System and method for automatic generation of a hierarchical tree network and the use of two complementary learning algorithms, optimized for each leaf of the hierarchical tree network
First Claim
Patent Images
1. A method for predicting a person'"'"'s future health status, comprising:
- a. establishing a hierarchical tree network that, for a plurality of members, assigns each member to at most only one of a plurality of nodes as a function of a plurality of stratification variables;
b. providing to a computer based system, for said plurality of members and for each said member, member demographic data, available member medical claim data, and available member pharmacy claim data;
c. performing feature selection for each of said plurality of nodes to identify for each said node an optimal subset of features from a set comprising at least some of said member demographic data, said available member medical claim data, and said available member pharmacy claim data for all members assigned to that said node;
d. training a MVLR algorithm and a BRN algorithm using at least some of said member demographic data, said available member medical claim data, and said available member pharmacy claim data and storing learned parameters in a database to create a learned parameter database;
e. using the learned parameter database and, for at least one said member, using that at least one said member'"'"'s member demographic data, said available member medical claim data, and said available member pharmacy claim data, calculating a MVLR future health status score using said MVLR algorithm and calculating a BRN future health status score using said BRN algorithm, and calculating an arithmetic mean of said MVLR future health status score and said BRN future health status score to determine a final score.
1 Assignment
0 Petitions
Accused Products
Abstract
A system and method that generates a hierarchical tree network and uses linear-plus-nonlinear learning algorithms to form a consensus view on a member'"'"'s future health status. Each leaf in the hierarchical tree network is homogeneous in clinical characteristics, experience period, and available data assets. Optimization is performed on each leaf so that features and learning algorithms can be tailored to local characteristics specific to each leaf.
-
Citations
13 Claims
-
1. A method for predicting a person'"'"'s future health status, comprising:
-
a. establishing a hierarchical tree network that, for a plurality of members, assigns each member to at most only one of a plurality of nodes as a function of a plurality of stratification variables;
b. providing to a computer based system, for said plurality of members and for each said member, member demographic data, available member medical claim data, and available member pharmacy claim data;
c. performing feature selection for each of said plurality of nodes to identify for each said node an optimal subset of features from a set comprising at least some of said member demographic data, said available member medical claim data, and said available member pharmacy claim data for all members assigned to that said node;
d. training a MVLR algorithm and a BRN algorithm using at least some of said member demographic data, said available member medical claim data, and said available member pharmacy claim data and storing learned parameters in a database to create a learned parameter database;
e. using the learned parameter database and, for at least one said member, using that at least one said member'"'"'s member demographic data, said available member medical claim data, and said available member pharmacy claim data, calculating a MVLR future health status score using said MVLR algorithm and calculating a BRN future health status score using said BRN algorithm, and calculating an arithmetic mean of said MVLR future health status score and said BRN future health status score to determine a final score. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
-
Specification