Academic Journal
User perceptions of machine learning models as decision support for colorectal cancer multidisciplinary team conferences (AID-SIM-2): a qualitative simulation study.
| Τίτλος: | User perceptions of machine learning models as decision support for colorectal cancer multidisciplinary team conferences (AID-SIM-2): a qualitative simulation study. |
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| Συγγραφείς: | Bendix Bräuner K; Center for Surgical Sciences, Zealand University Hospital, Køge, Denmark ; Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark; Copenhagen University Hospital - North Zealand, Hillerød, Denmark; The Hospital of Mid and Western Zealand, Slagelse, Slagelse, Denmark. karob@regionsjaelland.dk., Bruun B; Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark., Bertelsen CA; Copenhagen University Hospital - North Zealand, Hillerød, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Johansen Dagenborg V; Department of Surgical Oncology, The Norwegian Radium Hospital, Oslo University Hospital, Nydalen., Safir-Hansen K; The Hospital of Mid and Western Zealand, Slagelse, Slagelse, Denmark., Sanko R; Charlie Tango, Copenhagen, Denmark., Gögenur I; Center for Surgical Sciences, Zealand University Hospital, Køge, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Konge L; Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. |
| Πηγή: | Acta oncologica (Stockholm, Sweden) [Acta Oncol] 2026 Jul 31; Vol. 65, pp. 668-678. Date of Electronic Publication: 2026 Jul 31. |
| Τύπος έκδοσης: | Journal Article; Multicenter Study |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Medical Journals Sweden AB Country of Publication: Sweden NLM ID: 8709065 Publication Model: Electronic Cited Medium: Internet ISSN: 1651-226X (Electronic) Linking ISSN: 0284186X NLM ISO Abbreviation: Acta Oncol Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2024- : [Uppsala, Sweden] : Medical Journals Sweden AB Original Publication: Stockholm, Sweden : Acta Oncologica, [1987- |
| Ιατρικοί όροι (MeSH): | Colorectal Neoplasms*/therapy , Colorectal Neoplasms*/diagnosis , Patient Care Team*/organization & administration , Clinical Decision-Making*/methods , Machine Learning* , Decision Support Techniques* , Decision Support Systems, Clinical*, Humans ; Qualitative Research ; Predictive Learning Models ; Computer Simulation ; Female |
| Περίληψη: | Background: Multidisciplinary team (MDT) conferences are considered a cornerstone of decision-making in cancer diagnostics and care. However, the current literature has not demonstrated improved patient outcomes based on the decisions of the MDT conferences. Aim: We aimed to evaluate how four different decision-support modalities impacted the decision-making process and the internal discussions in the MDTs in a multicenter simulation study, with a focus on user perceptions. Methods: Four colorectal cancer centers with MDTs participated. We performed four simulations in each center. Each simulation used a different decision-support tool: (1) Current standard, (2) Current standard plus a prediction model, (3) A structured data presentation tool, and (4) A structured data presentation tool plus the prediction model. Clinician- and model-estimated risks were compared, the treatment suggestions from each site were compared, questionnaires about user perceptions were conducted after Simulations 2, 3, and 4 using a Google Form link, and a semi-structured interview was conducted at each site after the last simulation. Results: Similar distributions of risk groups between clinicians and models were found; however, distinct discrepancies in predictions arose, particularly with higher-risk patients, highlighting the need for standardization for more complex clinical cases. The primary perceived benefit of decision support was increased standardization of care, independent of the individual physicians' personal views. However, participants emphasized the necessity of clinician autonomy to overrule tool suggestions when identifying clinical nuances not captured by the model. Conclusions: The colorectal cancer MDTs expressed a positive view regarding the use of prediction models and other forms of decision-support in their workflow. While clinicians and prediction models had similar risk score distributions, they diverged in the assessment of specific individual patients. |
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| Entry Date(s): | Date Created: 20260731 Date Completed: 20260731 Latest Revision: 20260828 |
| Update Code: | 20260828 |
| PubMed Central ID: | PMC13434538 |
| DOI: | 10.2340/1651-226X.2026.45754 |
| PMID: | 42535303 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1651-226X |
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| DOI: | 10.2340/1651-226X.2026.45754 |