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Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease
OBJECTIVE: Since most biomedical research focuses on a specific disease, evaluation of research output requires disease-specific bibliometric indicators. Currently used methods are insufficient. The aim of this study is to develop a method that enables detailed analysis of worldwide biomedical resea...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988175/ https://www.ncbi.nlm.nih.gov/pubmed/29866730 http://dx.doi.org/10.1136/bmjopen-2017-020818 |
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author | van de Laar, Lissy de Kruif, Thijs Waltman, Ludo Meijer, Ingeborg Gupta, Anshu Hagenaars, Niels |
author_facet | van de Laar, Lissy de Kruif, Thijs Waltman, Ludo Meijer, Ingeborg Gupta, Anshu Hagenaars, Niels |
author_sort | van de Laar, Lissy |
collection | PubMed |
description | OBJECTIVE: Since most biomedical research focuses on a specific disease, evaluation of research output requires disease-specific bibliometric indicators. Currently used methods are insufficient. The aim of this study is to develop a method that enables detailed analysis of worldwide biomedical research output by disease. DESIGN: We applied text mining techniques and analysis of author keywords to link publications to disease groups. Fractional counting was used to quantify disease-specific biomedical research output of an institution or country. We calculated global market shares of research output as a relative measure of publication volume. We defined ‘top publications’ as the top 10% most cited publications per disease group worldwide. We used the percentage of publications from an institution or country that were top publications as an indicator of research quality. RESULTS: We were able to classify 54% of all 6.5 million biomedical publications in our database (based on Web of Science) to a disease group. We could classify 78% of these publications to a specific institution. We show that between 2000 and 2012,‘other infectious diseases’ were the largest disease group with 337 485 publications. Lifestyle diseases, cancers and mental disorders have grown most in research output. The USA was responsible for the largest number of top 10% most cited publications per disease group, with a global share of 45%. Iran (+3500%) and China (+700%) have grown most in research volume. CONCLUSIONS: The proposed method provides a tool to assess biomedical research output in new ways. It can be used for evaluation of historical research performance, to support decision-making in management of research portfolios, and to allocate research funding. Furthermore, using this method to link disease-specific research output to burden of disease can contribute to a better understanding of the societal impact of biomedical research. |
format | Online Article Text |
id | pubmed-5988175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-59881752018-06-07 Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease van de Laar, Lissy de Kruif, Thijs Waltman, Ludo Meijer, Ingeborg Gupta, Anshu Hagenaars, Niels BMJ Open Medical Publishing and Peer Review OBJECTIVE: Since most biomedical research focuses on a specific disease, evaluation of research output requires disease-specific bibliometric indicators. Currently used methods are insufficient. The aim of this study is to develop a method that enables detailed analysis of worldwide biomedical research output by disease. DESIGN: We applied text mining techniques and analysis of author keywords to link publications to disease groups. Fractional counting was used to quantify disease-specific biomedical research output of an institution or country. We calculated global market shares of research output as a relative measure of publication volume. We defined ‘top publications’ as the top 10% most cited publications per disease group worldwide. We used the percentage of publications from an institution or country that were top publications as an indicator of research quality. RESULTS: We were able to classify 54% of all 6.5 million biomedical publications in our database (based on Web of Science) to a disease group. We could classify 78% of these publications to a specific institution. We show that between 2000 and 2012,‘other infectious diseases’ were the largest disease group with 337 485 publications. Lifestyle diseases, cancers and mental disorders have grown most in research output. The USA was responsible for the largest number of top 10% most cited publications per disease group, with a global share of 45%. Iran (+3500%) and China (+700%) have grown most in research volume. CONCLUSIONS: The proposed method provides a tool to assess biomedical research output in new ways. It can be used for evaluation of historical research performance, to support decision-making in management of research portfolios, and to allocate research funding. Furthermore, using this method to link disease-specific research output to burden of disease can contribute to a better understanding of the societal impact of biomedical research. BMJ Publishing Group 2018-06-04 /pmc/articles/PMC5988175/ /pubmed/29866730 http://dx.doi.org/10.1136/bmjopen-2017-020818 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Medical Publishing and Peer Review van de Laar, Lissy de Kruif, Thijs Waltman, Ludo Meijer, Ingeborg Gupta, Anshu Hagenaars, Niels Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
title | Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
title_full | Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
title_fullStr | Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
title_full_unstemmed | Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
title_short | Improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
title_sort | improving the evaluation of worldwide biomedical research output: classification method and standardised bibliometric indicators by disease |
topic | Medical Publishing and Peer Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988175/ https://www.ncbi.nlm.nih.gov/pubmed/29866730 http://dx.doi.org/10.1136/bmjopen-2017-020818 |
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