REAL-TIME TIME SERIES MATRIX PATHOPHYSIOLOGIC PATTERN PROCESSOR AND QUALITY ASSESSMENT METHOD

• US 20130124221A1
• Filed: 11/14/2012
• Published: 05/16/2013
• Est. Priority Date: 11/14/2011
• Status: Abandoned Application

• Current Assignee: Lawrence A. Lynn
• Original Assignee: Lawrence A. Lynn
• Inventors: LYNN, Eric N., LYNN, Lawrence A.
• Application Number:
  US13/677,291
• Publication Number:
  US 20130124221A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06F 2218/18 by plotting the signal segments against each other, e.g. analysing scattergrams
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A device for providing information about a medical condition is described herein. A monitor gathers information about the physiological systems of the patient, reads from the memory storage, identifies time dimensioned dynamic patterns of the data, determines the severity of the patterns, identifies a distress condition based at least on a relative match between a the dynamic patterns of the data for a plurality of physiological systems, and calculates a real-time or near real-time sensitivity, specificity, therapeutic delay, and/or correlation metric. A display processor that provides a visual display of time dimensioned output of the severity of the dynamic patterns and a visual display of the sensitivity, specificity, therapeutic delay, and/or the correlation metric in real-time or near real-time.

Claims

1. A device for providing information about a medical condition, comprising:

a memory storage that contains information relating to software elements based on pathophysiological occurrence and the time series matrix data, being indicative of distress conditions of a patient;

a monitor that gathers information about the physiological systems of the patient, reads from the memory storage, identifies time dimensioned dynamic patterns of the data, determines the severity of the patterns, identifies a distress condition based at least on a relative match between a the dynamic patterns of the data for a plurality of physiological systems, and calculates a real-time or near real-time sensitivity, specificity, therapeutic delay, and/or correlation metric; and

a display processor that provides a visual display of time dimensioned output of the severity of the dynamic patterns and a visual display of the sensitivity, specificity, therapeutic delay, and/or correlation metric in real-time or near real-time.

2. The device of claim 1 wherein the device further determines and displays an animated time lapsed output of a time dimensioned correlation metric in spatial relation to physiological systems.

3. The device of claim 1 wherein the device further determines and displays the maximum potential correlation metric to a distress condition by processing additional simulated worst case or near worst case data as replacements for data which is unavailable for processing and by determining the maximum potential correlation metric using both the available data and the simulated replacement data.

4. The device of claim 3 wherein the device determines and displays a real-time, time dimensioned output of maximum potential correlation.

5. The device of claim 3 wherein the device further determines and displays the maximum potential correlation gap for a distress condition by comparing the correlation metric with the maximum potential correlation metric.

6. The device of claim 5 wherein the device further displays an animated time lapsed output of the time dimensioned correlation metric in spatial relation to at least one of the maximum potential correlation metric and the maximum potential correlation gap.

7. The device of claim 3 wherein the device identifies the potential gap as the difference between the maximum correlation and the maximum potential correlation and displays a time dimensioned output of the maximum potential correlation gap.

8. The device of claim 1 wherein the device determines and displays a real-time output of the maximum severity of patterns.

9. The device of claim 5 wherein the device determines and displays a real-time output of a time-series of a maximum correlation, maximum potential correlation, potential gap and/or maximum severity to at least one distress condition.

10. The device of claim 5 wherein the device determines and displays a time dimensioned output of maximum correlation, maximum potential correlation, potential gap and/or maximum severity separated by correlated distress conditions in the same display for comparison.

11. The device of claim 1 wherein the device provides a storm visualization utilizing maximum correlation.

12. The device of claim 3 wherein the device provides a storm visualization utilizing maximum potential correlation.

13. The device of claim 5 wherein the device provides a storm visualization utilizing potential gap.

14. The device of claim 8 wherein the device provides a storm visualization utilizing maximum severity.

15. The device of claim 1 wherein the device generates and displays a plurality of the correlations, potentials and severities of identified dynamic patterns to provide a time lapsed motion picture of aggregated evidence toward a distress condition.

16. The device of claim 1 wherein the device generates an output of the number of patterns that are within a specified range of the maximum pattern to provide weight to the diagnostic value of the maximum pattern.

17. The device of claim 5 wherein the device identifies patterns within a time dimensioned output of a maximum correlation, maximum potential correlation, potential gap and/or maximum severity.

18. The device of claim 5 wherein the device identifies patterns within of real-time output of at least one a time-series of a maximum correlation and at least one time series of maximum potential correlation, potential gap and/or maximum severity separated by physiological systems, correlated distress condition or disease stage.

19. The device of claim 5 wherein the device outputs a diagnostic or therapeutic response to patterns within the correlation metric time series and the patterns identified within the time-series of at least one of maximum correlation, maximum potential correlation, potential gap and/or maximum severity.

20. The device of claim 5 wherein the device provides at least one of a search, filter, sort and/or grouping of patients by dynamic patterns, changes in dynamic patterns, and/or by at least one of patterns within the time-series of a maximum correlation, maximum potential correlation, potential gap and/or maximum severity.

21. The device of claim 5 wherein the device identifies patterns between the correlation metric time series, maximum potential correlation time-series, potential gap time series and maximum severity time-series.

22. The device of claim 5 wherein the device displays the correlation metric time series, maximum potential correlation time-series, potential gap time series and maximum severity time-series in conjunction with clinical events.

23. The device of claim 3 wherein the device provides identification of recovery through trending patterns within the maximum correlation time series.

24. The device of claim 1 wherein the device provides tracking of healthcare expenses in conjunction with dynamic patterns.

25. The device of claim 1 wherein the device provides tracking response to thresholds and/or patterns with the maximum correlation time series.

26. The device of claim 1 wherein the device provides determining therapeutic delay by identifying when, based on the maximum correlation metric, action should be taken and when action was actually taken.

27. The device of claim 25 wherein the device generates a time series of therapeutic delay and provides identification of patterns within the time-series of therapeutic delay.

28. The device of claim 25 wherein the device provides comparing therapeutic delay between facilities, floors, and hospitals.

29. The device of claim 25 wherein the device provides a storm visualization utilizing therapeutic delay.

30. The device of claim 1 wherein the device provides determining expert to processor diagnostic gap by identifying the time-gap between when a distress condition is identified as present retrospectively by an expert and when device identified the distress condition.

31. The device of claim 29 wherein the device generates a time series of diagnostic gap and provides retrospective identification of patterns within a time-series of diagnostic gap.

32. The device of claim 1 wherein the device provides comparing diagnostic gap between different sets of patterns.

33. The device of claim 5 wherein the device provides comparison of at least one of techniques, biomarkers, and devices according to patterns of at least one of the time dimensioned correlatively, time dimensioned maximum potential, and time dimensioned diagnostic gap.