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      Data resource profile: the National Health Insurance Research Database (NHIRD)

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          Abstract

          Electronic health records (EHRs) can provide researchers with extraordinary opportunities for population-based research. The National Health Insurance system of Taiwan was established in 1995 and covers more than 99.6% of the Taiwanese population; this system’s claims data are released as the National Health Insurance Research Database (NHIRD). All data from primary outpatient departments and inpatient hospital care settings after 2000 are included in this database. After a change and update in 2016, the NHIRD is maintained and regulated by the Data Science Centre of the Ministry of Health and Welfare of Taiwan. Datasets for approved research are released in three forms: sampling datasets comprising 2 million subjects, disease-specific databases, and full population datasets. These datasets are de-identified and contain basic demographic information, disease diagnoses, prescriptions, operations, and investigations. Data can be linked to government surveys or other research datasets. While only a small number of validation studies with small sample sizes have been undertaken, they have generally reported positive predictive values of over 70% for various diagnoses. Currently, patients cannot opt out of inclusion in the database, although this requirement is under review. In conclusion, the NHIRD is a large, powerful data source for biomedical research.

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          Most cited references15

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          Nationwide Population Science: Lessons From the Taiwan National Health Insurance Research Database.

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            Aristolochic acids and their derivatives are widely implicated in liver cancers in Taiwan and throughout Asia

            Many traditional pharmacopeias include Aristolochia and related plants, which contain nephrotoxins and mutagens in the form of aristolochic acids and similar compounds (collectively, AA). AA is implicated in multiple cancer types, sometimes with very high mutational burdens, especially in upper tract urothelial cancers (UTUCs). AA-associated kidney failure and UTUCs are prevalent in Taiwan, but AA’s role in hepatocellular carcinomas (HCCs) there remains unexplored. Therefore, we sequenced the whole exomes of 98 HCCs from two hospitals in Taiwan and found that 78% showed the distinctive mutational signature of AA exposure, accounting for most of the nonsilent mutations in known cancer driver genes. We then searched for the AA signature in 1400 HCCs from diverse geographic regions. Consistent with exposure through known herbal medicines, 47% of Chinese HCCs showed the signature, albeit with lower mutation loads than in Taiwan. In addition, 29% of HCCs from Southeast Asia showed the signature. The AA signature was also detected in 13 and 2.7% of HCCs from Korea and Japan as well as in 4.8 and 1.7% of HCCs from North America and Europe, respectively, excluding one U.S. hospital where 22% of 87 "Asian" HCCs had the signature. Thus, AA exposure is geographically widespread. Asia, especially Taiwan, appears to be much more extensively affected, which is consistent with other evidence of patterns of AA exposure. We propose that additional measures aimed at primary prevention through avoidance of AA exposure and investigation of possible approaches to secondary prevention are warranted.
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              Bridging the efficacy-effectiveness gap: a regulator's perspective on addressing variability of drug response.

              Drug regulatory agencies should ensure that the benefits of drugs outweigh their risks, but licensed medicines sometimes do not perform as expected in everyday clinical practice. Failure may relate to lower than anticipated efficacy or a higher than anticipated incidence or severity of adverse effects. Here we show that the problem of benefit-risk is to a considerable degree a problem of variability in drug response. We describe biological and behavioural sources of variability and how these contribute to the long-known efficacy-effectiveness gap. In this context, efficacy describes how a drug performs under conditions of clinical trials, whereas effectiveness describes how it performs under conditions of everyday clinical practice. We argue that a broad range of pre- and post-licensing technologies will need to be harnessed to bridge the efficacy-effectiveness gap. Successful approaches will not be limited to the current notion of pharmacogenomics-based personalized medicines, but will also entail the wider use of electronic health-care tools to improve drug prescribing and patient adherence.
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                Author and article information

                Journal
                Epidemiol Health
                Epidemiol Health
                EPIH
                Epidemiology and Health
                Korean Society of Epidemiology
                2092-7193
                2018
                27 December 2018
                : 40
                : e2018062
                Affiliations
                [1 ]Department of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
                [2 ]Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University College of Public Health, Taipei, Taiwan
                [3 ]Department of Public Health, National Taiwan University College of Public Health, Taipei, Taiwan
                [4 ]Innovation and Policy Centre for Population Health and Sustainable Environment, National Taiwan University College of Public Health, Taipei, Taiwan
                [5 ]Department of Environmental and Occupational Medicine, National Taiwan University College of Medicine and Hospital, Taipei, Taiwan
                [6 ]Office of Occupational Safety and Health, National Taiwan University Hospital, Taipei, Taiwan
                Author notes
                Correspondence: Pau-Chung Chen  Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University College of Public Health, 17 Xu-Zhou Road, Taipei 10055, Taiwan  E-mail: pchen@ 123456ntu.edu.tw
                Author information
                http://orcid.org/0000-0003-4720-6738
                http://orcid.org/0000-0003-4524-3180
                http://orcid.org/0000-0002-9168-6022
                http://orcid.org/0000-0002-6242-5974
                Article
                epih-40-e2018062
                10.4178/epih.e2018062
                6367203
                30727703
                825c69ec-7117-4c52-8944-c013c572d391
                ©2018, Korean Society of Epidemiology

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 November 2018
                : 27 December 2018
                Categories
                Review Paper

                Public health
                database,electronic health records,information storage and retrieval,national health insurance research database,taiwan

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