Healthc Inform Res.  2019 Apr;25(2):61-72. 10.4258/hir.2019.25.2.61.

Analyzing and Visualizing Knowledge Structures of Health Informatics from 1974 to 2018: A Bibliometric and Social Network Analysis

Affiliations
  • 1Management Studies Center, Tarbiat Modares University, Tehran, Iran. t.saheb@modares.ac.ir
  • 2Caspian Higher Education Institute, Qazvin, Iran.

Abstract


OBJECTIVES
This paper aims to provide a theoretical clarification of the health informatics field by conducting a quantitative review analysis of the health informatics literature. And this paper aims to map scientific networks; to uncover the explicit and hidden patterns, knowledge structures, and sub-structures in scientific networks; to track the flow and burst of scientific topics; and to discover what effects they have on the scientific growth of health informatics.
METHODS
This study was a quantitative literature review of the health informatics field, employing text mining and bibliometric research methods. This paper reviews 30,115 articles with health informatics as their topic, which are indexed in the Web of Science Core Collection Database from 1974 to 2018. This study analyzed and mapped four networks: author co-citation network, co-occurring author keywords and keywords plus, co-occurring subject categories, and country co-citation network. We used CiteSpace 5.3 and VOSviewer to analyze data, and we used Gephi 0.9.2 and VOSviewer to visualize the networks.
RESULTS
This study found that the three major themes of the literature from 1974 to 2018 were the utilization of computer science in healthcare, the impact of health informatics on patient safety and the quality of healthcare, and decision support systems. The study found that, since 2016, health informatics has entered a new era to provide predictive, preventative, personalized, and participatory healthcare systems.
CONCLUSIONS
This study found that the future strands of research may be patient-generated health data, deep learning algorithms, quantified self and self-tracking tools, and Internet of Things based decision support systems.

Keyword

Medical Informatics; Data Mining; Algorithms; Machine Learning; Publications

MeSH Terms

Data Mining
Delivery of Health Care
Humans
Informatics*
Internet
Learning
Machine Learning
Medical Informatics
Patient Safety
Quality of Health Care

Figure

  • Figure 1 Map of co-occurring keywords visualized by the Gephi software (top 30% per 5-year slice).

  • Figure 2 Overlay visualization of keywords from 2010 to 2018.

  • Figure 3 Visualization of countries' citation numbers and citation links with the other countries (top 30% per 5-year slice).

  • Figure 4 Co-occurring subject categories (top 30% per 5-year slice).

  • Figure 5 Visualization of author co-citation analysis based on modularity score.


Cited by  1 articles

Keyword Trends for Mother–Child Oral Health in Korea Based on Social Media Big Data from Naver
Jung-Eun Park, Ja-Won Cho, Jong-Hwa Jang
Healthc Inform Res. 2020;26(3):212-219.    doi: 10.4258/hir.2020.26.3.212.


