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Integrating clinical decision support systems in pediatric oncology: A scoping review of applications, implementation
Mengyao Zhu1, Zhiyuan Yao1, Xinyu Feng2
1Department of Thoracic Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Background:
Clinical Decision Support Systems (CDSSs) are acknowledged as tools that leverage health data analytics to support clinical decision-making; however, systematic evidence regarding their deployment in pediatric oncology remains limited. This gap in the literature gives rise to unique challenges, particularly in addressing the individualized nature of pediatric cancer diagnosis, treatment, and the "doctor-nurse-patient" tripartite decision-making.
Aim:
To synthesize evidence on the application of CDSSs in the management of pediatric cancer patients, elucidate prevailing patterns of clinical utilization, and critically examine barriers to effective implementation in real-world practice.
Methods:
This review adhered to PRISMA-ScR guidelines. Six databases were systematically searched: PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), Wanfang Database, and China Science and Technology Journal Database (VIP). Two independent reviewers conducted study selection and content analysis to ensure rigor and minimize bias.
Results:
Seventeen studies were included, revealing four critical pertinent issues: (1) CDSSs demonstrate potential for application in pediatric cancer management; (2) the majority of applications are concentrated in the treatment phase (41.2%), with comparatively less emphasis on risk assessment, diagnosis, nursing workflow, and survivorship care; (3) user interaction and follow-up functionalities remain suboptimal and warrant further optimization; and (4) there is a critical need for multicenter randomized controlled trials to validate the clinical efficacy of CDSSs.
Conclusions:
This review delineates the characteristics of included studies, the specific features of CDSSs, and their clinical applications, including decision-making content, system functionalities, evaluation indicators of application effectiveness, in pediatric cancer. It also identifies critical gaps and future research directions to advance the field.
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