Using formal concept analysis to discover patterns of non-compliance with clinical practice guidelines: a case study in the management of breast cancer

  • Authors:

  • Nizar Messai;Jacques Bouaud;Marie-Aude Aufaure;Laurent Zelek;Brigitte Séroussi

  • Affiliations:

  • École Centrale Paris, MAS, Châtenay-Malabry, France;AP-HP, STIM, Paris, France and INSERM, UMR, CRC, Paris, France;École Centrale Paris, MAS, Châtenay-Malabry, France;Universitée Paris 13, UFR, SMBH, Bobigny, France and AP-HP, Hôpital Avicenne, Service d'Oncologie Médicale, Bobigny, France;UPMC, UFR de Médecine, Paris, France and AP-HP, Hôpital Tenon, Département de Santé Publique, Paris, France and Université Paris 13, UFR, SMBH, LIM&BIO, Bobigny, Franc ...

  • Venue:
  • AIME'11 Proceedings of the 13th conference on Artificial intelligence in medicine
  • Year:
  • 2011

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Abstract

Clinical decision support systems (CDSSs) may be appropriate tools to promote the use of clinical practice guidelines (CPGs). However, compliance with CPGs is a multifactorial process that relies on the CPGs to be implemented, the physician(s) in charge of the decision, and the patient to manage. Formal concept analysis (FCA) allows to derive implicit relationships from a set of objects described by their attributes, based on the principle of attribute sharing between objects.We used FCA to elicit patient-based formal concepts related to the non-conformity of multidisciplinary staff meetings (MSMs) decisions with CPGs in the domain of breast cancer management. We developed a strategy for selecting attributes and make lattices manageable. We found that when not using the guideline-based CDSS OncoDoc2, patients with bad prognostic factors were associated with non-compliant decisions. This was corrected when the system was used during MSMs.