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Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
2007 (English)In: MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2, IOS Press, 2007, 591-595 p.Conference paper, Published paper (Refereed)
Abstract [en]

Postmastectomy radiotherapy (PAMT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of noncompliance between the actual treatment and the PMRT guideline.Data from breast cancer patients admitted to Linkoping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

Place, publisher, year, edition, pages
IOS Press, 2007. 591-595 p.
Series
Studies in Health Technology and Informatics, ISSN 0926-9630
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-38015Local ID: 41111ISBN: 978-1-58603-774-1 (print)OAI: oai:DiVA.org:liu-38015DiVA: diva2:258864
Conference
12th World Congress on Health (Medical) Informatics
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-08-29

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Razavi, Amir RezaGill, HansÅhlfeldt, HansShahsavar, Nosrat

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