ORIGINAL RESEARCH article
Front. Digit. Health
Sec. Health Informatics
Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1595310
This article is part of the Research TopicDigital Health Past, Present, and FutureView all 34 articles
From the past into the future: Trends and developments in health systems modeling using bibliometric analysis
Provisionally accepted
- 1Mangosuthu University of Technology, Umlazi, South Africa
- 2University of Johannesburg, Johannesburg, Gauteng, South Africa
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This study used bibliometric analysis to outline trends and developments in health systems modeling, using data from the Web of Science (WoS) database covering 1992 to 2023. The study underscores the dynamic nature of health systems modeling, emphasizing its pivotal role in tackling complex health challenges and informing policy and decision-making in healthcare. The study aimed to describe the current and future trends in health systems modeling, identify leading publications, authors, institutions, and countries involved, and develop a thematic map to depict the latest research in the field. The analysis was conducted on March 10, 2023, using data from the WoS database and scientometric tools, specifically Biblioshiny and VOSviewer. The search string used was "health system*" AND "modelling" OR "modeling." In this study, 2,023 records were extracted, and the annual growth rate of publications is 7.53%, with an average of 9.35 co-authors per article and 37.67% international co-authorship. The bibliometric analysis identified significant trends and developments in health systems modeling, highlighting contributions from top journals like The Lancet and PLOS One, leading authors such as Blakely T. and Hay S.I., major institutions like the Tehran University of Medical Sciences and the University of Washington, and leading countries like the United States and the United Kingdom. Emerging themes include "health systems", "modelling", "predictive modeling", and "systems dynamics", suggesting promising directions for future research. The study recommends focusing on epidemiology and predictive modeling to advance the field. Nevertheless, it acknowledges the constraints of using a singular database (WoS) and proposes broader integration for future research. The study can be used to identify potential collaboration opportunities, publication venues, and research gaps in health systems modeling.
Keywords: health systems modeling1, bibliometric analysis 2, science mapping3, bibliometric performance analysis4, keyword5
Received: 17 Mar 2025; Accepted: 18 Sep 2025.
Copyright: © 2025 Maguraushe, Ndayizigamiye and Bokaba. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Kudakwashe Maguraushe, kmaguraushe@gmail.com
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