Method and System for Predictive Modeling of Patient Outcomes

• US 20080235049A1
• Filed: 03/23/2007
• Published: 09/25/2008
• Est. Priority Date: 03/23/2007
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Morita, Mark, Hughes, William Douglas, Fors, Steve Lawrence
• Application Number:
  US11/690,589
• Publication Number:
  US 20080235049A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method and system for predictive modeling of patient outcomes. The predictive method includes the steps of applying an algorithm to patient data and displaying predicted patient data. The predictive method may further include the step of adjusting one or more clinical variables. The system includes a database of patient data, a rules engine operably connected to the database wherein the rules engine is capable of applying algorithms to the patient data to generate predicted patient data, and a user interface operably connected to the database.

Claims

1. A method for predictive modeling of patient outcomes comprising the steps of:

applying an algorithm to patient data; and

displaying predicted patient data.

2. The method of claim 1 further comprising adjusting one or more clinical variables.

3. The method of claim 1 wherein the patient data is selected from the group consisting of historical data, current data, or both.

4. The method of claim 3 wherein the patient data is retrieved from a data archive.

5. The method of claim 2 wherein the algorithm applies clinical guidelines to the patient data.

6. The method of claim 1 wherein the one or more clinical variables are selected from the group consisting of patient vitals, laboratory measurements, and dosing profiles.

7. The method of claim 2 wherein at least one clinical variable remains fixed based on the clinical guidelines.

8. The method of claim 5 wherein the clinical guidelines further define ranges for the adjustment of the one or more clinical variables.

9. The method of claim 1 further comprising the step of displaying patient historical data.

10. The method of claim 9 wherein the predicted patient data is displayed concurrently with the patient historical data.

11. A system for modeling patient outcomes based on historical patient data comprising;

a database of patient data;

a rules engine operably connected to the database wherein the rules engine is capable of applying algorithms to the patient data to generate predicted patient data; and

a user interface operably connected to the database and the rules engine, wherein the user interface is capable of receiving user input, providing the user input to the rules engine, and displaying predicted patient data generated by the rules engine.

12. The system of claim 11 wherein the database, rules engine, and user interface are operably connected via a network.

13. The system of claim 11 wherein the database is a data archive.

14. The system of claim 11 wherein the rules engine comprises at least one set of rules that apply at least one set of clinical guidelines to the patient data.

15. The system of claim 14 wherein the rules engine comprises multiple sets of rules that apply multiple sets of clinical guidelines to the patient data.

16. The system of claim 15 wherein the results of the application of at least one of the multiple sets of rules varies according to the results of the application of at least another one of the multiple sets of rules.

17. A computer readable storage medium including a set of instructions for a computer, the set of instructions comprising:

a data retrieval routine, wherein the data retrieval routine retrieves patient data;

a rules routine, wherein the rules routine applies clinical guidelines to the patient data; and

a user interface.

18. The computer readable storage medium of claim 17, wherein the set of instructions further comprises a display routine for displaying predicted patient data.

19. The computer readable storage medium of claim 17, wherein the rules routine identifies key variables and fixed variables.

20. The computer readable storage medium of claim 17, wherein the user interface is a graphical user interface.