Health Information Transformation System

• US 20120173475A1
• Filed: 12/30/2010
• Published: 07/05/2012
• Est. Priority Date: 12/30/2010
• Status: Abandoned Application

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: Ash, Michael Alan, Kailasam, Kanakasabha, Murrish, John Christopher, Fangman, Thomas Anthony
• Application Number:
  US12/982,143
• Publication Number:
  US 20120173475A1
• Time in Patent Office: Days
• US Class Current: 707/600
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses

Abstract

Methods, computer systems, and computer readable media for transforming raw healthcare data into relevant healthcare data are provided. Transformation of raw healthcare data into relevant data is accomplished by receiving raw data from a plurality of data collectors, where the plurality of data collectors extract the raw data from a plurality of raw data sources, and sorting the raw data into unstructured raw data, structured data of non-standard nomenclature, and structured data of standard nomenclature. The data is transformed into relevant data through the use of natural language processing, nomenclature and ontology mapping, and adaptive knowledge processing. The relevant data is stored in a plurality of data repositories, and computer applications and services are allowed access to the plurality of data repositories.

Claims

1. One or more computer-readable storage media having computer-executable instructions embodied thereon, that, when executed, implement a method for transforming raw healthcare data into relevant healthcare data, the method comprising:

receiving raw data from a plurality of data collectors, wherein the plurality of data collectors extract the raw data from a plurality of raw data sources;

sorting the raw data into unstructured raw data, structured data of non-standard nomenclature, and structured data of standard nomenclature;

transforming the sorted data into relevant data, wherein;

1) the unstructured raw data is transformed into relevant data through natural language processing, nomenclature and ontology mapping, and distributed adaptive knowledge processing,

2) the structured data of non-standard nomenclature is transformed into relevant data through nomenclature and ontology mapping, and distributed adaptive knowledge processing, and

3) the structured data of standard nomenclature is transformed into relevant data through distributed adaptive knowledge processing;

loading the relevant data into a plurality of data repositories; and

providing computer applications and services access to the plurality of data repositories.

2. The method of claim 1, wherein the raw data is collected from at least one of disparate sources or disparate locations.

3. The method of claim 1, wherein the raw data is collected from at least one of electronic medical records, images, documents, or medical devices.

4. The method of claim 1, wherein the plurality of data collectors comprise electronic medical record crawlers, clinical and administrative data collectors, claims data collectors, document feed collectors, and medical device feed collectors.

5. The method of claim 4, wherein the plurality of data collectors collect Health Level 7 data and Electronic Data Interchange data.

6. The method of claim 1, wherein the plurality of data repositories are optimized for specific use cases.

7. The method of claim 6, wherein at least one data repository is optimized for one patient, and further wherein at least one data repository is optimized for a plurality of patients.

8. One or more computer-readable storage media having computer-executable instructions embodied thereon, that, when executed, implement a system for transforming raw healthcare data into relevant healthcare data, the system comprising:

a receiving component that receives raw data from a plurality of collecting components, wherein the plurality of collecting components collects raw data from a plurality of raw data sources;

a sorting component that sorts the raw data into unstructured raw data, structured data of non-standard nomenclature, and structured data of standard nomenclature;

a transforming component that transforms the unstructured raw data, structured data of non-standard nomenclature, and structured data of standard nomenclature into relevant data, the transforming component comprising;

1) a natural language processing component that transforms unstructured raw data into at least one of structured data of non-standard nomenclature or structured data of standard nomenclature,

2) a nomenclature and ontology mapping component that transforms structured data of non-standard nomenclature into structured data of standard nomenclature, and

3) a distributed adaptive knowledge engine component that transforms structured data of standard nomenclature into relevant data;

a loading component that loads the relevant data into a plurality of data repositories; and

an access component that provides access to the plurality of data repositories.

9. The system of claim 8, wherein the distributed adaptive knowledge engine component determines which structured data of standard nomenclature should be transformed into relevant data, and further wherein the distributed adaptive knowledge component performs interpretation on the structured data of standard nomenclature.

10. The system of claim 8, wherein at least one of the plurality of data repositories is a data mart data repository, and further wherein the data mart data repository is identified.

11. The system of claim 10, wherein the relevant data loaded into the data mart data repository is used for decision support for a patient.

12. The system of claim 8, wherein the plurality of data repositories comprise a master patient index.

13. The system of claim 8, wherein at least one of the plurality of data repositories comprises an online analytical processing data repository, and further wherein the online analytical data repository is either identified or de-identified.

14. One or more computer-readable storage media having computer-executable instructions embodied thereon, that, when executed, implement a method for transforming raw healthcare data into relevant healthcare data, the method comprising:

receiving raw data from a plurality of data collectors, wherein the plurality of data collectors comprise electronic medical records crawlers, clinical and administrative data collectors, claims data collectors, document feed collectors, and medical device feed collectors, and further wherein the plurality of data collectors collect raw data from a plurality of raw data sources where the plurality of raw data sources comprise electronic medical records, images, documents, and medical devices;

sorting the raw data into unstructured raw data, structured data of non-standard nomenclature, and structured data of standard nomenclature;

transforming the raw data into relevant data, wherein;

1) the unstructured raw data is transformed into relevant data through natural language processing, nomenclature and ontology mapping, and distributed adaptive knowledge processing,

2) the structured data of non-standard nomenclature is transformed into relevant data through nomenclature and ontology mapping, and distributed adaptive knowledge processing, and

3) the structured data of standard nomenclature is transformed into relevant data through distributed adaptive knowledge processing;

loading the relevant data into a plurality of data repositories, wherein the plurality of data repositories comprise real time transaction processing data repository, online analytical processing data repository, data mart data repository, search index data repository, and custom data repository; and

providing computer application and services access to the plurality of data repositories.

15. The method of claim 14, wherein the natural language processing comprises:

identifying clinical concepts with codified meanings,

labeling clinical concepts as positive, suspected, or negative, and

translating the clinical concepts into health concepts.

16. The method of claim 14, wherein a care card application is allowed access to the data mart data repository.

17. The method of claim 16, wherein the care card application comprises at least one of an artificial intelligence engine or a standard rules engine.

18. The method of claim 17, wherein the artificial intelligence engine determines recommended treatments for a patient.

19. The method of claim 14, wherein the ontology and mapping component comprises:

receiving structured data of non-standard nomenclature comprising at least one discrete health concept,

associating the at least one discrete health concept with a first broader health concept, and

associating the first broader health concept with a second broader health concept.

20. The method of claim 14, wherein the document feed crawler obtains documents through email, facsimile, or extraction from the document source.