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Identifying group and individual-level risk factors via risk-driven patient stratification

  • US 9,996,889 B2
  • Filed: 10/01/2012
  • Issued: 06/12/2018
  • Est. Priority Date: 10/01/2012
  • Status: Active Grant
First Claim
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1. A method for individual risk factor identification, comprising:

  • identifying common risk factors for one or more risk targets from population data;

    stratifying individuals into clusters based upon the common risk factors, wherein a distance between each cluster represents a similarity based upon the common risk factors, and wherein a closest pair of clusters is iteratively merged into a single cluster until a threshold condition is reached;

    determining, using a processor, a discriminability of each of the common risk factors for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a quantitative measure of how a risk factor discriminates its cluster from other clusters; and

    customizing and performing, using a personalized user interface and dashboard display operatively coupled to at least one hardware based care-management machine, a personalized hardware-based care management process by controlling the at least one hardware based care-management machine for personalized treatment of a particular individual, the personalized user interface and dashboard display comprising a customized graphical user interface (GUI) configured for customizing healthcare plans, tailored to the particular individual based on the individual risk factors determined by the identifying common risk factors, the stratifying individuals into clusters and the re-ranked common risk factors, and for providing real-time clinical decision support at a point-of-care for the particular individual.

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