About ParcoursVis

The French Social Security (CNAMTS) wants to analyze the patient pathways for specific treatments to understand how treatments are actually done in contrast to the recommendations. Aviz and CMAP/École Polytechnique are collaborating to design and implement a visualization system, ParcoursVis, to explore its prescription data.

ParcoursVis allow extracting a subset of the nationwide database from CNAMTS, transforming the raw data into meaningful medical events, and visualize it interactively at scale. It is part of a larger collaboration between École Polytechnique and CNAMTS.

The Data

For the moment, we focused on ParcoursVis on the adenoma of the prostate. With this focus, we extracted with our domain expert users the following high-level type of events (e.g., treatments) the patient follows in their care pathways. We do not yet consider which drugs the patients took, but we considered which molecules they were exposed to:

  • Alphabloc
  • Phyto
  • Surgery
  • Fivealpha
  • Interruption -- Patients interrupted their treatment but still benefit from them. We consider an interruption event when patient did not have any other event (related to our use-case) in the following 180 days.
  • No treatment -- We consider that patients are under no treatment when they did not have any other event (related to our use-case) in the following 360 days (~1 year).
  • Death

We also consider "composed types" of events when patients would benefit from multiple molecules at the same time, resulting in new treatments that the medical field recognized:

  • Alphabloc + Phyto
  • Fivealpha + Alphabloc
  • Fivealpha + Alphabloc + Phyto

The demo of ParcoursVis relies on synthetical data that we generated from a real cohort. This synthethical data tries to follow the same statistical distribution the real dataset has. However, all the "patients" our synthetical data has do not exist, which ensure anonymization from our real pool of patients. This synthethical dataset contains:

  • 2,000,000 patients
  • 50,640,284 low-level events (what the patients was reimbursed from)
  • 2,719,086 high-level events (what treatment did the patients follow. A high-level event, e.g., alphabloc, may come from patients buying multiple alphabloc pills (low-level events))