Clinically intelligent parsing

• US 20090210450A1
• Filed: 02/20/2008
• Published: 08/20/2009
• Est. Priority Date: 02/20/2008
• Status: Active Grant

• Current Assignee: Medicomp Systems Incorporated
• Original Assignee: Medicomp Systems Incorporated
• Inventors: Goltra, Peter S.
• Granted Patent: US 9,864,838 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 50/00 Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism healthcare informatics G16H
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 70/20 relating to practices or guidelines
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A method, a device and a system for correlating medical information of a first format to medical information of a second format are provided. The method includes parsing an input sequence representing textual information into plural terms; searching a medical database to associate each term with a medical diagnosis; and translating each term into a coded phrase previously associated with the medical diagnosis in the medical database.

Claims

1. A method of correlating medical information of a first format to medical information of a second format, the method comprising:

parsing an input sequence representing textual information into plural terms;

searching a medical database to associate each term with a medical diagnosis; and

translating each term into a coded phrase previously associated with the medical diagnosis in the medical database.

2. The method of claim 1, wherein the parsing of the input sequence comprises:

sequentially processing the input sequence by;

identifying whether a word of input sequence is included in a medical vocabulary file;

determining whether the word is part of a phrase of the input sequence using the medical database; and

if it is determined that the word is part of the phrase, including the word into the phrase to form a new term.

3. The method of claim 1, wherein the searching the medical database comprises:

identifying term groups, each term group including terms associated with at least one common diagnosis;

associating each term in the term group with the at least one common diagnosis.

4. The method of claim 3, wherein the term groups are identified by:

determining whether an intersection set between one or more diagnoses corresponding to the first of plural terms and one or more diagnoses corresponding to the second of the plural terms, which is a first intersection set, is an empty set;

if the first intersection set is a non-empty set, identifying the first term and the second term as part of one group; and

if the first intersection set is an empty set, identifying the first term and the second term as being in separate groups.

5. The method of claim 4, wherein the term groups are identified by:

sequentially processing each remaining term in the parsed input sequence by;

determining whether an intersection set between one or more diagnoses corresponding to the term and one or more diagnoses corresponding to a term group that immediately precedes the term, which is a second intersection set, is an empty set;

if the second intersection set is a non-empty set, including the term into the immediately preceding term group.

6. The method of claim 5, wherein:

if the second intersection set is an empty set, determining whether an intersection set between the one or more diagnoses corresponding to the term and one or more diagnoses corresponding to an existing term group, which is a third intersection set, is an empty set; and

if the third intersection set is a non-empty set, including the term into the existing term group; and

if the third intersection set is an empty set, identifying the term as part of a new term group.

7. The method of claim 3, wherein the parsing of the input sequence and the identifying of the term groups are performed concurrently.

8. The method of claim 3, wherein the parsing of the input sequence and the identifying of the term groups are performed concurrently with a nested loop, an outer loop of the nested loop executing the parsing of the input sequence, and an inner loop executing the identifying of the term groups.

9. The method of claim 1, comprising:

deleting any word that is included in an ignore word file from the input sequence before the parsing the input sequence.

10. The method of claim 9, wherein the ignore word file includes prepositions.

11. The method of claim 1, comprising:

determining alternative terms associated with a term by searching an additional word file.

12. The method of claim 11, wherein determining the alternative terms comprises:

selecting one or more of the alternative terms that have the strongest correlation with terms that immediately precede and succeed the term.

13. The method of claim 12, wherein a degree of correlation between two terms is determined by the size of intersection set between diagnoses which refer to the two terms in the medical database.

14. The method of claim 1, wherein the input sequence comprises:

a voice input that has been transcribed.

15. The method of claim 1, wherein the input sequence comprises:

a recording of a dictation.

16. The method of claim 1, wherein the input sequence comprises:

a live dictation.

17. The method of claim 3, wherein the input sequence representing textual information comprises:

one or more instructions.

18. The method of claim 17, wherein the one or more instructions comprise:

a first instruction indicating that content following the first instruction relates to a diagnosis.

19. The method of claim 18, comprising:

detecting the first instruction; and

translating the one or more terms in a term group immediately successive to the first instruction into coded phrases associated with the diagnosis indicated in the first instruction in the medical database.

20. The method of claim 17, wherein the one or more instructions comprise:

a second instruction indicating that content following the second instruction describes a medical problem previously described in the input sequence.

21. The method of claim 20, comprising:

detecting the second instruction;

identifying an existing term group relating to the medical problem indicated in the second instruction; and

identifying terms in a term group immediately successive to the second instruction and the identified existing term group as one group.

22. The method of claim 1, comprising:

outputting the translated phrases; and

selecting from a plurality of clinical protocol forms based on the output.

23. The method of claim 1, wherein the method comprises:

outputting the translated phrases; and

using the output as an input of a system which receives coded phrases as input.

24. A computer readable medium having stored therein a program, which when executed causes a processor to perform the method of claim 1.

25. A device of correlating medical information of a first format to medical information of a second format, the device comprising:

a parsing means for parsing an input sequence representing textual information into plural terms;

a searching means for searching a medical database to associate each term with a medical diagnosis; and

a translating means for translating each term into a coded phrase previously associated with the medical diagnosis in the medical database.

26. The device of claim 25, wherein the parsing means, the searching means and the translating means are implemented in separate software modules.

27. The device of claim 25, wherein the parsing means, the searching means and the translating means are implemented in a shared software module.

28. The device of claim 26, wherein the software modules are executable in a shared processor.

29. The device of claim 26, wherein each of the software modules is executable in a dedicated processor, each dedicated processor being dedicated to one of the software modules.

30. A system correlating medical information of a first format to medical information of a second format, the system comprising:

a medical vocabulary file; and

a medical database which includes coded phrases and coded diagnosis, and specifies relationships between the coded phrases and the coded diagnoses;

wherein the medical vocabulary file and the medical database are accessed to parse the input sequence into plural terms, and the medical database is accessed to associate each term with a medical diagnosis, and to translate each term into a coded phrase previously associated with the medical diagnosis in the medical database.

31. The system of claim 30, comprising:

an additional word file for determining alternative terms associated with a term.

32. A system correlating medical information of a first format to medical information of a second format, the system comprising:

a processor, the processor being able to execute a software module;

one or more data storage devices coupled to the processor, the data storage devices storing a medical vocabulary file, and a medical database;

one or more input devices connected to the processor for sending input to the processor; and

a display device connected to the processor for displaying an output of the processor;

wherein the software module is executed to access the medical vocabulary file and the medical database to parse an input sequence representing textual information into plural terms, and to access the medical database to associate each term with a medical diagnosis, and to translate each term into a coded phrase previously associated with the medical diagnosis in the medical database.

33. The system of claim 32, wherein the one or more input devices comprise a microphone.

34. The system of claim 33, wherein a cursor of the display device is controlled by an input to the microphone.

35. The system of claim 33, wherein the system further comprises a voice recognition software module which is executable to transcribe input to the microphone into textual information.