Journals / Journal of International Health Sciences and Management / 2026 / Volume: 12

Bibliometric Profile of Research on Digital Health Systems in Healthcare Delivery: A Bibliometric Analysis (2015–2025)

Hakan Işık(GİRESUN ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ)0000-0002-9907-9315
Elgiz Askeroğlu(GIRESUN UNIVERSITY, INSTITUTE OF SCIENCE, STATISTICS (DR))0000-0001-5883-5527
Selçuk Takır(GIRESUN UNIVERSITY, SCHOOL OF MEDICINE, DEPARTMENT OF INTERNAL MEDICINE, DEPARTMENT OF PHARMACOLOGY)0000-0002-9130-9518
Pages
—
Publication Date
2026-10-05
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Rather than representing a single homogeneous domain, these themes collectively form a multidimensional research landscape that connects healthcare delivery and technological innovation with service organization and digital transformation.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Digital health systems are playing an increasingly key role in the transformation of how healthcare is delivered today.
📊
Key Findings & Data:The international co-authorship rate of 17.53% indicates that collaboration was predominantly domestic, with a comparatively limited level of cross-country collaboration.
💡
Conclusion & Impact:Rather than representing a single homogeneous domain, these themes collectively form a multidimensional research landscape that connects healthcare delivery and technological innovation with service organization and digital transformation.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Digital Health Systems · Healthcare Delivery · Bibliometric Analysis

Abstract

Digital health systems are playing an increasingly key role in the transformation of how healthcare is delivered today. However, digital health literature remains highly fragmented and widely dispersed among disciplines, publications, and research themes, which limits the ability to have a clear understanding of the total current knowledge base. The purpose of this study is to develop an understanding of the total body of academic research associated with digital health systems within the healthcare delivery environment. Specifically, this study will identify the general layout of the digital health systems research field, research trends, primary source of outlets for publication, leading authors and their contribution to the field of digital health systems research, conceptual areas of research, and collaborative patterns of research using a bibliometric technique. The publications collected from both Scopus and the Web of Science Core Collection are subjected to pre-defined inclusion criteria, combined to form a unified data set, and cleaned to remove duplicate or incomplete records. The processing, integration and visualization of the data are performed using bibliometrix and Biblioshiny in the RStudio Environment. The international co-authorship rate of 17.53% indicates that collaboration was predominantly domestic, with a comparatively limited level of cross-country collaboration. Most of the research in the field of digital health systems can be found in just a few key journals/directories. The literature is organized around several recurring themes, including digital health, telemedicine, telehealth, mHealth, and related areas. Rather than representing a single homogeneous domain, these themes collectively form a multidimensional research landscape that connects healthcare delivery and technological innovation with service organization and digital transformation.

🔖

Cite This Article

Işık, H., Askeroğlu, E., Takır, S. (2026). Bibliometric Profile of Research on Digital Health Systems in Healthcare Delivery: A Bibliometric Analysis (2015–2025). Journal of International Health Sciences and Management, Volume: 12. https://doi.org/10.48121/jihsam.1956539

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (63)

