Challenge

Patients are assigned to risk bands. Sometimes patients migrate to a different risk band over the course of time. Several variables influence this, but prediction is complex. The challenge was to find out the reasons for the migration from low to high risk (or vice versa).

Approach

A classification model was built using a basis of the medication habits and physical lifestyle and predicts which patients are likely to deteriorate and which patients are likely to improve their risk level.

Industry

  • Healthcare

Tools Used

  • Spark Notebook on z/OS

Data Science Techniques

  • Classification

Benefits:

By finding out the reasons for risk migration, Argus Health is now able to act proactively and prevent a deterioration of the patient condition, as well as make recommendations on how to improve someone’s well-being.

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