Research Subjects and Research Trends in Medical Informatics

Abstract

Objectives To identify major research subjects and trends in medical informatics research based on the current set of core medical informatics journals.

Methods Analyzing journals in the Web of Science (WoS) medical informatics category together with related categories from the years 2013 to 2017 by using a smart local moving algorithm as a clustering method for identifying the core set of journals. Text mining analysis with binary counting of abstracts from these journals published in the years 2006 to 2017 for identifying major research subjects. Building clusters based on these terms for the complete time period as well as for the periods 2006–2008, 2009–2011, 2012–2014, and 2015–2017 for identifying trends.

Results The identified cluster includes 17 core medical informatics journals. By text mining of these journals, 224,992 different terms in 14,414 articles were identified covering 550 specific key terms. Based on these key terms five clusters were identified: “Biomedical Data Analysis,” “Clinical Informatics,” “EHR and Knowledge Representation,” “Mobile Health,” and “Organizational Aspects of Health Information Systems.” No shifts in the clusters were observed between the first two 3-year periods. In the third period, some terms like “mobile phone,” “mobile apps,” and “message” appear. Also, in the third period, a “Clinical Informatics” cluster appears and persists in the fourth period. In the fourth period, a rearrangement of clusters was observed.

Conclusions Beside classical subjects of medical informatics on organizing, representing, and analyzing data, we observed new developments in the context of mobile health and clinical informatics. These subjects tended to grow over the past years, and we can expect this trend to continue.

