Data translation

• US 10,482,540 B2
• Filed: 02/02/2018
• Issued: 11/19/2019
• Est. Priority Date: 02/02/2018
• Status: Active Grant

• Current Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Original Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Inventors: Li, Chung-Sheng, Xiong, Guanglei, Kang, Sukryool, Jain, Ashish, Connors, Colin, Grosof, Benjamin Nathan, Narang, Neeru
• Primary Examiner(s): Nguyen, Tien C
• Application Number:
  US15/887,813
• Publication Number:
  US 20190244300A1
• Time in Patent Office: 655 Days
• Field of Search: 705 2, 705 3, 705 4, 705 5, 705 39, 705 38, 706 13, 706 45, 709201, 707802
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records

Abstract

A classifier receives policy data corresponding to a new policy. Further, the classifier processes the policy data to classify the policy data into an obligation class and an informational class. An information extractor then extracts metadata from the policy data that is classified into the obligation class. Subsequently, a data translator determines if there is an incremental change in the policy data based on a comparison of the policy data with policy data corresponding to existing policies. On determining the incremental change in the policy data, the data translator translates the policy data that is classified into the obligation class into a rule based on the metadata. A rules engine then receives the rule from the data translator for claims adjudication.

Claims

1. A system to translate of policies into rules for claims adjudication, the system comprising:

a classifier to;

receive policy data corresponding to a new policy, the policy data comprising natural language content to be selectively translated to a new rule, wherein the new rule comprising a procedure to determine whether a claim complies with pre-determined requirements pertaining to claim adjudication; and

process a portion of the policy data to classify the portion of the policy data into an obligation class and an informational class, wherein the obligation class comprises useful information to be used for generating the new rule and the informational class refers to the class that signifies additional information or non-useful data that would not be used for translation of the new policy into rules;

an information extractor, in combination with the classifier, the information extractor to extract metadata from the portion of the policy data that is classified into the obligation class;

a data translator, in combination with the information extractor, the data translator to;

determine whether there is an incremental change in the portion of policy data based on a comparison of the portion of the policy data with existing policy data corresponding to existing policies, wherein the existing policy data comprises knowledge graphs of the existing policies and a plurality of rules corresponding to the existing policies, wherein the existing policies are decomposed and curated into multiple knowledge representations to form the knowledge graphs, and the comparison is based on at least one of topic classification, entities and relationship, and knowledge representations extracted from the new policy vs. the existing policies; and

on determining the incremental change in the portion of the policy data, selecting the portion of the policy data that is classified into the obligation class and discarding the portion of the policy data that is classified into the information class; and

translate the selected portion of policy data that is classified into the obligation class into the new rule based on the metadata; and

a rules engine, in combination with the data translator, the rules engine to receive the new rule from the data translator for the claim adjudication based in part on the portion of the new policy.

2. The system of claim 1, wherein the obligation class further includes a conditional class and an action class.

3. The system of claim 1, wherein the metadata includes entity data, parameter data, and relationship data.

4. The system of claim 3, wherein the entity data includes provider, billed dates, claim form, out-patient claim, and lifetime maximum.

5. The system of claim 1, wherein the policy data corresponding to the existing policies is pre-stored in a policy database.

6. A system to translate of policies into rules for claims adjudication, the system comprising:

a classifier to;

receive policy data corresponding to a new policy, the policy data comprising natural language content to be selectively translated to a new rule, wherein the new rule comprising a procedure to determine whether a claim complies with pre-determined requirements pertaining to claim adjudication; and

process a portion of the policy data to classify the portion of the policy data into an obligation class and an informational class, wherein the obligation class comprises useful information to be used for generating the new rule and the informational class refers to the class that signifies additional information or non-useful data that would not be used for translation of the new policy into rules;

an information extractor, in combination with the classifier, the information extractor to extract metadata from the portion of the policy data that is classified into the obligation class;

a data translator, in combination with the information extractor, the data translator to;

determine whether there is an incremental change in the portion of policy data based on a comparison of the portion of the policy data with existing policy data corresponding to existing policies, wherein the existing policy data comprises knowledge graphs of the existing policies and a plurality of rules corresponding to the existing policies, wherein the existing policies are decomposed and curated into multiple knowledge representations to form the knowledge graphs, and the comparison is based on at least one of topic classification, entities and relationship, and knowledge representations extracted from the new policy vs. the existing policies; and

on determining the incremental change in the portion of the policy data, selecting the portion of the policy data that is classified into the obligation class and discarding the portion of the policy data that is classified into the information class; and

translate the selected portion of policy data that is classified into the obligation class into the new rule based on the metadata.

7. The system of claim 6, wherein the portion of the policy data is indicative of a phrase of the policy data.

8. The system of claim 6, wherein the obligation class further includes a conditional class and an action class.

9. The system of claim 6, wherein the metadata includes entity data, parameter data, and relationship data.

10. The system of claim 6 further comprising a rules engine, in combination with the data translator, to receive the rule from the data translator for the claim adjudication.

11. A computer-implemented method to translate of policies into rules for claims adjudication, executed by at least one processor, the method comprising:

receiving policy data corresponding to a new policy, the policy data comprising natural language content to be selectively translated to a new rule, wherein the new rule comprising a procedure to determine whether a claim complies with pre-determined requirements pertaining to claim adjudication;

processing a portion of the policy data to classify the portion of the policy data into an obligation class and an informational class, wherein the obligation class comprises useful information to be used for generating the new rule and the informational class refers to the class that signifies additional information or non-useful data that would not be used for translation of the new policy into rules;

extracting metadata from the portion of the policy data that is classified into the obligation class;

determining whether there is an incremental change in the portion of policy data based on a comparison of the portion of the policy data with existing policy data corresponding to existing policies, wherein the existing policy data comprises knowledge graphs of the existing policies and a plurality of rules corresponding to the existing policies, wherein the existing policies are decomposed and curated into multiple knowledge representations to form the knowledge graphs, and the comparison is based on at least one of topic classification, entities and relationship, and knowledge representations extracted from the new policy vs. the existing policies; and

on determining the incremental change in the portion of the policy data, selecting the portion of the policy data that is classified into the obligation class and discarding the portion of the policy data that is classified into the information class; and

translate the selected portion of policy data that is classified into the obligation class into the new rule based on the metadata.

12. The computer-implemented method of claim 11, wherein the portion of the policy data is indicative of a phrase of the policy data.

13. The computer-implemented method of claim 11, wherein the portion of the policy data is classified into the obligation class and the informational class using a machine learning technique.

14. The computer-implemented method of claim 11, wherein the obligation class further includes a conditional class and an action class.

15. The computer-implemented method of claim 11, wherein the metadata includes entity data, parameter data, and relationship data.

16. The computer-implemented method of claim 15, wherein the entity data includes provider, billed dates, claim form, out-patient claim, and lifetime maximum.