Method, system, and apparatus for validation

• US 20040243614A1
• Filed: 05/30/2003
• Published: 12/02/2004
• Est. Priority Date: 05/30/2003
• Status: Active Grant

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: Dictaphone Corporation (Microsoft Corporation)
• Inventors: Gervais, Sean, Titemore, Robert G., Boone, Keith W., Chaparala, Sunitha, Hopkins, Jeffrey G., Manoukian, Roubik, Ogrinc, Harry J., Fordyce, Cameron
• Granted Patent: US 8,095,544 B2
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06F 40/226 Validation
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/56 Natural language generation
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

In a method for validating data, a text of a document is received. At least one fact is extracted from the text. At least one expert refinement is merged with the at least one fact to create at least one modified fact. The at least one modified fact is provided for a review. An expert refinement to the at least one modified fact is captured in response to the review. A superset document based on the at least one pre-existing refinement and the expert refinement is stored.

Claims

1. A method for reviewing data, the method comprising the steps of:

receiving a text of a document;

receiving at least one fact associated with the document;

capturing an expert refinement to the at least one fact in response to the review; and

storing a superset document based on the at least one pre-existing fact and the expert refinement.

2. The method according to claim 1, wherein the at least one fact from the text is subsequently merged with a previously stored expert refinement to produce at least one modified fact and the capturing of expert refinements is applied to the modified fact.

3. The method according to claim 2, wherein the step of receiving the text of the document further comprises the step of receiving the document by one of electronic mail, file transport protocol, and a network file transfer protocol.

4. The method according to claim 1, wherein the step of providing the review document for the review, further comprises the steps of:

providing a graphical user interface adapted to display the at least one modified fact; and

highlighting a selected fact displayed on the graphical user interface.

5. The method according to claim 4, further comprising the steps of:

displaying at least one category of facts, the selected fact being a member of the at least one category of facts;

displaying related details category for the selected fact; and

displaying the selected text and surrounding text (i.e., the context) of the selected fact in the graphical user interface.

6. The method according to claim 5, further comprising the step of displaying a relevancy indicator for each fact in the at least one category of facts.

7. The method according to claim 5, further comprising the step of displaying a truthfulness indicator for each fact in the at least one category of facts.

8. The method according to claim 1, further comprising the steps of:

providing the at least one modified fact and the text to a domain expert; and

determining the expert refinement based on a review of the at least one modified fact and the at least one expert refinement by the domain expert.

9. The method according to claim 8, further comprising the step of storing the expert refinement as an expert refinement file.

10. The method according to claim 1, further comprising the steps of:

collecting a set of related documents based on an index;

gathering the at least one fact based on the set of related documents; and

providing the at least one fact to a domain expert.

11. The method according to claim 10, wherein the related documents may be of similar date, topic or clustered by similar content.

12. The method according to claim 11, wherein the related documents are classified by one of K-nearest neighbor algorithm or cosine similarity metric.

13. The method according to claim 2, further comprising the step of determining a set of normalized facts based on the at least one fact.

14. The method according to claim 13, where the at least one fact is a classifying facts.

15. The method according to claim 14, where the at least one fact is a SNOMED code.

16. The method according to claim 14, where the at least one fact is a ICD-9-CM code

17. The method according to claim 14, where the at least one fact is a CPT code.

18. The method according to claim 13, further comprising the step of:

providing the set of normalized facts with the at least one modified fact for the review.

19. The method according to claim 2, further comprising the step of:

determining a temporal significance for the at least one modified fact, for example by recording the date the fact was observed based on metadata included with the medical record.

20. The method according to claim 2, further comprising the step of determining a relevancy factor for the at least one modified fact.

21. The method according to claim 20, further comprising the step of providing the relevancy factor with the at least one modified fact for the review.

22. A system for reviewing data, the system comprising:

an extraction module configured to extract a set of facts from a captured electronic document;

a storage device configured to interface with the extraction module and the validation module; and

a validation module configured to provide a graphical user interface to validate the facts, wherein the validation module is configured to receive a set of facts from the extraction module, apply a set of expert facts retrieved from storage device to the set of facts to create a set of modified facts, and provide the set of modified facts to an author for review.

23. The system according to claim 22, wherein the validation module is further configured to determine a set of normalized facts for the set of facts.

24. The system according to claim 23, wherein the validation module is further configured to determine a temporal significance for the set of facts.

25. The system according to claim 24, wherein the validation module is further configured to determine a relevancy factor for the set of facts.

26. The system according to claim 25, wherein the validation module is further configured to provide at least one of a set of normalized facts, a temporal significance, and a relevancy factor with the set of facts to a domain expert.

27. The system according to claim 26, wherein the validation module is further configured to capture modifications to the set of facts as the set of expert facts based on a review of the at least one of the set of normalized facts, the temporal significance, and relevancy factor with the set of facts by the domain expert.

28. The system according to claim 27, wherein the validation module is further configured to store the set of expert facts.