Reference

1. Carter CE, Veale BL. Digital radiography and PACS. St. Louis (MO): Mosby;2008.
2. Fitzgerald-Hayes M, Reichsman F. DNA and biotechnology. Boston (MA): Elsevier;2010.
3. Smallwood RF. Managing electronic records: Methods, best practices, and technologies. Hoboken (NJ): John Wiley & Sons;2013.
4. Ballweg R, Brown D, Vetrosky DT, Ritsema TS. Physician assistant: a guide to clinical practice. Philadelphia (PA): Elsevier;2017.
5. O'Carroll PW, Ripp LH, Yasnoff WA, Ward ME, Martin EL. Public health informatics and information systems. New York (NY): Springer;2003.
6. Masic I. The history and new trends of medical informatics. Donald School J Ultrasound Obstet Gynecol. 2013; 7(3):301–302.
Article
7. Bronzino JD. Medical devices and systems. Boca Raton (FL): CRC Press;2006.
8. Scaletti A. Evaluating investments in health care systems: health technology assessment. Heidelberg: Springer;2014.
9. Hayes BM, Aspray W. Health informatics: a patient-centered approach to diabetes. Cambridge (MA): MIT Press;2010.
10. Deng H, Wang J, Liu X, Liu B, Lei J. Evaluating the outcomes of medical informatics development as a discipline in China: a publication perspective. Comput Methods Programs Biomed. 2018; 164:75–85.
Article
11. Kruse CS, Stein A, Thomas H, Kaur H. The use of electronic health records to support population health: a systematic review of the literature. J Med Syst. 2018; 42(11):214.
Article
12. Ross T. A survival guide for health research methods. Maidenhead, UK: McGraw-Hill Education;2012.
13. Walker E, Hernandez AV, Kattan MW. Meta-analysis: its strengths and limitations. Cleve Clin J Med. 2008; 75(6):431–439.
Article
14. Stegenga J. Is meta-analysis the platinum standard of evidence? Stud Hist Philos Biol Biomed Sci. 2011; 42(4):497–507.
Article
15. Watanabe M. Going multidisciplinary. Nature. 2003; 425(6957):542–543.
Article
16. Chen C. Mapping scientific frontiers: the quest for knowledge visualization. London: Springer;2013.
17. Xu G, Zhang Y, Li L. Web mining and social networking: techniques and applications. New York (NY): Springer;2011.
18. Gonzalez GH, Tahsin T, Goodale BC, Greene AC, Greene CS. Recent advances and emerging applications in text and data mining for biomedical discovery. Brief Bioinform. 2016; 17(1):33–42.
Article
19. Aggarwal CC, Wang H. Text mining in social networks. In : Aggarwal CC, editor. Social network data analytics. Boston (MA): Springer;2011. p. 353–378.
20. Bornmann L, Haunschild R, Hug SE. Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis. Scientometrics. 2018; 114(2):427–437.
Article
21. Khokhar D. Gephi cookbook. Birmingham, UK: Packt Publishing Ltd.;2015.
22. Parente ST, McCullough JS. Health information technology and patient safety: evidence from panel data. Health Aff (Millwood). 2009; 28(2):357–360.
Article
23. Alotaibi YK, Federico F. The impact of health information technology on patient safety. Saudi Med J. 2017; 38(12):1173–1180.
Article
24. Kaelber DC, Bates DW. Health information exchange and patient safety. J Biomed Inform. 2007; 40:6 Suppl. S40–S45.
Article
25. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005; 330(7494):765.
Article
26. Sim I, Gorman P, Greenes RA, Haynes RB, Kaplan B, Lehmann H, et al. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc. 2001; 8(6):527–534.
Article
27. Bates DW, Cohen M, Leape LL, Overhage JM, Shabot MM, Sheridan T. Reducing the frequency of errors in medicine using information technology. J Am Med Inform Assoc. 2001; 8(4):299–308.
Article
28. Bauchner H, Simpson L, Chessare J. Changing physician behaviour. Arch Dis Child. 2001; 84(6):459–462.
Article
29. Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer-based guideline implementation systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc. 1999; 6(2):104–114.
Article
30. Purcell GP, Wilson P, Delamothe T. The quality of health information on the internet. BMJ. 2002; 324(7337):557–558.
Article
31. Gagliardi A, Jadad AR. Examination of instruments used to rate quality of health information on the internet: chronicle of a voyage with an unclear destination. BMJ. 2002; 324(7337):569–573.
Article
32. Skiba DJ. Informatics competencies for nurses revisited. Nurs Educ Perspect. 2016; 37(6):365–367.
Article
33. Graves JR, Corcoran S. The study of nursing informatics. Image J Nurs Sch. 1989; 21(4):227–231.
Article
34. Bickley L, Szilagyi PG. Bates' guide to physical examination and history-taking. Philadelphia (PA): Lippincott Williams & Wilkins;2012.
35. Hersh W. Medical informatics education: an alternative pathway for training informationists. J Med Libr Assoc. 2002; 90(1):76–79.
36. Norris AC. Current trends and challenges in health informatics. Health Informatics J. 2002; 8(4):205–213.
Article
37. Gagnon MP, Ngangue P, Payne-Gagnon J, Desmartis M. m-Health adoption by healthcare professionals: a systematic review. J Am Med Inform Assoc. 2016; 23(1):212–220.
Article
38. Wilkowska W, Ziefle M. Privacy and data security in ehealth: requirements from the user's perspective. Health Informatics J. 2012; 18(3):191–201.
Article
39. Pilemalm S, Timpka T. Third generation participatory design in health informatics: making user participation applicable to large-scale information system projects. J Biomed Inform. 2008; 41(2):327–339.
Article
40. Kvedar J, Coye MJ, Everett W. Connected health: a review of technologies and strategies to improve patient care with telemedicine and telehealth. Health Aff (Millwood). 2014; 33(2):194–199.
Article
41. Swan M. Health 2050: the realization of personalized medicine through crowdsourcing, the quantified self, and the participatory biocitizen. J Pers Med. 2012; 2(3):93–118.
Article
Full Text Links
  • HIR
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr