ArticleJMIR human factors2025
Need Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: Qualitative Descriptive Study.
Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors.
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Abstract
backgroundThe rapid advancement of next-generation sequencing has significantly expanded the landscape of precision medicine. However, health care professionals face increasing challenges in keeping pace with the growing body of oncological knowledge and integrating it effectively into clinical workflows. Precision oncology decision support (PODS) tools aim to assist clinicians in navigating this complexity, yet their current functionalities only partially address clinical needs. A lack of comprehensive needs assessment may result in unaddressed requirements, limiting the effectiveness of these tools in real-world practice.
objectiveThis study aimed to explore clinicians' needs and expectations regarding the functionalities of integrated PODS tools, providing insights into essential features that could enhance their usability and impact.
methodsWe conducted a qualitative investigation at Peking University Cancer Hospital to explore clinicians' needs and expectations for the functions of integrated PODS tools. Data were collected through 143 structured participant observations during multidisciplinary team meetings and 17 in-depth semistructured interviews with a diverse group of oncology specialists, including physicians, surgeons, molecular biologists, radiotherapists, radiologists, and pathologists. Thematic analysis was applied to identify key functional requirements, and a requirements framework was formed.
resultsThree overarching functional needs emerged: (1) better access to oncological knowledge, including support for therapy selection (guidelines, conferences, and consensuses), clinical trials, drug and treatment information, and complex case knowledge, as well as improved diagnostic and prognostic insights; (2) clinical contextualization and resource navigation, referring to the process of contextualizing scientific knowledge within real-world clinical settings, including access to clinical trials and drugs, along with predictive models for treatment response; and (3) support abilities in the decision-making process, highlighting the need for integration of flexible biological knowledge and phenotypic data; automated patient information synthesis; improved data visualization; and optimized retrieval, recommendation, and question-answering functionalities. A functional framework for integrated PODS tools was proposed based on these findings.
conclusionsThe study conducted a qualitative descriptive observation and interview in the use, needs of integrated PODS tools. PODS tools serve as complex, multilevel decision support systems. A clear understanding of clinicians' actual needs is crucial for their refinement and practical adoption. By capturing perspectives directly from oncology professionals, this study provides actionable insights into the functional enhancements required for PODS tools, ultimately aiming to bridge the gap between genomic advancements and clinical decision-making in precision oncology.
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