System and method of extracting and managing knowledge from medical documents

• US 20070055696A1
• Filed: 09/02/2005
• Published: 03/08/2007
• Est. Priority Date: 09/02/2005
• Status: Abandoned Application

• Current Assignee: Finetooth Enterprises, Inc.
• Original Assignee: Finetooth Enterprises, Inc.
• Inventors: Lagarde, James, Diedrick, Scott, Maycotte, Higinio, Fricke, Christian, Liu, Zhongjian, Alletto, Michael, Simon, Lindsey, Currie, Anne-Marie
• Application Number:
  US11/218,694
• Publication Number:
  US 20070055696A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

A method of managing medical documents is provided and includes receiving a plurality of medical documents and normalizing each of the plurality of medical documents. Further, the method includes selecting at least one automated text-based medical document analyst from a library system based on a specified context and/or a medical document type.

Claims

1. A method of processing medical documents using an automated system, the method comprising:

receiving a plurality of medical documents;

normalizing each of the plurality of medical documents; and

based on an identified medical document type, selecting at least one automated text-based document analyst from a library system that includes a plurality of text-based medical document analysts.

2. The method of claim 1, wherein the library system includes at least a first automated text-based medical document analyst associated with a first medical document type and at least a second automated text-based document analyst associated with a second medical document type.

3. The method of claim 1, further comprising extracting data and associated fields from each of the plurality of medical documents using the at least one automated text-based medical document analyst.

4. The method of claim 3, further comprising creating a medical data knowledge bundle from the data and associated fields.

5. The method of claim 4, further comprising outputting the medical data knowledge bundle.

6. The method of claim 5, further comprising storing the medical data knowledge bundle in a medical data repository.

7. The method of claim 6, further comprising providing access to the medical data repository using a user interface.

8. The method of claim 6, further comprising providing access to the medical data repository using a client application.

9. The method of claim 1, wherein the plurality of documents are normalized by converting each document into a standard format.

10. The method of claim 1, wherein the medical document type is a clinical report and wherein the plurality of documents includes at least one clinical report.

11. The method of claim 1, wherein the medical document type is a pathology report and wherein the plurality of documents includes at least one pathology report.

29. The method of claim 1, further comprising processing the automated text-based medical document analyst based on a plurality of dictionary files to create a pre-production automated text-based medical document analyst.

30. The method of claim 29, further comprising performing further processing of the pre-production automated text-based medical document analyst based on a plurality of patterns identified by performing at least one of the following:

a linguistic analysis, a statistical analysis, and a document structure analysis.

31. The method of claim 30, further comprising performing additional processing on the pre-production automated text-based medical document analyst based on desired data formats and desired data extractions.

32. The method of claim 31, further comprising performing a set of normalization rules with respect to the pre-production automated text-based medical document analyst with respect to desired data formats and data extraction.

33. The method of claim 32, further comprising testing the pre-production automated text-based medical document analyst using a set of test medical documents to determine a tested accuracy measure.

39. The method of claim 33, wherein the tested accuracy measure is based on a substantially randomized testing procedure.

12. A system for analyzing a plurality of documents, the system comprising:

a normalization module;

a categorization module coupled to the normalization module;

a text-based medical document analyzer coupled to the categorization module; and

a library system coupled to the text-based medical document analyzer, wherein the library system includes at least a first automated text-based medical document analyst associated with a first medical document type and at least a second automated text-based medical document analyst associated with a second medical document type.

13. The system of claim 12, wherein the text-based medical document analyzer selects at least one automated text-based medical document analyst from the library system based on at least one of the following:

an identified medical document type or one or more desired contexts.

14. The system of claim 12, wherein the first automated text-based medical document analyst and the second automated text-based medical document analyst are generated based on an output file that results from an automated computer executable build operation performed on a plurality of source medical documents with respect to at least one target field associated with data to be extracted from the plurality of source documents.

15. The system of claim 12, wherein the normalization module receives a plurality of source medical documents and converts each of the plurality of source medical documents to a standard format.

16. The system of claim 15, wherein the categorization module receives a plurality of standardized documents from the normalization module and wherein the categorization module can be used to determine a medical document type associated with each of the plurality of standardized medical documents.

17. The system of claim 12, wherein the text-based medical document analyzer uses at least one automated text-based medical document analyst to extract a plurality of data and associated fields from a plurality of source medical documents received by the system.

18. The system of claim 17, wherein the text-based medical document analyzer provides a medical knowledge bundle that is constructed from the plurality of data and associated fields.

19. A system for analyzing a plurality of medical documents, the system comprising:

a library system that includes at least a first automated text-based medical document analyst associated with a first document type and at least a second automated text-based medical document analyst associated with a second document type, wherein the first automated text-based medical document analyst and the second automated text-based medical document analyst have a data extraction precision rate that is greater than 85 percent.

20. The system of claim 19, wherein the first automated text-based medical document analyst and the second automated text-based medical document analyst have a precision rate that is greater than 90 percent.

21. The system of claim 19, wherein the first automated text-based medical document analyst and the second automated text-based medical analyst have a precision rate that is greater than 95 percent.

22. The system of claim 19, wherein at least one automated text-based medical document analyst is selected from the library system based on a medical document type.

23. A method of generating an automated medical document analyst, the method comprising:

receiving a plurality of source medical documents;

performing an automated computer executable build operation on the plurality of source medical documents with respect to at least one target field associated with data to be extracted from the plurality of source medical documents; and

performing a linguistic analysis on an output file produced as a result of performing the automated computer executable build operation.

24. The method of claim 23, wherein the linguistic analysis includes at least one of the following:

a lexical analysis, a semantic analysis, a pragmatic analysis, a syntactic analysis, and a discourse analysis.

25. The method of claim 23, further comprising performing a statistical analysis with respect to the output file.

26. The method of claim 25, wherein the statistical analysis includes at least one of the following:

a lexical frequency analysis and a clustering analysis.

27. The method of claim 23, further comprising performing a document structure analysis on the output file.

28. The method of claim 27, wherein the document structure analysis includes at least one of the following:

a section analysis, a table structure analysis, a document format analysis, and a document level discourse analysis.

34. The method of 33, further comprising modifying the pre-production automated text-based medical document analyst after determining that the tested accuracy measure is below a threshold.

35. The method of claim 34, further comprising classifying the pre-production automated text-based medical document analyst as a production automated text-based medical document analyst after determining that the tested accuracy measure is above a threshold.

36. The method of claim 35, further comprising documenting the tested accuracy measure associated with the production automated text-based medical document analyst.

37. The method of claim 36, further comprising storing the production automated text-based medical document analyst in a library of automated text-based medical document analysts and storing the tested accuracy measure associated with the production automated text-based medical document analyst.

38. The method of claim 37, wherein the library of automated text-based medical document analysts includes at least a first automated text-based medical document analyst and at least a second automated text-based medical document analyst, wherein the first automated text-based medical document analyst is associated with at least one of the following:

a first medical document type and a first specified context, and wherein the second automated text-based medical document analyst is associated with at least one of the following;

a second medical document type and a second specified context.

40. A method of processing pathology reports using an automated system, the method comprising:

receiving a plurality of pathology reports;

normalizing each of the plurality of pathology reports; and

based on an identified medical document type, selecting at least one automated text-based document analyst from a library system that includes a plurality of text-based medical document analysts.

41. The method of claim 40, wherein the plurality of pathology reports are associated repository of cancer information.