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Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study

There has been a surge in the academic publication output based on secondary analyses of the data from the Taiwan's National Health Insurance claim records. It has become a challenge to comprehend such a rapid expansion of the literature. Therefore, this study aimed to explore the conceptual co...

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Autores principales: Chiang, Jui-Kun, Lin, Chih-Wen, Wang, Chun-Lung, Koo, Malcolm, Kao, Yee-Hsin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5413242/
https://www.ncbi.nlm.nih.gov/pubmed/28445277
http://dx.doi.org/10.1097/MD.0000000000006704
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author Chiang, Jui-Kun
Lin, Chih-Wen
Wang, Chun-Lung
Koo, Malcolm
Kao, Yee-Hsin
author_facet Chiang, Jui-Kun
Lin, Chih-Wen
Wang, Chun-Lung
Koo, Malcolm
Kao, Yee-Hsin
author_sort Chiang, Jui-Kun
collection PubMed
description There has been a surge in the academic publication output based on secondary analyses of the data from the Taiwan's National Health Insurance claim records. It has become a challenge to comprehend such a rapid expansion of the literature. Therefore, this study aimed to explore the conceptual content of National Health Insurance Research Database-based cancer research, using the abstract of articles extracted from PubMed between 2002 and 2015. Search terms including “National Health Insurance Research Database (NHIRD) AND Taiwan,” “Taiwan AND population-based,” and “Taiwan AND nationwide” were used to search in PubMed with the publication date limited to between 1997 and 2015. The retrieved articles were manually screened to retain only those that were cancer-related and were based on secondary data analysis of the NHIRD. A total 589 articles were selected for subsequent text mining using the R software. Among the 589 articles, the top 5 most studied cancer types were breast (16.3%), lung (11.4%), colorectal (10.4%), liver (8.3%), and prostate (7.5%). The articles that received the highest number of citations by PubMed Central articles were cited 92 times. The top 3 most frequently occurred keywords in the abstracts of the 589 articles were cancer, patient, and risk, with 3670, 2535, and 1652 times, respectively. Analysis of key conception indicated that the most common conceptions were diabetes, survival, breast cancer, lung cancer, and colorectal cancer. In conclusion, in this study of 589 published articles on secondary data analysis of the NHIRD, indexed by PubMed between 2002 and 2015, we found that while the risk factors of cancer, treatment of cancer, and survival of cancer patients were popular research topics, end-of-life cancer care issues were less studied. Further studies should explore these areas since they are as important as treatment of the disease itself for many patients.
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spelling pubmed-54132422017-05-05 Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study Chiang, Jui-Kun Lin, Chih-Wen Wang, Chun-Lung Koo, Malcolm Kao, Yee-Hsin Medicine (Baltimore) 5700 There has been a surge in the academic publication output based on secondary analyses of the data from the Taiwan's National Health Insurance claim records. It has become a challenge to comprehend such a rapid expansion of the literature. Therefore, this study aimed to explore the conceptual content of National Health Insurance Research Database-based cancer research, using the abstract of articles extracted from PubMed between 2002 and 2015. Search terms including “National Health Insurance Research Database (NHIRD) AND Taiwan,” “Taiwan AND population-based,” and “Taiwan AND nationwide” were used to search in PubMed with the publication date limited to between 1997 and 2015. The retrieved articles were manually screened to retain only those that were cancer-related and were based on secondary data analysis of the NHIRD. A total 589 articles were selected for subsequent text mining using the R software. Among the 589 articles, the top 5 most studied cancer types were breast (16.3%), lung (11.4%), colorectal (10.4%), liver (8.3%), and prostate (7.5%). The articles that received the highest number of citations by PubMed Central articles were cited 92 times. The top 3 most frequently occurred keywords in the abstracts of the 589 articles were cancer, patient, and risk, with 3670, 2535, and 1652 times, respectively. Analysis of key conception indicated that the most common conceptions were diabetes, survival, breast cancer, lung cancer, and colorectal cancer. In conclusion, in this study of 589 published articles on secondary data analysis of the NHIRD, indexed by PubMed between 2002 and 2015, we found that while the risk factors of cancer, treatment of cancer, and survival of cancer patients were popular research topics, end-of-life cancer care issues were less studied. Further studies should explore these areas since they are as important as treatment of the disease itself for many patients. Wolters Kluwer Health 2017-04-28 /pmc/articles/PMC5413242/ /pubmed/28445277 http://dx.doi.org/10.1097/MD.0000000000006704 Text en Copyright © 2017 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle 5700
Chiang, Jui-Kun
Lin, Chih-Wen
Wang, Chun-Lung
Koo, Malcolm
Kao, Yee-Hsin
Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study
title Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study
title_full Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study
title_fullStr Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study
title_full_unstemmed Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study
title_short Cancer studies based on secondary data analysis of the Taiwan's National Health Insurance Research Database: A computational text analysis and visualization study
title_sort cancer studies based on secondary data analysis of the taiwan's national health insurance research database: a computational text analysis and visualization study
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5413242/
https://www.ncbi.nlm.nih.gov/pubmed/28445277
http://dx.doi.org/10.1097/MD.0000000000006704
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