  1. Adegoke, K., Adegoke, A., Dawodu, D., Adekoya, A., Bayowa, A., Kayode, T., & Singh, M. (2025). Interoperability as a Catalyst for Digital Health and Therapeutics: A Scoping Review of Emerging Technologies and Standards (2015–2025). International Journal of Environmental Research and Public Health, 22(10), 1535. https://doi.org/10.3390/ijerph22101535
  2. Aizaz, M., Khan, F., Ali, B., Ahmad, S., Naseem, K., Mishra, S., & others. (2023). Significance of Digital Health Technologies (DHTs) to manage communicable and non-communicable diseases in Low and Middle-Income Countries (LMICs). Health and Technology, 13(6), 883–892. https://doi.org/10.1007/s12553-023-00792-w
  3. Akhtar, M. N., Haleem, A., & Javaid, M. (2024). Exploring the advent of Medical 4.0: A bibliometric analysis systematic review and technology adoption insights. Informatics and Health, 1(1), 16–28. https://doi.org/10.1016/j.infoh.2023.10.001
  4. Aldousari, E., & Kithinji, D. (2024). Artificial intelligence and health information: A bibliometric analysis. Health Informatics Journal. https://doi.org/10.1177/14604582241283969
  5. Alipanah, N., Jarlsberg, L., Miller, C., Linh, N. N., Falzon, D., Jaramillo, E., & Nahid, P. (2018). Adherence interventions and outcomes of tuberculosis treatment: A systematic review and meta-analysis of trials and observational studies. https://doi.org/10.1371/journal.pmed.1002595
  6. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
  7. Banos, O., Villalonga, C., Garcia, R., Saez, A., Damas, M., Holgado-Terriza, J. A., Lee, S., Pomares, H., & Rojas, I. (2015). Design, implementation and validation of a novel open framework for agile development of mobile health applications. BioMedical Engineering OnLine, 14(2), S6. https://doi.org/10.1186/1475-925X-14-S2-S6
  8. Bernuzzi, C., Piccardo, M. A., & Guglielmetti, C. (2025). Mapping Research Trends on the Implications of Telemedicine for Healthcare Professionals: A Comprehensive Bibliometric Analysis. Healthcare, 13(10), 1149. https://doi.org/10.3390/healthcare13101149
  9. Bertolazzi, A., Quaglia, V., & Bongelli, R. (2024). Barriers and facilitators to health technology adoption by older adults with chronic diseases: An integrative systematic review. BMC Public Health, 24(1), 506. https://doi.org/10.1186/s12889-024-18036-5
  10. Bhattacharya, S., Singh, A., & Kashyap, A. (2025). Digital horizons in non-communicable disease care: A bibliometric exploration of intervention impact and innovation. Frontiers in Digital Health, 7. https://doi.org/10.3389/fdgth.2025.1528711
  11. Birkle, C., Pendlebury, D. A., Schnell, J., & Adams, J. (2020). Web of Science as a data source for research on scientific and scholarly activity. Quantitative Science Studies, 1(1), 363–376. https://doi.org/10.1162/qss_a_00018
  12. Bokolo, A. J. (2020). Use of Telemedicine and Virtual Care for Remote Treatment in Response to COVID-19 Pandemic | Journal of Medical Systems | Springer Nature Link. 44(7), 132. https://doi.org/10.1007/s10916-020-01596-5
  13. Chang, J. E., Lai, A. Y., Gupta, A., Nguyen, A. M., Berry, C. A., & Shelley, D. R. (2021). Rapid Transition to Telehealth and the Digital Divide: Implications for Primary Care Access and Equity in a Post-COVID Era. The Milbank Quarterly, 99(2), 340–368. https://doi.org/10.1111/1468-0009.12509
  14. Cheng, W., Hu, Z., & Yu, H. (2025). A bibliometric analysis of artificial intelligence in medical education (2015–2025). Medicine, 104(46), e45684. https://doi.org/10.1097/MD.0000000000045684
  15. Chowhan, S. S., Mohan, N., Nayak, N. S., & Pal Yadav, C. (2025). Digital Health for All: Building a Patient-Centered Public Health Framework through Telemedicine. Advances in Consumer Research, 2(4).
  16. Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. https://doi.org/10.1002/asi.21525
  17. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
