Background: Molecular tumor boards (MTBs) play a pivotal role in personalized oncology, leveraging complex data sets to tailor therapy for cancer patients. The integration of digital support and visualization tools is essential in this rapidly evolving field facing fast-growing data and changing clinical processes. This study addresses the gap in understanding the evolution of software and visualization needs within MTBs and evaluates the current state of digital support. Alignment between user requirements and software development is crucial to avoid waste of resources and maintain trust.
Methods: In two consecutive nationwide medical informatics projects in Germany, surveys and expert interviews were conducted as stage 1 (n = 14), stage 2 (n = 30), and stage 3 (n = 9). Surveys, via the SoSci Survey tool, covered participants' roles, working methods, and support needs. The second survey additionally addressed requirements for visualization solutions in molecular tumor boards. These aimed to understand diverse requirements for preparation, implementation, and documentation. Nine semi-structured expert interviews complemented quantitative findings through open discussion.
Results: Using quantitative and qualitative analyses, we show that existing digital tools may improve therapy recommendations and streamline MTB case preparation, while continuous training and system improvements are needed.
Conclusions: Our study contributes to the field by highlighting the importance of developing user-centric, customizable software solutions that can adapt to the fast-paced environment of MTBs to advance personalized oncology. In doing so, it lays the foundation for further advances in personalized medicine in oncology and points to a shift towards more efficient, technology-driven clinical decision-making processes. This research not only enriches our understanding of the integration of digital tools into MTBs, but also signals a broader shift towards technological innovation in healthcare.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11736948 | PMC |
http://dx.doi.org/10.1186/s12911-024-02821-8 | DOI Listing |
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