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A data mining approach to analyze non-compliance with a guideline for the treatment of breast cancer.

Authors
  • Razavi, Amir R
  • Gill, Hans
  • Ahlfeldt, Hans
  • Shahsavar, Nosrat
Type
Published Article
Journal
Studies in health technology and informatics
Publication Date
Jan 01, 2007
Volume
129
Issue
Pt 1
Pages
591–595
Identifiers
PMID: 17911785
Source
Medline
License
Unknown

Abstract

Postmastectomy radiotherapy (PMRT) 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 non-compliance between the actual treatment and the PMRT guideline. Data from breast cancer patients admitted to Linköping 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.

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