  18. Eberly, L. A., Kallan, M. J., Julien, H. M., Haynes, N., Khatana, S. A. M., Nathan, A. S., Snider, C., Chokshi, N. P., Eneanya, N. D., Takvorian, S. U., Anastos-Wallen, R., Chaiyachati, K., Ambrose, M., O’Quinn, R., Seigerman, M., Goldberg, L. R., Leri, D., Choi, K., Gitelman, Y., … Adusumalli, S. (2020). Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic. JAMA Network Open, 3(12), e2031640. https://doi.org/10.1001/jamanetworkopen.2020.31640
  19. Endalamaw, A., Zewdie, A., Wolka, E., & others. (2025). A scoping review of digital health technologies in multimorbidity management: Mechanisms, outcomes, challenges, and strategies. BMC Health Services Research, 25, 382. https://doi.org/10.1186/s12913-025-12548-5
  20. Fatehi, F., & Wootton, R. (2012). Telemedicine, telehealth or e-health? A bibliometric analysis. Journal of Telemedicine and Telecare, 18(8), 460–464. https://doi.org/10.1258/jtt.2012.120591
  21. Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., & others. (2013). The effectiveness of mobile-health technologies to improve health care service delivery processes: A systematic review and meta-analysis. PLoS Medicine, 10(1), e1001363. https://doi.org/10.1371/journal.pmed.1001363
  22. Garçon, Q., Cabanes, B., & Denis-Rémis, C. (2025). Managerial Challenges in Digital Health: Bibliometric and Network Analysis. Journal of Medical Internet Research, 27, e57980. https://doi.org/10.2196/57980
  23. Guo, Y., Hao, Z., Zhao, S., Gong, J., & Yang, F. (2020). Artificial intelligence in health care: Bibliometric analysis. Journal of Medical Internet Research, 22(7), e18228. https://doi.org/10.2196/18228
  24. He, H., Abdul-Rashid, S. H., & Ghazilla, R. A. R. (2024). Research trends and hot spots in telemedicine for the elderly: A scientometric analysis. Healthcare, 12(18), 1853. https://doi.org/10.3390/healthcare12181853
  25. Hong, Z., Li, N., Li, D., Li, J., Li, B., Xiong, W., Lu, L., Li, W., & Zhou, D. (2020). Telemedicine During the COVID-19 Pandemic: Experiences From Western China. Journal of Medical Internet Research, 22(5), e19577. https://doi.org/10.2196/19577
  26. Hu, J., Li, C., Ge, Y., Yang, J., Zhu, S., & He, C. (2024). Mapping the Evolution of Digital Health Research: Bibliometric Overview of Research Hotspots, Trends, and Collaboration of Publications in JMIR (1999-2024). Journal of Medical Internet Research, 26(1), e58987. https://doi.org/10.2196/58987
  27. Huang, J., Liu, Y., Huang, S., Ke, G., Chen, X., Gong, B., & others. (2022). Research output of artificial intelligence in arrhythmia from 2004 to 2021: A bibliometric analysis. Journal of Thoracic Disease, 14(5), 1411. https://doi.org/10.21037/jtd-21-1767
  28. Işık, H. (2025). Global Trends in Condition Factor and Length–Weight Relationships in Fisheries Science (2000–2025): A Bibliometric Analysis. Journal of Anatolian Environmental and Animal Sciences, 10(6), 889–901. https://doi.org/10.35229/jaes.1766015
  29. Işık, H., & Palabıyık, S. (2025). Evde Bakım Hizmetlerinde Yapay Zekanın Rolü: Bibliyometrik Bir Analiz. Doğu Karadeniz Sağlık Bilimleri Dergisi, 4(2), 123–138. https://doi.org/10.59312/ebshealth.1674263
  30. Ivanitskaya, L. V., Zikos, D., & Erzikova, E. (2025). Multidisciplinary Contributions and Research Trends in eHealth Scholarship (2000–2024): Bibliometric Analysis. Journal of Medical Internet Research, 27, e60071. https://doi.org/10.2196/60071
  31. Judijanto, L. (2024). Bibliometric Insights into the Evolution of Health Information Systems and Telemedicine Research. The Eastasouth Journal of Information System and Computer Science, 1(03), 167–175. https://doi.org/10.58812/esiscs.v1i03.241
  32. Khatun, F., Heywood, A. E., Ray, P. K., Hanifi, S., Bhuiya, A., & Liaw, S.-T. (2015). Determinants of readiness to adopt mHealth in a rural community of Bangladesh. International Journal of Medical Informatics, 84(10), 847–856. https://doi.org/10.1016/j.ijmedinf.2015.06.008
