{"title":"Utilization of health insurance data in an environmental epidemiology","authors":"J. Ha, Seongkyung Cho, Yongseung Shin","doi":"10.5620/eht.e2015012","DOIUrl":null,"url":null,"abstract":"Objectives In South Korea, health insurance data are used as material for the health insurance of national whole subject. In general, health insurance data could be useful for estimating prevalence or incidence rate that is representative of the actual value in a population. The purpose of this study was to apply the concept of episode of care (EoC) in the utilization of health insurance data in the field of environmental epidemiology and to propose an improved methodology through an uncertainty assessment of disease course and outcome. Methods In this study, we introduced the concept of EoC as a methodology to utilize health insurance data in the field of environmental epidemiology. The characterization analysis of the course and outcome of applying the EoC concept to health insurance data was performed through an uncertainty assessment. Results The EoC concept in this study was applied to heat stroke (International Classification of Disease, 10th revision, code T67). In the comparison of results between before and after applying the EoC concept, we observed a reduction in the deviation of daily claims after applying the EoC concept. After that, we categorized context, model, and input uncertainty and characterized these uncertainties in three dimensions by using uncertainty typology. Conclusions This study is the first to show the process of constructing episode data for environmental epidemiological studies by using health insurance data. Our results will help in obtaining representative results for the processing of health insurance data in environmental epidemiological research. Furthermore, these results could be used in the processing of health insurance data in the future.","PeriodicalId":11853,"journal":{"name":"Environmental Health and Toxicology","volume":"60 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Health and Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5620/eht.e2015012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 7
Abstract
Objectives In South Korea, health insurance data are used as material for the health insurance of national whole subject. In general, health insurance data could be useful for estimating prevalence or incidence rate that is representative of the actual value in a population. The purpose of this study was to apply the concept of episode of care (EoC) in the utilization of health insurance data in the field of environmental epidemiology and to propose an improved methodology through an uncertainty assessment of disease course and outcome. Methods In this study, we introduced the concept of EoC as a methodology to utilize health insurance data in the field of environmental epidemiology. The characterization analysis of the course and outcome of applying the EoC concept to health insurance data was performed through an uncertainty assessment. Results The EoC concept in this study was applied to heat stroke (International Classification of Disease, 10th revision, code T67). In the comparison of results between before and after applying the EoC concept, we observed a reduction in the deviation of daily claims after applying the EoC concept. After that, we categorized context, model, and input uncertainty and characterized these uncertainties in three dimensions by using uncertainty typology. Conclusions This study is the first to show the process of constructing episode data for environmental epidemiological studies by using health insurance data. Our results will help in obtaining representative results for the processing of health insurance data in environmental epidemiological research. Furthermore, these results could be used in the processing of health insurance data in the future.