METHOD AND SYSTEM FOR MAKING MULTISITE PERFORMANCE MEASURE ANONYMOUS AND FOR CONTROLLING ACTIONS AND RE-IDENTIFICATION OF ANONYMOUS DATA

• US 20150302070A1
• Filed: 12/09/2013
• Published: 10/22/2015
• Est. Priority Date: 12/10/2012
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: GROSS, Brian David, ELDO, Issac
• Granted Patent: US 10,025,840 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/20 of structured data, e.g. relational data
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46

Abstract

A system for making data source anonymous including a plurality of data sources, each data source including a data creation engine which creates normalized data in accordance with a common schema and a transformation engine which de-normalizes the normalized data such that the data source cannot be inferred by other data sources and transmits the de-normalized data to a remote computing resource.A remote computing resource receives and stores the de-normalized data from the plurality of data sources.

Claims

1. A system for making data source anonymous, the system comprising:

a plurality of data sources, each data source including;

a data creation engine which creates normalized data in accordance with a common schema;

a transformation engine which de-normalizes the normalized data such that the data source cannot be inferred by other data sources and transmits the de-normalized data to a remote computing resource;

the remote computing resource receiving and storing the de-normalized data from the plurality of data sources.

2. The system according to claim 1, wherein the normalized data includes one or more unique attributes that infer the identity of the data source

3. The system according to claim 2, wherein the transformation engine transforms the normalized data to de-normalized data by altering the number of entries for each of the one or more unique attributes.

4. The system according to claim 1, wherein the transformation engine generates a table of global unique identifiers to maps each unique attribute in the de-normalized data back to the normalized data format.

5. The system according to claim 1, wherein the remote computing resource utilizes the de-normalized data from the one or more data sources to provide performance analysis and/or reports.

6. The system according to claim 1, wherein the data sources are healthcare providers and the normalized data is clinical data.

7. A method for making data source anonymous, the method comprising:

creating normalized data in accordance with a common schema by a plurality of data sources;

de-normalizing the normalized data such that the data source cannot be inferred by other data sources by a transformation engine;

transmitting the de-normalized data to a remote computing resource;

storing the de-normalized data from the plurality of data sources at the remote computing resource.

8. (canceled)

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12. (canceled)

13. A system for making data source anonymous, the system comprising:

a plurality of data sources, each data source including;

a data creation engine which creates normalized data in accordance with a common schema and transmits the normalized data to a remote computing resource;

the remote computing resource receiving and storing the normalized data from the plurality of data sources and including;

a transformation engine which de-normalizes the normalized data such that the data source cannot be inferred by other data sources and stored the de-normalized data.

14. The system according to claim 13, wherein the remote computing engine controls access and re-identification of the de-normalized data.

15. The system according to claim 14, wherein the remote computing engine controls the actions to be invoked on the de-normalized data based on the role of the user logged into the data provider.

16. The system according to claim 15, wherein each data source includes:

an authorization engine which transmits a certificate to the remote computing resource to invoke a re-identification action.

17. The system according to claim 16, wherein the remote computing service compares the certificate transmitted from the data source to a stored certificate to authenticate the re-identification action.

18. The system according to claim 14, wherein the transformation engine generates a table of global unique identifiers to maps each unique attribute in the de-normalized data back to the normalized data format to re-identify the normalized data.

19. The system according to claim 13, wherein the normalized data includes one or more unique attributes that infer the identity of the data source.

20. The system according to claim 19, wherein the transformation engine transforms the normalized data to de-normalized data by altering the number of entries for each of the one or more unique attributes.