  33. Kissi, J., Dai, B., Dogbe, C. S., Banahene, J., & Ernest, O. (2020). Predictive factors of physicians’ satisfaction with telemedicine services acceptance. Health Informatics Journal, 26(3), 1866–1880. https://doi.org/10.1177/1460458219892162
  34. Kong, S., Lin, C., Shen, Y., & Chen, J. (2026). Global trends of peripheral immune tolerance research: A bibliometric and visualization analysis. Frontiers in Immunology, 17, 1730575. https://doi.org/10.3389/fimmu.2026.1730575
  35. Liu, S., Ma, J., Sun, M., Zhang, C., Gao, Y., & Xu, J. (2025). Mapping the landscape of digital health intervention strategies: 25-year synthesis. Journal of Medical Internet Research, 27, e59027. https://doi.org/10.2196/59027
  36. Maguraushe, K., Ndayizigamiye, P., & Bokaba, T. (2025). Frontiers | Trends and developments in health systems modeling: A bibliometric analysis. https://doi.org/10.3389/fdgth.2025.1595310
  37. Mangion, A., & Piller, N. (2025). What is digital health, eHealth, uHealth and Healthcare 4.0? Informatics and Health, 2(2), 137–142. https://doi.org/10.1016/j.infoh.2025.06.002
  38. Marcolino, M. S., Oliveira, J. A. Q., D’Agostino, M., Ribeiro, A. L., Alkmim, M. B., & Novillo-Ortiz, D. (2018). The impact of mHealth interventions: Systematic review of systematic reviews. JMIR mHealth and uHealth, 6(1), e23. https://doi.org/10.2196/mhealth.8873
  39. Mbewe, A., Sarkwah, H. N., Ijaodola, O., Ratevosian, J., Simba, S., Smith, T. R., Holmes, C. B., & others. (2026). The role of digital health and artificial intelligence in improving the reach and effectiveness of HIV prevention in Africa. The Lancet Global Health, 14(1), e131–e142. https://doi.org/10.1016/S2214-109X(25)00447-4
  40. Mukherjee, D., Lim, W. M., Kumar, S., & Donthu, N. (2022). Guidelines for advancing theory and practice through bibliometric research. Journal of Business Research, 148, 101–115. https://doi.org/10.1016/j.jbusres.2022.04.042
  41. Odabaş Alver, D. (2025). Global and Turkish Research Trends in PM₁₀ Prediction Using Machine Learning: A Bibliometric Perspective. Journal of Anatolian Environmental and Animal Sciences, 10(6), 954–971. https://doi.org/10.35229/jaes.1766267
  42. Olayiwola, Q. B., Sanusi, O. M., Amoo, G. S., & others. (2026). Barriers to digital health implementation in low- and middle-income countries: A narrative review. Discover Public Health, 23, 499. https://doi.org/10.1186/s12982-026-01875-5
  43. Ologun, A. G., Olajide, O., Olajojo, R. A. O., Mordi, I. C., Umoru, N. B., Palmer, S. A., & Blessing, R. B. M. O. B. (2025). Evaluating digital health tools in chronic disease management effectiveness. Zenodo. https://doi.org/10.5281/zenodo.17999815
  44. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., & others. (2021). Updating guidance for reporting systematic reviews: Development of the PRISMA 2020 statement. Journal of Clinical Epidemiology, 134, 103–112. https://doi.org/10.1016/j.jclinepi.2021.02.003
  45. Pradana, M., Elisa, H. P., & Syarifuddin, S. (2023). Discussing ChatGPT in education: A literature review and bibliometric analysis. Cogent Education, 10(2), 2243134. https://doi.org/10.1080/2331186X.2023.2243134
  46. Prakash, A., Tummers, M., Segur-Ferrer, J., Vivano Hidalgo, R. M., Di Bidino, R., Tsiasiotis, E., Sacchini, D., Cicchetti, A., & Oortwijn, W. J. (2026). Toward a Harmonized Definition of Digital Health Technologies for Use in Health Technology Assessment: A Scoping Review and Modified Delphi Consensus Study. Value in Health, 29(8), 1515–1528. https://doi.org/10.1016/j.jval.2026.03.009
  47. Pussegoda, K., Turner, L., Garritty, C., Mayhew, A., Skidmore, B., Stevens, A., & others. (2017). Identifying approaches for assessing methodological and reporting quality of systematic reviews: A descriptive study. Systematic Reviews, 6(1), 117. https://doi.org/10.1186/s13643-017-0507-6
