Revisiting real-world data studies: Progress, value, and challenges

Zhirong Yang; Houyu Zhao; Meng Zhang; Huairong Xiang; Huakang Tu; Feng Sun

doi:10.59717/j.xinn-med.2025.100143

The Innovation Medicine > 2025 Vol. 3 > No. 3 > 100143

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Revisiting real-world data studies: Progress, value, and challenges

1.
Department of Computational Biology and Medical Big Data, Faculty of Computer Science and Control Engineering, Shenzhen University of Advanced Technology, Shenzhen 518107, China
2.
Center for AI in Medicine, Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology, Shenzhen 518107, China
3.
Center for Biomedical Information Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
4.
Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
5.
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
6.
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
7.
Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, China
8.
Zhejiang Key Laboratory of Intelligent Preventive Medicine, Hangzhou 310058, China
9.
These authors contributed equally

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Corresponding authors: sunfeng@bjmu.edu.cn (F.S.); huakangtu@zju.edu.cn (H.T.)
Received Date: December 23, 2024

Accepted Date: July 09, 2025

Published Online: August 06, 2025

The Innovation Medicine 3(3), https://doi.org/10.59717/j.xinn-med.2025.100143 | Cite this article

GRAPHICAL ABSTRACT

GRAPHICAL ABSTRACT

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PUBLIC SUMMARY

PUBLIC SUMMARY
1. Real-world data can derive from clinical records, insurance claims, health devices, and multi-omics sources.
  
  Real-world data studies investigate treatment effects, service quality, and health policy impacts.
  
  Real-world evidence can support better health care and more informed decisions.
  
  Key challenges include data quality, study validity, ethical standards, and interdisciplinary teamwork.

ABSTRACT

ABSTRACT

This review highlights the indispensable role of real-world data studies (RWS) in complementing randomized controlled trials by generating real-world evidence (RWE) that reflects diverse patient populations and clinical settings. It explores the origins and regulatory frameworks of RWS, the evolution of real-world data sources, and their expanding applications in evaluating post-marketing medical products, optimizing pre-marketing medical product development, measuring disease burden, assessing medical professional competence, evaluating healthcare service quality, and informing clinical guidelines and public health policies. The contributions of RWE to personalized medicine, healthcare resource management, and regulatory decisions underscore its significance in evidence-based practice. Despite its potential, RWS faces challenges such as data quality, purpose-driven data sharing, ethical standards, RWE validity and transparency, RWE translation, and multidisciplinary expertise, and this review proposes some strategies to advance these fields. By addressing these challenges, RWS can enhance their impact on healthcare innovation and translate into better patient outcomes globally.

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Yang Z., Zhao H., Zhang M., et al. (2025). Revisiting real-world data studies: Progress, value, and challenges. The Innovation Medicine 3:100143. https://doi.org/10.59717/j.xinn-med.2025.100143

Yang Z., Zhao H., Zhang M., et al. (2025). Revisiting real-world data studies: Progress, value, and challenges. The Innovation Medicine 3:100143. https://doi.org/10.59717/j.xinn-med.2025.100143

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