Hoier, David, Groß-Ophoff-Müller, Carolin, Franklin, Cindy
ORCID: 0000-0001-9142-5423, Hallek, Michael
ORCID: 0000-0002-7425-4455, von Stebut, Esther
ORCID: 0000-0001-9802-9642, Elter, Thomas
ORCID: 0000-0003-0748-7600, Mauch, Cornelia
ORCID: 0000-0002-3989-0536, Kreuzberg, Nicole and Koll, Philipp
ORCID: 0009-0001-2425-5345
(2024).
Digital decision support for structural improvement of melanoma tumor boards: using standard cases to optimize workflow.
Journal of Cancer Research and Clinical Oncology, 150 (3).
pp. 1-13.
Springer Nature.
ISSN 1432-1335
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s00432-024-05627-3.pdf Bereitstellung unter der CC-Lizenz: Creative Commons Attribution. Download (1MB) |
Abstract
[Artikel-Nr.: 115] Purpose: Choosing optimal cancer treatment is challenging, and certified cancer centers must present all patients in multidisciplinary tumor boards (MDT). Our aim was to develop a decision support system (DSS) to provide treatment recommendations for apparently simple cases already at conference registration and to classify these as “standard cases”. According to certification requirements, discussion of standard cases is optional and would thus allow more time for complex cases. Methods: We created a smartphone query that simulated a tumor conference registration and requested all information needed to provide a recommendation. In total, 111 out of 705 malignant melanoma cases discussed at a skin cancer center from 2017 to 2020 were identified as potential standard cases, for which a digital twin recommendation was then generated by DSS. Results: The system provided reliable advice in all 111 cases and showed 97% concordance of MDT and DSS for therapeutic recommendations, regardless of tumor stage. Discrepancies included two cases (2%) where DSS advised discussions at MDT and one case (1%) with deviating recommendation due to advanced patient age. Conclusions: Our work aimed not to replace clinical expertise but to alleviate MDT workload and enhance focus on complex cases. Overall, our DSS proved to be a suitable tool for identifying standard cases as such, providing correct treatment recommendations, and thus reducing the time burden of tumor conferences in favor for the comprehensive discussion of complex cases. The aim is to implement the DSS in routine tumor board software for further qualitative assessment of its impact on oncological care.
| Item Type: | Article |
| Creators: | Creators Email ORCID ORCID Put Code Hoier, David UNSPECIFIED UNSPECIFIED UNSPECIFIED Groß-Ophoff-Müller, Carolin UNSPECIFIED UNSPECIFIED UNSPECIFIED Kreuzberg, Nicole UNSPECIFIED UNSPECIFIED UNSPECIFIED |
| URN: | urn:nbn:de:hbz:38-815190 |
| Identification Number: | 10.1007/s00432-024-05627-3 |
| Journal or Publication Title: | Journal of Cancer Research and Clinical Oncology |
| Volume: | 150 |
| Number: | 3 |
| Page Range: | pp. 1-13 |
| Number of Pages: | 13 |
| Date: | 8 March 2024 |
| Publisher: | Springer Nature |
| ISSN: | 1432-1335 |
| Language: | English |
| Faculty: | Faculty of Medicine |
| Divisions: | Faculty of Medicine > Dermatologie > Klinik und Poliklinik für Dermatologie und Venerologie Faculty of Medicine > Innere Medizin > Klinik I für Innere Medizin - Hämatologie und Onkologie Faculty of Medicine > Weitere > Centrum für integrierte Onkologie (CIO) |
| Subjects: | Medical sciences Medicine |
| Uncontrolled Keywords: | Keywords Language Malignant melanoma ; Algorithm ; Multidisciplinary tumor board (MDT) ; Tumor board evaluation ; Digital recommendations ; Documentation burden · Digital health ; Mobile application ; Expert-curated decision support system ; Oncology English |
| ['eprint_fieldname_oa_funders' not defined]: | Publikationsfonds UzK |
| Refereed: | Yes |
| URI: | http://kups.ub.uni-koeln.de/id/eprint/81519 |
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https://orcid.org/0000-0001-9142-5423