  48. Rana, M. M., Chowdhury, S. R., Siddiqee, M. S., Momo, E. N., Yusuf, A., & Rahman, M. M. (2026). Thirty years of digital entrepreneurship research through a systematic review and bibliometric analysis. Future Business Journal, 12(1), 35. https://doi.org/10.1186/s43093-026-00739-3
  49. Shala, B., Lahu, A., Azizi, K., Behluli, B., Brajshori, N., & Beqiri, P. (2025). Digital Healthcare Transformation: A Systematic Review of Academic Research Trends (2010–2025). E3S Web of Conferences, 669, 05005. https://doi.org/10.1051/e3sconf/202566905005
  50. Sikandar, H., Abbas, A. F., Khan, N., & Qureshi, M. I. (2022). Digital technologies in healthcare: A systematic review and bibliometric analysis. https://doi.org/10.3991/ijoe.v18i08.31961
  51. Sylla, B., Ismaila, O., & Diallo, G. (2025). 25 years of digital health toward universal health coverage in low-and middle-income countries: Rapid systematic review. Journal of Medical Internet Research, 27, e59042. https://doi.org/10.2196/59042
  52. Tekin, A. (2025). Global Research Trends and Thematic Development on the Biological Protective Effects of Boron: A Comprehensive Bibliometric Analysis (1990–2025). Journal of Anatolian Environmental and Animal Sciences, 10(6), 844–860. https://doi.org/10.35229/jaes.1773399
  53. Tran, B. X., McIntyre, R. S., Latkin, C. A., Phan, H. T., Vu, G. T., Nguyen, H. L. T., Ho, R. C., & others. (2019). The current research landscape on the artificial intelligence application in the management of depressive disorders: A bibliometric analysis. International Journal of Environmental Research and Public Health, 16(12), 2150. https://doi.org/10.3390/ijerph16122150
  54. Waqas, A., Teoh, S. H., Lapão, L. V., Messina, L. A., & Correia, J. C. (2020). Harnessing telemedicine for the provision of health care: Bibliometric and scientometric analysis. Journal of Medical Internet Research, 22(10), e18835. https://doi.org/10.2196/18835
  55. Yang, S., & Zhu, J. (2024). Analysis of Global Research Trends and Development Trends in Smart Healthcare: A Bibliometric Study. Proceedings of the 2024 3rd International Symposium on Robotics, Artificial Intelligence and Information Engineering, 81–87. https://doi.org/10.1145/3689299.368931
  56. Yao, L., Liu, Y., Wang, T., Han, C., Li, Q., Li, Q., Wang, Y., & others. (2025). Global trends of big data analytics in health research: A bibliometric study. Frontiers in Medicine, 12, 1456286. https://doi.org/10.3389/fmed.2025.1456286
  57. Yeung, A. W. K., Torkamani, A., Butte, A. J., Glicksberg, B. S., Schuller, B., Rodriguez, B., & Atanasov, A. G. (2023). The promise of digital healthcare technologies. Frontiers in Public Health, 11, 1196596. https://doi.org/10.3389/fpubh.2023.1196596
  58. Zhang, R., & Wang, H. (2025). Insights into the technological evolution and research trends of mobile health: Bibliometric analysis. Healthcare, 13(7), 740. https://doi.org/10.3390/healthcare13070740
  59. Zhi, H., & Zolotova, M. (2025). Wearable devices & elderly: A bibliometric analysis of 2014–2024. Healthcare, 13(16), 2066. https://doi.org/10.3390/healthcare13162066
  60. Zhou, X., Hu, D., Xiong, H., Zhou, H., Xu, H., & Tang, H. (2026). Bibliometric analysis of home-based self-health monitoring in chronic disease management: Current trends and research activity in telemedicine. DIGITAL HEALTH, 12, 20552076261433666. https://doi.org/10.1177/20552076261433666
  61. Zhou, Z., Xiang, Y., Liu, C., Huang, X., & Fu, Y. (2025). Quantitative evaluation and optimization of AI policy and regulatory texts for smart healthcare. Frontiers in Public Health, 13, 1731013. https://doi.org/10.3389/fpubh.2025.1731013
  62. Zhu, J., & Liu, W. (2020). A tale of two databases: The use of Web of Science and Scopus in academic papers. Scientometrics, 123(1), 321–335. https://doi.org/10.1007/s11192-020-03387-8
  63. Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/109442811456