future researchers should develop and improve the approach combined with their own application systems.

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