Analytics and data warehousing infrastructure and services

• US 7,191,183 B1
• Filed: 04/05/2002
• Issued: 03/13/2007
• Est. Priority Date: 04/10/2001
• Status: Active Grant

• Current Assignee: Rgi Informatics LLC
• Original Assignee: Rgi Informatics LLC
• Inventors: Goldstein, Richard H.
• Primary Examiner(s): Pham; Khanh B.
• Application Number:
  US10/118,219
• Time in Patent Office: 1,803 Days
• Field of Search: 707/6, 707/10, 707/100, 707/101, 705/2
• US Class Current: 707/602
• CPC Class Codes: G06F 16/972 Access to data in other repository systems, e.g. legacy data or dynamic Web page generation
• 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: Y10S 707/941 Human sciences
• CPC Class Codes: Y10S 707/962 Entity-attribute-value
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

An analytics and data warehousing infrastructure and services system that uses an analytic rather than a transactional data model. The system preferably has at least one extracted source data store, at least one staging data store, and at least one analytic data store. The at least one staging data store preferably has at least one staging data table. The at least one analytic data store preferably has at least one analytic data table for storing transformed data. A staging data table loading algorithm may be used for populating the at least one staging data table with source data. A data transformation algorithm may be used for moving and transforming data from a staging data table into an analytic data store. Other algorithms that may be used in the present invention include algorithms for creating derived variables, creating event proxies, and restructuring data. In one preferred embodiment, the system is a data model based on a clinical rather than a financial understanding of healthcare.

Claims

1. An analytics and data warehousing infrastructure and services system, said system comprising:

a. at least one source data store;

b. at least one extractor for extracting source data from said source data store;

c. at least one staging data store having at least one staging data table, said at least one staging data table being populated with said source data;

d. at least one analytic data store for storing transformed data;

e. at least one interrogation engine for moving and transforming data from said staging data table into said at least one analytic data store, said interrogation engine providing at least a partial denormalization of said data;

f. said at least one interrogation engine for supporting ad hoc analysis and data mining from a user interface, said at least one interrogation engine facilitating user independent definition and user generation of user defined query concepts, said interrogation engine generating computer programming to modify and query said at least one analytic data store or said at least one staging data store, said user defined query concepts being user independently defined and user independently generated analytic concepts, stratifications, or events created from variables in said at least one analytic data store or said at least one staging data store; and

g. at least one analytic and report means for generating analysis and reports;

h. wherein said system uses an analytic data model that allows said user to extract useful information from said at least one analytic data store or said at least one staging data store, find patterns in said at least one analytic data store or said at least one staging data store and interpret patterns in said at least one analytic data store or said at least one staging data store.

2. The system of claim 1, wherein said interrogation engine includes at least one interrogation means for moving and transforming data, said interrogation means selected from the group consisting of:

a. transformation algorithms;

b. means for creating derived variables;

c. means for restructuring data;

d. analytic store update algorithms; and

e. creation of derived variables algorithm.

3. The system of claim 1, wherein said interrogation engine allows independent authoring of new user defined query concepts to said at least one analytic data store or said at least one staging data store.

4. The system of claim 1, wherein said interrogation engine permits clinical user defined query concept questions of said at least one analytic data store or said at least one staging data store without knowing the question in advance.

5. The system of claim 1, wherein said said interrogation engine permits independent authoring of user defined query concepts that have not been pre-defined to said at least one analytic data store or said at least one staging data store.

6. The system of claim 1 wherein said at least one analytic and report means uses algorithms based on data mining and knowledge discovery.

7. The system of claim 1 wherein said system provides business solutions.

8. The system of claim 1 wherein said system is an application service provider model.

20. The system of claim 1, wherein said interrogation engine includes means for creating derived variables.

24. The system of claim 1, wherein said interrogation engine provides at least a partial denormalization of said data using an “

entity—

attribute—

value (EAV)”

schema.

28. The system of claim 1, wherein said interrogation engine facilitates user searching of said at least one analytic data store or said at least one staging data store for variables to use in stratification or event creation.

9. An analytics and data warehousing infrastructure and services system, said system comprising:

a. at least one source data store;

b. at least one extractor for extracting source data from said source data store;

c. at least one staging data table, said at least one staging data table being populated with said source data;

d. at least one analytic data store for storing transformed data;

e. at least one interrogation engine for moving and transforming data from said staging data table into said at least one analytic data store, said interrogation engine providing at least a partial denormalization of said data;

f. said at least one interrogation engine for supporting ad hoc analysis and data mining from a user interface, said at least one interrogation engine facilitating user independent definition and user generation of user defined query concepts, said interrogation engine generating computer programming to modify and query said at least one analytic data store or said at least one staging data store, said user defined query concepts being user independently defined and user independently generated analytic concepts, stratifications, or events created from variables in said at least one analytic data store or said at least one staging data store; and

g. at least one analytic and report means for generating analysis and reports;

h. wherein said system uses a data model based on a clinical rather than a financial understanding of healthcare.

