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Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards
Certified Cancer Centers must present all patients in multidisciplinary tumor boards (MTB), including standard cases with well-established treatment strategies. Too many standard cases can absorb much of the available time, which can be unfavorable for the discussion of complex cases. In any case, t...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246794/ https://www.ncbi.nlm.nih.gov/pubmed/37285355 http://dx.doi.org/10.1371/journal.pdig.0000054 |
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author | Ural, Yasemin Elter, Thomas Yilmaz, Yasemin Hallek, Michael Datta, Rabi Raj Kleinert, Robert Heidenreich, Axel Pfister, David |
author_facet | Ural, Yasemin Elter, Thomas Yilmaz, Yasemin Hallek, Michael Datta, Rabi Raj Kleinert, Robert Heidenreich, Axel Pfister, David |
author_sort | Ural, Yasemin |
collection | PubMed |
description | Certified Cancer Centers must present all patients in multidisciplinary tumor boards (MTB), including standard cases with well-established treatment strategies. Too many standard cases can absorb much of the available time, which can be unfavorable for the discussion of complex cases. In any case, this leads to a high quantity, but not necessarily a high quality of tumor boards. Our aim was to develop a partially algorithm-driven decision support system (DSS) for smart phones to provide evidence-based recommendations for first-line therapy of common urological cancers. To assure quality, we compared each single digital decision with recommendations of an experienced MTB and obtained the concordance.1873 prostate cancer patients presented in the MTB of the urological department of the University Hospital of Cologne from 2014 to 2018 have been evaluated. Patient characteristics included age, disease stage, Gleason Score, PSA and previous therapies. The questions addressed to MTB were again answered using DSS. All blinded pairs of answers were assessed for discrepancies by independent reviewers. Overall concordance rate was 99.1% (1856/1873). Stage specific concordance rates were 97.4% (stage I), 99.2% (stage II), 100% (stage III), and 99.2% (stage IV). Quality of concordance were independent of age and risk profile. The reliability of any DSS is the key feature before implementation in clinical routine. Although our system appears to provide this safety, we are now performing cross-validation with several clinics to further increase decision quality and avoid potential clinic bias. |
format | Online Article Text |
id | pubmed-10246794 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-102467942023-06-08 Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards Ural, Yasemin Elter, Thomas Yilmaz, Yasemin Hallek, Michael Datta, Rabi Raj Kleinert, Robert Heidenreich, Axel Pfister, David PLOS Digit Health Research Article Certified Cancer Centers must present all patients in multidisciplinary tumor boards (MTB), including standard cases with well-established treatment strategies. Too many standard cases can absorb much of the available time, which can be unfavorable for the discussion of complex cases. In any case, this leads to a high quantity, but not necessarily a high quality of tumor boards. Our aim was to develop a partially algorithm-driven decision support system (DSS) for smart phones to provide evidence-based recommendations for first-line therapy of common urological cancers. To assure quality, we compared each single digital decision with recommendations of an experienced MTB and obtained the concordance.1873 prostate cancer patients presented in the MTB of the urological department of the University Hospital of Cologne from 2014 to 2018 have been evaluated. Patient characteristics included age, disease stage, Gleason Score, PSA and previous therapies. The questions addressed to MTB were again answered using DSS. All blinded pairs of answers were assessed for discrepancies by independent reviewers. Overall concordance rate was 99.1% (1856/1873). Stage specific concordance rates were 97.4% (stage I), 99.2% (stage II), 100% (stage III), and 99.2% (stage IV). Quality of concordance were independent of age and risk profile. The reliability of any DSS is the key feature before implementation in clinical routine. Although our system appears to provide this safety, we are now performing cross-validation with several clinics to further increase decision quality and avoid potential clinic bias. Public Library of Science 2023-06-07 /pmc/articles/PMC10246794/ /pubmed/37285355 http://dx.doi.org/10.1371/journal.pdig.0000054 Text en © 2023 Ural et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ural, Yasemin Elter, Thomas Yilmaz, Yasemin Hallek, Michael Datta, Rabi Raj Kleinert, Robert Heidenreich, Axel Pfister, David Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
title | Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
title_full | Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
title_fullStr | Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
title_full_unstemmed | Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
title_short | Validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
title_sort | validation and implementation of a mobile app decision support system for prostate cancer to improve quality of tumor boards |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246794/ https://www.ncbi.nlm.nih.gov/pubmed/37285355 http://dx.doi.org/10.1371/journal.pdig.0000054 |
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