Implementing Guideline-Based, Experience-Based, and Case-Based Approaches to Enrich Decision Support for the Management of Breast Cancer Patients in the DESIREE Project

Stud Health Technol Inform. 2018;255:190-194.

Abstract

DESIREE is a European-funded project to improve the management of primary breast cancer. We have developed three decision support systems (DSSs), a guideline-based, an experience-based, and a case-based DSSs, resp. GL-DSS, EXP-DSS, and CB-DSS, that operate simultaneously to offer an enriched multi-modal decision support to clinicians. A breast cancer knowledge model has been built to describe within a common ontology the data model and the termino-ontological knowledge used for representing breast cancer patient cases. It allows for rule-based and subsumption-based reasoning in the GL-DSS to provide best patient-centered reconciled care plans. It also allows for using semantic similarity in the retrieval algorithm implemented in the CB-DSS. Rainbow boxes are used to display patient cases similar to a given query patient. This innovative visualization technique translates the question of deciding the most appropriate treatment into a question of deciding the colour dominance among boxes.

Keywords: Breast cancer; Case-based decision support; Clinical practice guidelines; Decision support systems; Ontology; Rainbow boxes.

MeSH terms

  • Breast
  • Breast Neoplasms* / therapy
  • Decision Support Systems, Clinical*
  • Female
  • Humans
  • Software