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What can we learn from 30 years development of clinical decision support system?
Yifan Zhu1, Shuangyi Yin1, Yalin Song2
1Translational Medicine Center, The Second College of Clinical Medicine, Henan University, Kaifeng, Henan 475000, China.
International Journal of Medical Informatics
|July 10, 2026
Summary
Clinical decision support systems (CDSS) increasingly focus on data processing, neglecting clinical applications and medical knowledge. This trend must reverse to improve CDSS utility.
Area of Science:
- Medical Informatics
- Health Systems Research
Background:
- Clinical decision support systems (CDSS) are crucial for enhancing clinician decision-making.
- Low clinical adoption rates hinder the full potential of current CDSS.
Purpose of the Study:
- To systematically analyze the evolution and trends of CDSS research over 30 years.
- To identify factors influencing CDSS development and clinical utility.
Main Methods:
- A comprehensive literature review of CDSS publications from 1995 to 2024 in PubMed and IEEE.
- Analysis of 34,100 publications across various journal quartiles and topic trends.
Main Results:
- CDSS development from 2007-2024 prioritized data processing techniques over clinical applications.
- Attention to medical knowledge and clinical guidelines declined amidst rising interest in knowledge graphs.
- Interpretability gained traction, but focus on clinical reasoning theory decreased.
Conclusions:
- The shift towards data-centric paradigms has diminished the clinical relevance of CDSS.
- Reversing this trend is essential to enhance the practical utility of CDSS in healthcare settings.
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