AUTOMATED PERFORMANCE MEASUREMENT PROCESSES AND SYSTEMS

• US 20130151197A1
• Filed: 11/21/2012
• Published: 06/13/2013
• Est. Priority Date: 11/23/2011
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Vattathara, Johny, Eppner, Vincent
• Application Number:
  US13/683,208
• Publication Number:
  US 20130151197A1
• Time in Patent Office: Days
• US Class Current: 702/179
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• 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: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Certain examples provide methods and systems to monitor performance. An example method includes triggering automated execution of one or more applications on one or more medical servers according to a selected template providing data for application execution. The example method includes monitoring the execution of the one or more applications to collect application execution information. The example method includes generating one or more log files based on the monitoring of the execution. The example method includes invoking a monitoring tool to process the log files and to provide statistical analysis regarding performance. The example method includes creating a report based on the statistical analysis.

Claims

1. A computer-implemented method to monitor performance, the method comprising:

triggering automated execution of one or more applications on one or more medical servers according to a selected template providing data for application execution;

monitoring the execution of the one or more applications to collect application execution information;

generating one or more log files based on the monitoring of the execution;

invoking a monitoring tool to process the log files and to provide statistical analysis regarding performance; and

creating a report based on the statistical analysis.

2. The method of claim 1, wherein the method is facilitated via a single automated script.

3. The method of claim 1, wherein the report comprises a performance matrix report organized by product and feature.

4. The method of claim 1, wherein the one or more medical servers comprise one or more of a picture archiving and communication system, a cardiovascular information system, and an electronic medical record system.

5. The method of claim 1, further comprising restarting the one or more medical servers prior to triggering execution of the one or more applications.

6. The method of claim 5, further comprising repeating the process one or more times beginning with restarting and updating the report after each repetition.

7. The method of claim 5, wherein the process is repeated until a target confidence level is reached.

8. The method of claim 7, wherein the confidence level is generated based on a variance in collected performance statistics.

9. The method of claim 8, wherein variation or spike in collected application execution information is evaluated to reject data noise from collected information and performance statistics to determine the confidence level.

10. The method of claim 1, wherein the one or more applications includes an image viewer and wherein statistical analysis of performance includes comparison of image viewer statistics across different image studies.

11. A tangible computer-readable storage medium including computer program instructions for execution by a computer, the instructions, which executed, are to implement a method to monitor performance, the method comprising:

triggering automated execution of one or more applications on one or more medical servers according to a selected template providing data for application execution;

monitoring the execution of the one or more applications to collect application execution information;

generating one or more log files based on the monitoring of the execution;

invoking a monitoring tool to process the log files and to provide statistical analysis regarding performance; and

creating a report based on the statistical analysis.

12. The computer-readable storage medium of claim 11, wherein the method is facilitated via a single automated script.

13. The computer-readable storage medium of claim 11, wherein the report comprises a performance matrix report organized by product and feature.

14. The computer-readable storage medium of claim 11, wherein the one or more medical servers comprise one or more of a picture archiving and communication system, a cardiovascular information system, and an electronic medical record system.

15. The computer-readable storage medium of claim 11, wherein the method further comprises restarting the one or more medical servers prior to triggering execution of the one or more applications.

16. The computer-readable storage medium of claim 15, wherein the method further comprises repeating the process one or more times beginning with restarting and updating the report after each repetition.

17. The computer-readable storage medium of claim 15, wherein the process is repeated until a target confidence level is reached.

18. The computer-readable storage medium of claim 17, wherein the confidence level is generated based on a variance in collected performance statistics.

19. The computer-readable storage medium of claim 18, wherein variation or spike in collected application execution information is evaluated to reject data noise from collected information and performance statistics to determine the confidence level.

20. The computer-readable storage medium of claim 11, wherein the one or more applications includes an image viewer and wherein statistical analysis of performance includes comparison of image viewer statistics across different image studies.