Background: Like with all cancers, multidisciplinary team (MDT) meetings are the norm in bone and soft tissue tumour (BST) management too. Problem in attendance of specialists due to geographical location is the one of the key barriers to effective functioning of MDTs. To overcome this problem, virtual MDTs involving videoconferencing or telemedicine have been proposed, but however this has been seldom used and tested. The COVID-19 pandemic forced the implementation of virtual MDTs in the Oxford sarcoma service in order to maintain normal service provision. We conducted a survey among the participants to evaluate its efficacy.
Methods: An online questionnaire comprising of 24 questions organised into 4 sections was circulated among all participants of the MDT after completion of 8 virtual MDTs. Opinions were sought comparing virtual MDTs to the conventional face-to-face MDTs on various aspects. A total of 36 responses were received and were evaluated.
Results: 72.8% were satisfied with the depth of discussion in virtual MDTs and 83.3% felt that the decision-making in diagnosis had not changed following the switch from face-to-face MDTs. About 86% reported to have all essential patient data was available to make decisions and 88.9% were satisfied with the time for discussion of patient issues over virtual platform. Three-fourths of the participants were satisfied (36.1% - highly satisfied; 38.9% - moderately satisfied) with virtual MDTs and 55.6% of them were happy to attend MDTs only by the virtual platform in the future. Regarding future, 77.8% of the participants opined that virtual MDTs would be the future of cancer care and an overwhelming majority (91.7%) felt that the present exercise would serve as a precursor to global MDTs involving specialists from abroad in the future.
Conclusion: Our study shows that the forced switch to virtual MDTs in sarcoma care following the unprecedented COVID-19 pandemic to be a viable and effective alternative to conventional face-to-face MDTs. With effective and efficient software in place, virtual MDTs would also facilitate in forming extended MDTs in seeking opinions on complex cases from specialists abroad and can expand cancer care globally.
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http://dx.doi.org/10.1186/s12891-020-03925-8 | DOI Listing |
BMJ Open
August 2024
Surgical Sabermetrics Laboratory, Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, UK.
Introduction: The efficiency of multidisciplinary teams (MDTs) in cancer care hinges on facilitating clinicians' cognitive processes as they navigate complex and uncertain judgements during treatment planning. When systems and workflows are not designed to adequately support human judgement and decision-making, even experts are prone to fallible reasoning due to cognitive biases. Incomplete integration of information or biased interpretations of patient data can lead to clinical errors and delays in the implementation of treatment recommendations.
View Article and Find Full Text PDFCancer Invest
January 2024
Cancerology Coordination Center, Oncoloire of Department Loire and Northern Ardeche, France Saint-Etienne.
Multidisciplinary team meeting (MDT) became a standard of care in cancer management. The COVID-19 epidemic induced unprecedented pressure on the health system. The impact of this health crisis on MDTs held within a regional French health structures was analyzed.
View Article and Find Full Text PDFArch Dis Child
March 2024
Department of Paediatric Oncology, Southampton Children's Hospital, Southampton, UK.
Br J Surg
January 2024
Reconstructive Surgery and Regenerative Medicine Research Centre, Institute of Life Sciences, Swansea University Medical School, Swansea, UK.
Background: Cancer multidisciplinary team (MDT) meetings are under intense pressure to reform given the rapidly rising incidence of cancer and national mandates for protocolized streaming of cases. The aim of this study was to validate a natural language processing (NLP)-based web platform to automate evidence-based MDT decisions for skin cancer with basal cell carcinoma as a use case.
Methods: A novel and validated NLP information extraction model was used to extract perioperative tumour and surgical factors from histopathology reports.
Gynecol Obstet Invest
June 2024
Division of Clinical Pathology, Diagnostic Department, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Background: Gestational trophoblastic disease (GTD), comprising hydatidiform moles and gestational trophoblastic tumours, is extremely rare. Exact diagnosis is crucial to indicate the appropriate treatment and to prevent complications. The scarcity and variability in the number of cases available for reporting, lack of specialised training in GTD, and non-existence of refresher courses implies that the pathologist dealing with these rare and, at times, extremely challenging cases is not completely confident in their diagnosis.
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