Keywords

medical informatics - biomedical and health informatics - research

• References

• 1 Musen MA, van Bemmel JH. Challenges for medical informatics as an academic discipline: workshop report. Yearb Med Inform 2002; [phone]
• 2 Hersh W. A stimulus to define informatics and health information technology. BMC Med Inform Decis Mak 2009; 9: 24
• 3 Haux R. On determining factors for good research in biomedical and health informatics. Some lessons learned. Yearb Med Inform 2014; 9: 255-264
• 4 Mantas J, Ammenwerth E, Demiris G. , et al; IMIA Recommendations on Education Task Force. Recommendations of the International Medical Informatics Association (IMIA) on education in biomedical and health informatics. First revision. Methods Inf Med 2010; 49 (02) 105-120
• 5 Chen ES, Sarkar IN. *informatics: identifying and tracking informatics sub-discipline terms in the literature. Methods Inf Med 2015; 54 (06) 530-539
• 6 Bernstam EV, Smith JW, Johnson TR. What is biomedical informatics?. J Biomed Inform 2010; 43 (01) 104-110
• 7 Sittig DF. Identifying a core set of medical informatics serials: an analysis using the MEDLINE database. Bull Med Libr Assoc 1996; 84 (02) 200-204
• 8 Lavallie DL, Wolf FM. Publication trends and impact factors in the medical informatics literature. AMIA Annu Symp Proc 2005; 1018
• 9 Deshazo JP, Lavallie DL, Wolf FM. Publication trends in the medical informatics literature: 20 years of “Medical Informatics” in MeSH. BMC Med Inform Decis Mak 2009; 9: 7
• 10 Elkin PL, Brown SH, Wright G. Biomedical informatics: we are what we publish. Methods Inf Med 2013; 52 (06) 538-546
• 11 Lyu PH, Yao Q, Mao J, Zhang SJ. Emerging medical informatics research trends detection based on MeSH terms. Inform Health Soc Care 2015; 40 (03) 210-228
• 12 Wang L, Topaz M, Plasek JM, Zhou L. Content and trends in medical informatics publications over the past two decades. Stud Health Technol Inform 2017; 245: 968-972
• 13 Morris TA, McCain KW. The structure of medical informatics journal literature. J Am Med Inform Assoc 1998; 5 (05) 448-466
• 14 Schuemie MJ, Talmon JL, Moorman PW, Kors JA. Mapping the domain of medical informatics. Methods Inf Med 2009; 48 (01) 76-83
• 15 Morris SA, Van der Veer Martens B. Mapping research specialties. Annu Rev Inform Sci Tech 2008; 42 (01) 213-295
• 16 Kessler MM. Bibliographic coupling between scientific papers. Am Doc 1963; 14 (01) 10-25
• 17 Marshakova-Shaikevich I. System of document connections based on references. Nauchno Tekhnicheskaya Informatsiya Seriya 2–Informatsionnye Protsessy i Sistemy 1973;6:3–8
• 18 Small H. Co-citation in the scientific literature: a new measure of the relationship between two documents. J Am Soc Inf Sci 1973; 24 (04) 265-269
• 19 Boyack KW, Klavans R. Co-citation analysis, bibliographic coupling, and direct citation: which citation approach represents the research front most accurately?. J Am Soc Inform Sci Tech Arch 2010; 61 (12) 2389-2404
• 20 Klavans R, Boyack KW. Which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge?. J Assoc Inf Sci Technol 2017; 68 (04) 984-998
• 21 Morris TA. Structural relationships within medical informatics. Proc AMIA Symp 2000; 590-594
• 22 González LM, García-Massó X, Pardo-Ibañez A, Peset F, Devís-Devís J. An author keyword analysis for mapping sport sciences. PLoS One 2018; 13 (08) e0201435
• 23 VOSviewer version 1.6.8. Available at: http://www.vosviewer.com . Accessed August 20, 2018
• 24 Waltman L, van Eck NJ. A smart local moving algorithm for large-scale modularity-based community detection. Eur Phys J B 2013; 86 (11) 471
• 25 Perianes-Rodriguez A, Waltman L, Van Eck NJ. Constructing bibliometric networks: A comparison between full and fractional counting. J Informetrics 2016; 10 (04) 1178-1195
• 26 Van Eck NJ, Waltman L. How to normalize co-occurrence data? An analysis of some well-known similarity measures. J Am Soc Inf Sci Technol 2009; 60 (08) 1635-1651
• 27 Van Eck NJ, Waltman L. Visualizing bibliometric networks. In: Ding Y, Rousseau R, Wolfram D. , eds. Measuring Scholarly Impact: Methods and Practice. Berlin: Springer; 2014: 285-320
• 28 Van Eck NJ, Waltman L. VOSviewer Manual. Available at: http://www.vosviewer.com/download/f-z2X2.pdf . Accessed August 20, 2018
• 29 Apache OpenNLP library. Available at: http://opennlp.apache.org . Accessed August 20, 2018
• 30 Van Eck NJ, Waltman L. Text mining and visualization using VOSviewer. ISSI Newsletter 2011; 7 (03) 50-54
• 31 Archambault É, Beauchesne OH, Caruso J. Towards a multilingual, comprehensive and open scientific journal ontology. In: Noyons B, Ngulube P, Leta J, eds. Proceedings of the 13th International Conference of the International Society for Scientometrics and Informetrics (ISSI), Durban, South Africa; 2011:66–77
• 32 Science-Metrix Classification of Scientific Journals. Sixth public release: 2006–03–31 (v1.06). Available at: http://science-metrix.com/sites/default/files/science-metrix/sm_journal_classification_106_1.xls . Accessed October 19, 2018
• 33 Maojo V, García-Remesal M, Bielza C, Crespo J, Perez-Rey D, Kulikowski C. Biomedical informatics publications: a global perspective: part I: conferences. Methods Inf Med 2012; 51 (01) 82-90
• 34 Maojo V, Garcia-Remesal M, Bielza C, Crespo J, Perez-Rey D, Kulikowski C. Biomedical informatics publications: a global perspective. Part II: journals. Methods Inf Med 2012; 51 (02) 131-137
• 35 Geissbuhler A, Hammond WE, Hasman A. , et al. Discussion of “Biomedical informatics: we are what we publish”. Methods Inf Med 2013; 52 (06) 547-562
• 36 Saka O, Gülkesen KH, Gülden B, Koçgil OD. Evaluation of two search methods in PubMed; the regular search and search by MeSH terms. Acta Inform Med 2005; 13 (04) 180-183
• 37 van Bemmel JH. Medical informatics, art or science?. Methods Inf Med 1996; 35 (03) 157-172 , discussion 173–201
• 38 Martin-Sanchez FJ, Lopez-Campos GH. The new role of biomedical informatics in the age of digital medicine. Methods Inf Med 2016; 55 (05) 392-402
• 39 Al-Shorbaji N, Bellazzi R, Gonzalez Bernaldo de Quiros F. , et al. Discussion of “The New Role of Biomedical Informatics in the Age of Digital Medicine”. Methods Inf Med 2016; 55 (05) 403-421
• 40 Haux R, Kulikowski CA, Bakken S. , et al. Research strategies for biomedical and health informatics. Some thought-provoking and critical proposals to encourage scientific debate on the nature of good research in medical informatics. Methods Inf Med 2017; 56 (Open): e1-e10
• 41 Watanabe S. Knowing and Guessing: a Quantitative Study of Inference and Information. New York, NY: John Wiley & Sons Inc; 1969