  Pharmaco-epidemiology (PE) is the study of uses and effects of drugs in well
defined populations. As medico-administrative databases cover a large part of
the population, they have become very interesting to carry PE studies. Such
databases provide longitudinal care pathways in real condition containing
timestamped care events, especially drug deliveries. Temporal pattern mining
becomes a strategic choice to gain valuable insights about drug uses. In this
paper we propose DCM, a new discriminant temporal pattern mining algorithm. It
extracts chronicle patterns that occur more in a studied population than in a
control population. We present results on the identification of possible
associations between hospitalizations for seizure and anti-epileptic drug
switches in care pathway of epileptic patients.
