Medical information translation system

• US 10,490,306 B2
• Filed: 02/20/2015
• Issued: 11/26/2019
• Est. Priority Date: 02/20/2015
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: Haley, John D.
• Primary Examiner(s): Go, John P
• Application Number:
  US14/627,756
• Publication Number:
  US 20160246946A1
• Time in Patent Office: 1,740 Days
• Field of Search: 705 2- 4
• CPC Class Codes: G06F 16/2291 User-Defined Types; Storage management thereof
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/58 Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

Medical information is communicated between different entities. Personalized models of peoples'"'"' understanding of a medical field are created. Role information is used to create the personalized model. More information than mere role may be used for at least one of the personalized models, such as information on past medical history. The personalized models link to various subsets of base medical ontologies for one or more medical subjects. The concepts and relationships in these ontologies formed by the linking may be matched, providing a translation from one personalized model to another. The terminology with similar or the same concepts and/or relationships is output for a given user based on their model.

Claims

1. A system for network-based communication of medical information between different entities, the system comprising:

a healthcare database configured to store roles for a first user and a second user, login credentials used by each of the first user and the second user to access the healthcare database, and different base models of ontologies for their respective roles;

a first computer in communication with the healthcare database through an internet computer network, the first computer configured to receive an input first expression from a first user having a first one of the roles, the first expression communicating a healthcare concept; and

a second computer in communication with the healthcare database through the internet computer network, the second computer configured to output a second expression to a second user having a second one of the roles, the second role different than the first role, the second expression communicating the healthcare concept, and wherein the first expression necessitates translation into the second expression to enable the second user to understand the second expression;

wherein the first computer or the second computer perform actions comprising;

selecting the second user as a target of the second expression from a healthcare group, the selecting based on an identity of the first user and a context of a communication sent by the first user to the healthcare group;

subsequent to the selecting, determining roles of each of the first user and the second user based on the login credentials used by each of the first and the second users to access the healthcare database;

assigning, based on the determined role of each of the first and second users and the context of the communication, at least a first base model ontology to the first user and at least a second base model ontology to the second user, the first base model ontology being different than the second base model ontology;

creating, by mining the healthcare database for data about the first user and the second user, each of a first personalized ontology model by linking to first subsets of a first base model ontology and a second personalized ontology model by linking to second subsets of a second base model ontology, wherein the first personalized ontology model is automatically created by data available to the processor about the first user and the second personalized ontology model is automatically created by data available to the processor about the second user;

upon receiving an indication that the second computer in internet communication with the healthcare database has requested the healthcare concept for the second user, translating the first expression to the second expression by using the first personalized ontology to decompose the first expression into the healthcare concept and the second personalized ontology to re-express the healthcare concept into the second expression, the first expression being different than the second expression; and

transmitting the second expression to the second user.

2. The system of claim 1 wherein the healthcare database comprises a computerized patient record.

3. The system of claim 1 wherein the first computer comprises a workstation of the medical facility and the second computer comprises a personal computer.

4. The system of claim 1 wherein the first role is a physician, nurse, or physical therapist and wherein the second role is a patient.

5. The system of claim 1 wherein the different base models comprise a layman ontology, a physician ontology, and a therapist ontology, the input expression having a different granularity for the concept than the output expression, the different granularity reflected in differences in the different base models.

6. The system of claim 1 wherein the different base models of the ontologies are for a same subject matter identified by a communications model.

7. The system of claim 1 wherein the different base models of the ontologies are for the different roles for each of a plurality of different healthcare subjects.

8. The system of claim 1 wherein the first computer, the second computer, or another computer is configured to translate by recursive introspection of concepts and relationships in the ontologies.

9. The system of claim 1 wherein the first computer, the second computer, or another computer is configured to translate by semantic query.

10. The system of claim 1 wherein the first computer, the second computer, or another computer is configured to convert the output expression of the second information into a language of the second user.

11. The system of claim 1 wherein the first user is a healthcare worker using medical terms in the input expression of the first information, and wherein the second user is a patient reading the output expression of the second information, the output expression using replacement terms for the medical terms.

12. The system of claim 1, further comprising a third computer connected with the healthcare network, the third computer configured to output third information to a third user having a third role, the third role different than the first role and the second role, wherein the first computer or the third computer perform actions comprising:

selecting the third user as a target of the third information;

determining the roles of each of the first and the third users based on a login credential used by each of the first and the third users;

assigning, based on the determined role of each of the first and third users and a context of the communication, at least a first base model ontology to the first user and at least a third base model ontology to the third user, the first base model ontology being different than each of the second and third base model ontologies;

translating the first information to the third information using the first and the third base models of the ontologies for the first and third roles, an input expression of the first information input from the first user being different than an output expression of the second information output to the second user and different than an output expression of the third information output to the third user, but the three expressions communicating a same concept.

13. The system of claim 12, wherein the second user and the third user are members of a common healthcare group.

14. A computer-implemented method for communicating medical information between different entities, the method comprising:

selecting a second user from a healthcare group, the selecting based on an identity of a first user and a context of a communication sent by the first user to the healthcare group;

subsequent to the selecting, determining a first role of the first user and a second role of the second user, the determining based on login credentials used by each of the first user and the second user to access medical information on a healthcare network of a medical facility;

assigning a first base model ontology to the first user and a second base model ontology to the second user, wherein the assigning is based on the determined roles of each of the first and the second users and the context of a communication between the first user and the second user;

creating, by mining a healthcare database for data about the first user and the second user, a first personalized ontology model by linking to first subsets of a first base model ontology and a second personalized ontology model by linking to second subsets of a second base model ontology, the first personalized ontology model automatically determined by data available to the processor about the first user and the second personalized ontology model automatically determined by data available to the processor about the second user;

translating, using the first personalized ontology model and the second personalized ontology model, a first information input by the first user having the first role to a second information to output to the second user having the second role, the first information being different than the second information but communicating a same concept; and

transmitting the second information to the second user.

15. The method of claim 14, wherein the data mined and used to create each of the first personalized ontology model and the second personalized ontology model comprises:

treatment experience of each of the first and the second user, education of each of the first and second user, specialization of the second user, and gender of the each of the first and second user.

16. The method of claim 15, wherein the data mined and used to create at least the first personalized ontology model comprises a patient profile on the healthcare network and an electronic medical record.