In a situation where only 4% of the population accounts for over 70% of the total cost in health care, such models allow insurers not only to better manage costs, but mostly to positively impact the health and the lives of their covered populations.

Using TIMi on the data from the company, Sura developed predictive models to identify the patients with the highest risk of deadly or costly complication, such as heart attacks, dialysis, chronic liver disease or extreme cardio vascular risk. This project was performed with the help of an allied consulting firm that provided part of the manpower.

In less than 3 months, they built 4 predictive models using 8 years of clinical history with over 23.000 variables and 4.5 million rows for the diabetic population, and integrated the results in analytics solution that helped articulate new patient care programs.

Sura obtained the following results:

  • Prediction of the last stage of diabetes :
    over 80% AUC (i.e. ultra high accuracy)
  • Prediction of heart-related complications for diabetics:
    ultra high accuracy
  • Early detection of pregrancy-related complications:
    20% babies less in intensive care.



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