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An Approach for Mining Care Trajectories for Chronic Diseases

  • Elias Egho
  • Nicolas Jay
  • Chedy Raïssi
  • Gilles Nuemi
  • Catherine Quantin
  • Amedeo Napoli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

With the increasing burden of chronic illnesses, administrative health care databases hold valuable information that could be used to monitor and assess the processes shaping the trajectory of care of chronic patients. In this context, temporal data mining methods are promising tools, though lacking flexibility in addressing the complex nature of medical events. Here, we present a new algorithm able to extract patient trajectory patterns with different levels of granularity by relying on external taxonomies. We show the interest of our approach with the analysis of trajectories of care for colorectal cancer using data from the French casemix information system.

Keywords

datamining chronic illness claim data sequential pattern mining trajectory of care 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Elias Egho
    • 1
  • Nicolas Jay
    • 1
  • Chedy Raïssi
    • 2
  • Gilles Nuemi
    • 3
  • Catherine Quantin
    • 3
  • Amedeo Napoli
    • 1
  1. 1.Orpailleur TeamLORIAVandoeuvre-les-NancyFrance
  2. 2.Nancy Grand EstINRIAFrance
  3. 3.Service de Biostatistique et d’Information MédicaleCHU de DijonDijonFrance

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