ArticleTranslational lung cancer research2020
Looking through the eyes of the multidisciplinary team: the design and clinical evaluation of a decision support system for lung cancer care.
Article in Translational lung cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Impact of Multidisciplinary Team Care on Patient-Reported Outcomes in Patients with Lung Cancer: A Systematic Review.Current oncology (Toronto, Ont.) · 2025Pooled it
- Advancing Human-Centered AI in Clinical Decision Support: Sociocognitive Human-in-the-Loop Study in HIV Care.Journal of medical Internet research · 2026Article
- Revealing the Physician's Task Conceptualization in Melanoma Treatment: Qualitative User Experience Study.JMIR cancer · 2026Article
- AI-MDT: an automatic and intelligent multidisciplinary team consultations platform for lung cancer diagnosis.Journal of cancer research and clinical oncology · 2026Article
- Assessing clinician performance using a multi-modality clinical decision-support system for lung cancer prognostication.Scientific reports · 2025Article
- The initiation of the second-step intradisciplinary tumor board discussion and its impact on treatment decision. Retrospective data analysis of 12 years' experience in a tertiary oncology center.Frontiers in oncology · 2025Article
- Artificial intelligence in clinical decision support systems for oncology.International journal of medical sciences · 2023Review
- Optimising the quality of multidisciplinary team meetings: A narrative review.Cancer medicine · 2022Review
- Quality indicators and excellence requirements for a multidisciplinary lung cancer tumor board by the Spanish Lung Cancer Group.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022Review
- Virtual Multidisciplinary Tumor Boards: A Narrative Review Focused on Lung Cancer.Pulmonary therapy · 2021Review
- The Impact of Multidisciplinary Team Meetings on Patient Management in Oncologic Thoracic Surgery: A Single-Center Experience.Cancers · 2021Article
- Article
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Authors and funding
7 authors.
Funding
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Abstract
backgroundDecision-making in lung cancer is complex due to a rapidly increasing amount of diagnostic data and treatment options. The need for timely and accurate diagnosis and delivery of care demands high-quality multidisciplinary team (MDT) collaboration and coordination. Clinical decision support systems (CDSSs) can potentially support MDTs in constructing a shared mental model of a patient case. This enables the team to assess the strength and completeness of collected diagnostic data, stratification for the right personalized therapy driven by clinical stage and other treatment-influencing factors, and adapt care management strategies when needed. Current CDSSs often have a suboptimal fit into the decision-making workflow, which hampers their impact in clinical practice.
methodsA CDSS for multidisciplinary decision-making in lung cancer was designed to support the abovementioned goals through presentation of relevant clinical data in line with existing mental model structures of the MDT members. The CDSS was tested in a simulated multidisciplinary tumor board meeting for primary diagnosis and treatment selection, based on de-identified primary lung cancer cases (n=8). Decision course analysis, eye-tracking data and questionnaires were used to assess the impact of the CDSS on constructing shared mental models to improve the decision-making process and outcome.
resultsThe CDSS supported the team in their self-correcting capacity for accurate diagnosis and TNM classification. It enabled cross-validation of diagnostic findings, surfaced discordance between diagnostic tests and facilitated cancer staging according the diagnostic evidence, as well as spotting contra-indications for personalized treatment selection.
conclusionsThis study shows the potential of CDSS on clinical decision making, when these systems are properly designed in line with clinical thinking. The presented setup enables assessment of the impact of CDSS design on clinical decision making and optimization of CDSSs to maximize their effect on decision quality and confidence.
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