What can we learn from 30 years development of clinical decision support system?

Authors

Yifan Zhu, Shuangyi Yin, Yalin Song, Ling Bai, Zheng Guan, Yuquan Lu

Published in

International journal of medical informatics. Volume 220. Pages 106591. Jul 07, 2026. Epub Jul 07, 2026.

Abstract

Clinical decision support systems (CDSS) have emerged as a vital means to boost decision-making capabilities of clinicians, but still exhibit low clinical adoption rates. Systematically exploring the evolution, status, topic trends and variations of CDSS is expected to guide the development of next-generation CDSS.
This study investigated scientific publications pertaining to CDSS over a 30-year period. Publications about primary topic (clinical decision support system) and 24 sub-topics grouped into application purposes, technical features and medical resources in PubMed and IEEE from 1 January 1995 to 31 December 2024 were collected. A total of 34,100 publications across 4315 journals were identified, where the number of publications belonged to Q1, Q2, Q3, and Q4 journals was 9721, 5074, 2667 and 1328 respectively, and 15,310 publications were not indexed by Journal Citation Reports in the publication year.
This study found that data processing techniques from 2007 to 2024 profoundly steered CDSS toward data centric paradigms, whereas its clinical applications were significantly neglected from thereon. Uncannily, with the rising attention to "knowledge graph", its two important knowledge resources, "medical knowledge" and "clinical guidelines", have simultaneously declined in attention. Similarly, although interpretability has gradually gained visibility, focus on clinical reasoning/thinking/decision (RTD) theory has paradoxically declined.
Concerning data processing techniques has significantly upwardly diverged with declined focus on medical related concerning. Such a focus shift has reduced contemporary CDSS to a technical showcase of data manipulation, a trend that should be reversed to enhance subsequent clinical utility.

PMID:
42430884
Bibliographic data and abstract were imported from PubMed on 11 Jul 2026.

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