This paper is in the following e-collection/theme issue:

Digital Health Reviews (1626) Registered Report (723) Clinical Information and Decision Making (1765) Diabetes (240) Decision Support for Health Professionals (1438)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51024, first published .
Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review

Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review

Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review

Authors of this article:

Shan Huang1 Author Orcid Image ;   Yuzhen Liang2 Author Orcid Image ;   Jiarui Li3 Author Orcid Image ;   Xuejun Li4, 5, 6 Author Orcid Image
Article Authors Cited by (17) Tweetations (4) Metrics

Journals

  1. Overgaard K, Mohamed R, Andersen T, Lambrechtsen J, Egstrup K, Auscher S. ProtecT-2-D trial protocol: cardiovascular protection in patients with type 2 diabetes and established heart and/or vascular disease at a cardio-metabolic clinic—a randomized controlled trial. Cardiovascular Diabetology 2024;23(1) View
  2. Tlili N, Robert L, Gerard E, Lemaitre M, Vambergue A, Beuscart J, Quindroit P. A systematic review of the value of clinical decision support systems in the prescription of antidiabetic drugs. International Journal of Medical Informatics 2024;191:105581 View
  3. von Sengbusch S, Biester T. Praktische Nutzung von künstlicher Intelligenz in der Diabetologie. Die Diabetologie 2024;20(7):799 View
  4. Subrata S, Masithoh R, Sasongko D. Indonesian Nurses’ Perspectives on Developing Mobile Applications to Improve Diabetes Management in the Community: A Qualitative Study. Pacific Rim International Journal of Nursing Research 2024;29(1):137 View
  5. Christy A, Fernanda F, Insani W, Abdulah R. Pharmacist-Led Digital Health Interventions for Patients with Diabetes: A Systematic Review. Journal of Multidisciplinary Healthcare 2025;Volume 18:101 View
  6. Giger O, Pfitzer E, Mekniran W, Gebhardt H, Fleisch E, Jovanova M, Kowatsch T. Digital health technologies and innovation patterns in diabetes ecosystems. DIGITAL HEALTH 2025;11 View
  7. Grechuta K, Shokouh P, Bayer V, Kraemer H, Gilbert J, Jin S, Alhussein A. Analytical validation of Exandra: a clinical decision support system for promoting guideline-directed therapy of type-2 diabetes in primary care – a collaborative study with experts from Diabetes Canada. BMC Medical Informatics and Decision Making 2025;25(1) View
  8. Kostiuk M, Moore S, Kramer E, Gilens J, Sarwal A, Saxon D, Thomas J, Oser T. Assessment and Intervention for Diabetes Distress in Primary Care Using Clinical and Technological Interventions: Protocol for a Single-Arm Pilot Trial. JMIR Research Protocols 2025;14:e62916 View
  9. Montagna M, Chiabrando F, De Lorenzo R, Rovere Querini P. Impact of Clinical Decision Support Systems on Medical Students’ Case-Solving Performance: Comparison Study with a Focus Group. JMIR Medical Education 2025;11:e55709 View
  10. Zheng R, Jiang X, Shen L, He T, Ji M, Li X, Yu G. Investigating Clinicians’ Intentions and Influencing Factors for Using an Intelligence-Enabled Diagnostic Clinical Decision Support System in Health Care Systems: Cross-Sectional Survey. Journal of Medical Internet Research 2025;27:e62732 View
  11. van der Lubbe S, Goh L, Kontopantelis E, Tam W, Valderas J. Measuring guideline concordance via electronic health records: a new model for estimating concordance scores. BMJ Quality & Safety 2025:bmjqs-2025-018494 View
  12. Guiriguet C, Bustos M, Cantenys R, Hermosilla E, Camús J, Medina M, Martín C, Gonçalves A, Gavaldà-Espelta E, Cos F, Nadal N, Fàbregas M, Fina F, Méndez-Boo L, Balló E, Canela M, Lladó M, Mas A, Coma E, Rodoreda S. Enhancing the follow-up for patients with type 2 diabetes mellitus using a proactive scheduling computer tool: A paired cohort study in primary care. Primary Care Diabetes 2025;19(3):334 View
  13. Mo Y, Zhao F, Yuan L, Xing Q, Zhou Y, Wu Q, Li C, Lin J, Wu H, Deng S, Zhang M. Healthcare providers’ perceptions of artificial intelligence in diabetes care: A cross-sectional study in China. International Journal of Nursing Sciences 2025;12(3):218 View
  14. Rodrigues D, Jasmins C, Ladeiras-Lopes R, Patrao L, Rodrigues E. Personalized Digital Care Pathways Enable Enhanced Patient Management as Perceived by Health Care Professionals: Mixed-Methods Study. JMIR Human Factors 2025;12:e68581 View
  15. Kim M, Choi Y, Prakash B, Lee Y, Lim S, Woo S. A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021). Frontiers in Medicine 2025;12 View
  16. Nimri R, Phillip M. Enhancing Care in Type 1 Diabetes with Artificial Intelligence Driven Clinical Decision Support Systems. Hormone Research in Paediatrics 2025;98(4):384 View

Books/Policy Documents

  1. Hassan M. Revolutionizing Healthcare Experience With Digital Medical Tourism. View