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

Scoping Review Protocols (584) Decision Support for Health Professionals (2360) Participatory Design and Participatory Research (542) Artificial Intelligence (5054) Co-Design & Participatory Design (377)

Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58185, first published .
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Challenges and Facilitation Approaches for the Participatory Design of AI-Based Clinical Decision Support Systems: Protocol for a Scoping Review

Challenges and Facilitation Approaches for the Participatory Design of AI-Based Clinical Decision Support Systems: Protocol for a Scoping Review

Authors of this article:

Tabea Rambach1 Author Orcid Image ;   Patricia Gleim2 Author Orcid Image ;   Sekina Mandelartz2 Author Orcid Image ;   Carolin Heizmann2 Author Orcid Image ;   Christophe Kunze1 Author Orcid Image ;   Philipp Kellmeyer2, 3 Author Orcid Image
Article Authors Cited by (10) Tweetations Metrics

Journals

  1. Yu S, Lee S, Hwang H. The ethics of using artificial intelligence in medical research. Kosin Medical Journal 2024;39(4):229 View
  2. Tun H, Rahman H, Naing L, Malik O. Trust in Artificial Intelligence–Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review. Journal of Medical Internet Research 2025;27:e69678 View
  3. Kreutz J, Lauten P, Chatzis G, Nabrotzki M, Patsalis N, Syntila S, Lapp H, Schieffer B, Markus B. Patient risk evaluation for transcatheter aortic valve replacement (PRE-TAVR) — identification of real-time predictors of short- and long-term mortality. Clinical Research in Cardiology 2025;114(11):1574 View
  4. El-Bassel N, David J, Mukherjee T, Aggarwal M, Wu E, Gilbert L, Walters S, Chandler R, Hunt T, Frye V, Aimee Campbell , Goddard-Eckrich D, Keyes K, Benjamin S, Balise R, Muresan S, Aragundi E, Chen M, Davé P, Lounsbury D, Sabounchi N, Feaster D, Huang T, Zheng T. The Practical, Robust Implementation and Sustainability (PRISM)-capabilities model for use of Artificial Intelligence in community-engaged implementation science research. Implementation Science 2025;20(1) View
  5. Gadepalli Sri Pratyak A. Artificial Intelligence in Clinical Decision-Making: Current Applications, Challenges, and Future Directions in Modern Healthcare. Cureus 2026 View
  6. Rambach T, Gleim P, Heizmann C, Kellmeyer P, Kunze C. Participatory Design of AI-Based Clinical Decision Support Systems: Scoping Review. JMIR Medical Informatics 2026;14:e88368 View
  7. Hu H, LI R, Yin Y, Liu Y, Wang X. Human factors engineering in intelligent medical devices: paradigm evolution, core issues and frontier prospects. Frontiers in Industrial Engineering 2026;4 View
  8. Su H, Zou Y, Fang W, Hu Y, Yuan Z, Zhang Q, Qin W. “It Has to Be Done Manually”: A Qualitative Study of Clinical Nursing Information System as Both Enforcer and Barrier in Nursing Work. Asian Nursing Research 2026 View
  9. Schließer J, Schlecht C, Hemming N, Brückner A, Kirschenbaum A, Hein P. Die Rolle des Menschen in Datenpipelines: Erkenntnisse aus vier KI-Anwendungsfällen in KMU. HMD Praxis der Wirtschaftsinformatik 2026 View

Books/Policy Documents

  1. Plafky C, Badertscher H. Künstliche Intelligenz in der Sozialen Arbeit. View