Systems and Methods for Identifying and Driving Actionable Insights from Data

• US 20150317337A1
• Filed: 05/05/2015
• Published: 11/05/2015
• Est. Priority Date: 05/05/2014
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Edgar, Marc Thomas
• Application Number:
  US14/704,939
• Publication Number:
  US 20150317337A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Certain examples provide systems and methods to identify and drive actionable insight from data. An example system includes a configured processor that is configured to: identify, using the processor, a pattern in a data set using an analytic algorithm, the data set associated with a domain; process, using the processor, the identified pattern to assign a score to the identified pattern based on a comparison to statistical model meta data; construct, using the processor, a semantic model modeling people, processes, and systems associated with the domain; combine, using the processor, the identified pattern with the semantic model; determine, using the semantic model and the processor, an output including: a) a root cause for the identified pattern and b) a recommended action to remediate the root cause; and facilitate, using the processor, execution of the recommended action based on a trigger associated with the output.

Claims

1. A system comprising:

a memory storing instructions for execution; and

a configured processor, the processor configured by executing the instructions stored in the memory to;

identify, using the processor, a pattern in a data set using an analytic algorithm, the data set associated with a domain;

process, using the processor, the identified pattern to assign a score to the identified pattern based on a comparison to statistical model meta data;

construct, using the processor, a semantic model modeling people, processes, and systems associated with the domain;

combine, using the processor, the identified pattern with the semantic model;

determine, using the semantic model and the processor, an output including;

a) a root cause for the identified pattern and b) a recommended action to remediate the root cause; and

facilitate, using the processor, execution of the recommended action based on a trigger associated with the output.

2. The system of claim 1, wherein the statistical model meta data comprises at least one of a p value, an odds ratio, a relative risk, and a business metric.

3. The system of claim 1, wherein the identified pattern is associated with a denial of a claim.

4. The system of claim 1, wherein the trigger comprises at least one of an automated threshold comparison and rule matching.

5. The system of claim 1, wherein the processor is further configured to:

generate, using the processor, a visualization of the identified pattern using the identified pattern and the score.

6. The system of claim 1, wherein the processor is further configured to:

generate, using the processor, an alert associated with the identified pattern based on the identified pattern and the score.

7. The system of claim 6, wherein the alert, when analyzed singularly or combined with other alerts, is triggered when the identified pattern exceeds a significance threshold or matches a rule.

8. The system of claim 1, wherein the recommended action comprises creating a resolution system based on criteria associated with the identified pattern to automatically transform future pattern matches, wherein the transform includes a resolution to the root cause identified by the pattern and associated semantic model.

9. A non-transitory computer-readable storage medium including computer program instructions which, when executed by a processor, cause the processor to execute a method comprising:

identify, using the processor, a pattern in a data set using an analytic algorithm, the data set associated with a domain;

process, using the processor, the identified pattern to assign a score to the identified pattern based on a comparison to statistical model meta data;

construct, using the processor, a semantic model modeling people, processes, and systems associated with the domain;

combine, using the processor, the identified pattern with the semantic model;

determine, using the semantic model and the processor, an output including;

a) a root cause for the identified pattern and b) a recommended action to remediate the root cause; and

facilitate, using the processor, execution of the recommended action based on a trigger associated with the output.

10. The computer-readable storage medium of claim 9, wherein the statistical model meta data comprises at least one of a p value, an odds ratio, a relative risk, and a business metric.

11. The computer-readable storage medium of claim 9, wherein the identified pattern is associated with a denial of a claim.

12. The computer-readable storage medium of claim 9, wherein the trigger comprises at least one of an automated threshold comparison and rule matching.

13. The computer-readable storage medium of claim 9, wherein the computer program instructions further configure the processor to:

generate, using the processor, a visualization of the identified pattern using the identified pattern and the score.

14. The computer-readable storage medium of claim 9, wherein the computer program instructions further configure the processor to:

generate, using the processor, an alert associated with the identified pattern based on the identified pattern and the score.

15. The computer-readable storage medium of claim 14, wherein the alert, when analyzed singularly or combined with other alerts, is triggered when the identified pattern exceeds a significance threshold or matches a rule.

16. The computer-readable storage medium of claim 9, wherein the recommended action comprises creating a resolution system based on criteria associated with the identified pattern to automatically transform future pattern matches, wherein the transform includes a resolution to the root cause identified by the pattern and associated semantic model.

17. A computer-implemented method comprising:

identifying, using a processor, a pattern in a data set using an analytic algorithm, the data set associated with a domain;

processing, using the processor, the identified pattern to assign a score to the identified pattern based on a comparison to statistical model meta data;

constructing, using the processor, a semantic model modeling people, processes, and systems associated with the domain;

combining, using the processor, the identified pattern with the semantic model;

determining, using the semantic model and the processor, an output including;

a) a root cause for the identified pattern and b) a recommended action to remediate the root cause; and

facilitating, using the processor, execution of the recommended action based on a trigger associated with the output.

18. The method of claim 17, further comprising:

generate, using the processor, a visualization of the identified pattern using the identified pattern and the score.

19. The method of claim 17, further comprising:

generate, using the processor, an alert associated with the identified pattern based on the identified pattern and the score.

20. The method of claim 17, wherein the recommended action comprises creating a resolution system based on criteria associated with the identified pattern to automatically transform future pattern matches, wherein the transform includes a resolution to the root cause identified by the pattern and associated semantic model.