HEALTH SEVERITY SCORE PREDICTIVE MODEL

• US 20160358290A1
• Filed: 04/16/2013
• Published: 12/08/2016
• Est. Priority Date: 04/20/2012
• Status: Abandoned Application

• Current Assignee: Humana Incorporated
• Original Assignee: Humana Incorporated
• Inventors: Chiu, Sandy, Gopal, Vipin
• Application Number:
  US13/863,498
• Publication Number:
  US 20160358290A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A computerized health severity score predictive model for assigning a health severity score to a member of a health insurance member population is disclosed. The computerized system and method comprises a predictive model for scoring members. The predictive model is developed based on health insurance claim data. Member claim data may comprise eligibility, demographics, medical claims, pharmacy claims, pharmacy benefit management, laboratory test results, and disease management data. A utilization transition pattern is identified from a comparison of costs observed during a first year and a subsequent year. Members are segmented into groups according to predetermined segmenting rules derived from a segmentation model that applies the utilization transition pattern. The health severity score is thus based on demographic and clinical data as well as utilization transition pattern (or cost transition) data.

Claims

1. A computerized method for assigning health severity scores to members of a health insurance population comprising:

(a) extracting at a server from at least one health claims database utilization data for a plurality of members of said health insurance population, said utilization data comprising for each member cost data for said member;

(b) identifying at said server for each of said plurality of members a utilization transition pattern based on a comparison of a first year of cost data and a second year of cost data;

(c) segmenting members at said server in to a plurality of groups based on data driven rules derived from a supervised segmentation model;

(d) integrating at said server a predictive model trained on member data and observed utilization transition patterns with a model software application that;

(1) applies said predictive model to member data for said plurality of members; and

(2) assigns to each of said plurality of members a health severity score based on application of said predictive model; and

(3) outputs for each member said health severity score.

2. The computerized method of claim 1 wherein said utilization data is selected from the group consisting of:

demographic and geographical data, membership and plan benefit data, medical, pharmacy, lab, dental and vision claims data, pharmacy benefit management data, clinical data, lab test results data, care management, disease management and health program data, socio-economic data, health risk assessment and survey data, call center, messaging and weblogs data, electronic medical records data, biometric data, and healthcare provider data.

3. The computerized method of claim 1 wherein said demographic and geographical data comprises data selected from the group consisting of:

age, gender, location, market and plan data.

4. The computerized method of claim 1 wherein said clinical data comprises data selected from the group consisting of:

comorbidity, number of medications, heart disease, severity of illness, and treatments.

5. The computerized method of claim 1 wherein said cost data comprises data selected from the group consisting of:

chronic condition cost, total cost, recent cost, physician cost ratio, and prescription cost ratio.

6. The computerized method of claim 1 wherein said utilization transition pattern is a pattern selected from the group consisting of:

low to low costs, low to high costs, high to low costs, and high to high costs.

7. The computerized method of claim 1 wherein said utilization transition pattern indicates significance and direction between said first year of cost data and said second year of cost data.

8. The computerized method of claim 1 wherein said supervised segmentation model is developed on member data, clinical knowledge, utilization transition patterns, and cost transition indices.

9. A computerized system for assigning health severity scores to members of a health insurance population comprising:

(a) at least one health claims database comprising utilization data for a plurality of members; and

(b) a server executing instructions to;

(1) extract at said server from said at least one health claims database utilization data for a plurality of members of said health insurance population, said utilization data comprising for each member cost data for said member;

(2) identify at said server for each of said plurality of members a utilization transition pattern based on a comparison of a first year of cost data and a second year of cost data;

(3) segment members at said server in to a plurality of groups based on data driven rules derived from a supervised segmentation model; and

(c) a model software application executing at said server with an integrated predictive model trained on member data and observed utilization transition patterns for a plurality of years that;

(1) applies at said server said predictive model to said member data for said plurality of members; and

(2) assigns to each of said plurality of members a health severity score based on application of said predictive model; and

(3) outputs for each member said health severity score.

10. The computerized system of claim 9 wherein said utilization data is selected from the group consisting of:

demographic and geographical data, membership and plan benefit data, medical, pharmacy, lab, dental and vision claims data, pharmacy benefit management data, clinical data, lab test results data, care management, disease management and health program data, socio-economic data, health risk assessment and survey data, call center, messaging and weblogs data, electronic medical records data, biometric data, and healthcare provider data.

11. The computerized system of claim 9 wherein said demographic and geographical data comprises data selected from the group consisting of:

age, gender, location, market and plan data.

12. The computerized system of claim 9 wherein said clinical data comprises data selected from the group consisting of:

comorbidity, number of medications, heart disease, severity of illness, and treatments.

13. The computerized system of claim 9 wherein said cost data comprises data selected from the group consisting of:

chronic condition cost, total cost, recent cost, physician cost ratio, and prescription cost ratio.

14. The computerized system of claim 9 wherein said utilization transition pattern is a transition selected from the group consisting of:

low to low costs, low to high costs, high to low costs, and high to high costs.

15. The computerized system of claim 9 wherein said utilization transition pattern indicates significance and direction between said first year of cost data and said second year of cost data.

16. The computerized system of claim 9 wherein said supervised segmentation model is developed on member data, clinical knowledge, utilization transition patterns, and cost transition indices.

17. A computerized method for assigning health severity scores to members of a health insurance population comprising:

(a) extracting at a server from at least one health claims database utilization data for a plurality of members of said health insurance population, said utilization data comprising cost data for each member;

(b) comparing at said server for each of said plurality of members a first year of cost data and a second year of cost data to identify a utilization transition pattern;

(c) segmenting said plurality of members at said server in to a plurality of groups based on data driven rules derived from a supervised segmentation model;

(d) integrating at said server a predictive model trained on member data and identified utilization transition patterns with a model software application that;

(1) applies said predictive model to member data for said plurality of members;

(2) assigns to each of said plurality of members a health severity score based on application of said predictive model; and

(3) outputs for each member said health severity score.

18. The computerized method of claim 17 wherein said cost data comprises data selected from the group consisting of:

chronic condition cost, total cost, recent cost, physician cost ratio, and prescription cost ratio.

19. The computerized method of claim 17 wherein said utilization transition pattern is a transition selected from the group consisting of:

low to low costs, low to high costs, high to low costs, and high to high costs.

20. The computerized method of claim 17 wherein said utilization transition pattern indicates significance and direction between said first year of cost data and said second year of cost data.