21. The system of claim 9, wherein said interrogation engine includes means for creating derived variables.

25. The system of claim 9, wherein said interrogation engine provides at least a partial denormalization of said data using an “

entity—

attribute—

value (EAV)”

schema.

29. The system of claim 9, wherein said interrogation engine facilitates user searching of said at least one analytic data store or said at least one staging data store for variables to use in stratification or event creation.

10. An analytics and data warehousing infrastructure and services method, said method comprising:

a. providing at least one source data store;

b. extracting source data from said source data store;

c. populating at least one staging data table with said source data;

d. moving and transforming data from said staging data table into at least one analytic data store using at least one interrogation engine;

e. supporting ad hoc analysis and data mining from a user interface of said at least one interrogation engine, said at least one interrogation engine facilitating user independent definition and user generation of user defined query concepts, said interrogation engine generating computer programming to modify and query said at least one analytic data store or said at least one staging data store, said user defined query concepts being user independently defined and user independently generated analytic concepts, stratifications, or events created from variables in said at least one analytic data store or said at least one staging data store; and

f. generating analysis and reports using said at least one interrogation engine.

11. The method of claim 10 wherein said step of moving and transforming data from said staging data table into said at least one analytic data store further comprises the step of providing at least a partial denormalization of said data.

12. The method of claim 10, wherein said step of moving and transforming data from said staging data table into said at least one analytic data store further comprises at least one step selected from the group consisting of:

a. performing transformation algorithms;

b. creating derived variables;

c. restructuring data;

d. updating analytic stores; and

e. creating derived variables algorithm.

13. The method of claim 10, wherein said step of supporting ad hoc analysis and data mining from a user interface of said at least one interrogation engine further comprises the step of independently authoring of new user defined query concepts to said at least one analytic data store or said at least one staging data store.

14. The method of claim 10, wherein said step of supporting ad hoc analysis and data mining from a user interface of said at least one interrogation engine further comprises the step of permitting clinical user defined query concepts of said at least one analytic data store or said at least one staging data store without knowing the question in advance.

15. The method of claim 10, wherein said step of supporting ad hoc analysis and data mining from a user interface of said at least one interrogation engine further comprises the step of permitting independent authoring of user defined query concepts that have not been pre-defined to said at least one analytic data store or said at least one staging data store.

22. The method of claim 10, wherein said step of moving and transforming data from said staging data table into said at least one analytic data store further comprises the step of creating derived variables.

26. The method of claim 10, wherein said step of moving and transforming data further comprises the step of moving and transforming data from said staging data table into at least one analytic data store using an “

entity—

attribute—

value (EAV)”

schema.

30. The method of claim 10, further comprising the step of supporting user searching of said at least one analytic data store or said at least one staging data store for variables to use in stratification or event creation using said interrogation engine.

16. An analytic and data warehousing infrastructure and services system, said system comprising:

a. at least one extracted source data store;

b. at least one staging data store having at least one stating data table;

c. at least one analytic data store for storing transformed data;

d. at least one staging data table loading algorithm for populating said at least one stating data table with source data;

e. at least one data transformation algorithm for moving and transforming data from said at least one staging data table into said at least one analytic data store; and

f. at least one query algorithm that facilitates user generation of user defined query concepts and generates said user defined query concepts computer programming to modify and query said at least one analytic data store or said at least one stating data store, said at least one query algorithm implemented by at least one interrogation engine;

wherein said at least one query algorithm facilitates independent authoring of ad hoc queries that have not been pre-defined to said at least one analytic data store or said at least one staging data store.

17. The system of claim 16, wherein said at least one staging data table loading algorithm and said at least one data transformation algorithm are performed by said at least one interrogation engine.

18. The system of claim 16, wherein said at least one query algorithm facilitates independent authoring of new user defined query concepts to said at least one analytic data store or said at least one staging data store.

19. The system of claim 16, wherein said at least one query algorithm allows for clinical questions of said at least one at least one analytic data store or said at least one staging data store without knowing the question in advance.

23. The system of claim 16, wherein said at least one staging data table loading algorithm and said at least one data transformation algorithm create derived variables.

27. The system of claim 16, wherein said at least one data transformation algorithm further comprises at least one data transformation algorithm for moving and transforming data from said at least one staging data table into said at least one analytic data store using an “

entity—

attribute—

value (EAV)”

schema.

31. The system of claim 16, wherein said interrogation engine facilitates user searching of said at least one analytic data store or said at least one staging data store for variables to use in stratification or event creation.