Accepted for/Published in: JMIR Human Factors
Date Submitted: Oct 14, 2024
Date Accepted: Jun 26, 2025
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Need Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: A Mixed-Method Qualitative Descriptive Study
ABSTRACT
Background:
With the advancement of next generation sequencing, healthcare professionals face challenges in keeping pace with increasingly extensive body of knowledge and information in prediction medicine. In oncology area, current functionalities of precision oncology decision support (PODS) tools only partially address clinicians' needs, leaving certain clinical requirements within PODS inadequately defined. Lack of need analysis may result in unaddressed clinician requirements.
Objective:
We aimed to explore clinicians’ needs and expectations of functions in integrated PODS tools.
Methods:
Qualitative investigation was held in Peking University Cancer Hospital (PUCH). Data were derived from structured participant observation records (n=143) from multidisciplinary team (MDT) and in-depth interviews (n=17). Participants included physicians, surgeons, molecular biologists, radiotherapists, radiologists, and pathologists.
Results:
Three main themes of functions arose from our data: better access to oncological knowledge; feasibility support; and support abilities demands in decision-making process. Oncological knowledge themes included support in therapies (guidelines, conferences, and consensuses; clinical trials; information of drugs and treatments; and knowledge of complex cases), diagnosis and prognosis. Feasibility support themes included accessibility of clinical trials, accessibility of drugs, and prediction models. Decision-making process support themes included flexible biological knowledge and phenotypes, automatic integration of patient information, better visualization of information, and optimization in retrieval, recommendation and question answering. Several example quotes describing these themes were provided. A functional framework of needs for integrated PODS tools was proposed.
Conclusions:
PODS is complex, multi-level decision support. Clear elucidation of the actual clinical needs may impact the improvement of PODS. This study presents unique perspectives directly from clinicians in this new arena of precision oncology.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.