Method and apparatus for monitoring using a mathematical model

• US 20040236188A1
• Filed: 05/19/2003
• Published: 11/25/2004
• Est. Priority Date: 05/19/2003
• Status: Abandoned Application

• Current Assignee: GE Medical Systems Information Technologies Incorporated (GE Healthcare Technologies, Inc.)
• Original Assignee: Technologies, Inc. (APi Group Corp.), GE Medical Systems Information
• Inventors: Schluter, Paul S., Hutchinson, George M.
• Application Number:
  US10/440,747
• Publication Number:
  US 20040236188A1
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method and an apparatus for use in monitoring are disclosed. The method and system involve the use of a mathematical model. The method and system are particularly useful in the field of patient monitoring when using a physiological mathematical model. A mathematical model can be used to identify an abnormal condition. The mathematical model can also be used to generate an alarm. Also, the mathematical model can be used to generate a suggested treatment for correcting an abnormal condition if an abnormal condition should arise, especially abnormal conditions requiring relatively immediate attention.

Claims

1. A method for generating an alarm, comprising:

acquiring data from a subject; and

generating a comparison based on the data and a mathematical model representing the subject.

2. The method of claim 1, further comprising generating an alarm based on the comparison.

3. The method of claim 1, further comprising identifying an abnormal condition based on the comparison.

4. The method of claim 3, further comprising displaying information relating to an abnormal condition that has been identified.

5. The method of claim 4, wherein the information displayed is a reason that the abnormal condition was identified.

6. The method of claim 4, wherein the information displayed is a suggested response to the identification of the abnormal condition.

7. The method of claim 1, wherein the data is data relating to a physiological characteristic.

8. The method of claim 1, wherein the mathematical model comprises a physiological mathematical model.

9. The method of claim 1, wherein comparing the data to the mathematical model comprises determining a degree of difference between a predicted value predicted based on the model and a data value based on the acquired data.

10. The method of claim 9, wherein the alarm generated depends on the degree of difference between the predicted value and the data value.

11. The method of claim 2, further comprising generating an alarm based on the comparison and indicating a reason for the alarm.

12. The method of claim 1, further comprising modifying parameters of the mathematical model to reflect characteristics of the subject.

13. The method of claim 12 , further comprising obtaining characteristics of the subject from a database.

14. The method of claim 1, further comprising identifying a subject using an identification device.

15. A method for generating an alarm in a medical monitoring device, comprising:

acquiring data from a patient; and

comparing the data to a physiological mathematical model.

16. The method of claim 15, further comprising generating an alarm based on the comparison of the data to the mathematical model.

17. The method of claim 15, further comprising identifying an abnormal condition based on the comparison.

18. The method of claim 17, further comprising displaying information relating to an abnormal condition that has been identified.

19. The method of claim 15, wherein the mathematical model of the patient models effects of a treatment selected from a group consisting of an administered drug and an administered therapy.

20. The method of claim 15, further comprising identifying a subject using an identification device.

21. The method of claim 15, wherein comparing the data to the mathematical model comprises determining a degree of difference between a predicted value predicted based on the model and a data value based on the data.

22. The method of claim 23, wherein the alarm generated depends on the degree of difference between the predicted value and the data value.

23. The method of claim 15, further comprising generating a record of an alarm that is generated.

24. The method of claim 15, wherein acquiring data from a patient comprises acquiring physiological data from a plurality of monitors.

25. A medical monitoring system comprising:

a data acquisition device configured to acquire physiological data relating to a patient; and

a processor configured to generate a comparison based on the physiological data acquired by the data acquisition device and a predicted value predicted by a physiological mathematical model, and configured to send an alarm signal based on the comparison.

26. The system of claim 25, further comprising an alarm signaling device that is responsive to the alarm signal from the processor.

27. The system of claim 25, further comprising a network interface that facilitates transfer of data across a network.

28. The system of claim 27, wherein the network interface facilitates the transfer of data relating to the physiological mathematical model.

29. The system of claim 25, further comprising an identity detection device configured to identify the patient.

30. The system of claim 25, further comprising a bill generator configured to generate a billing record based on the use of the system.

31. The system of claim 25, wherein the processor determines a degree of difference between the predicted value and a data value that is based on the physiological data.

32. The system of claim 31, wherein the processor generates a different alarm signal based on the degree of difference between the predicted value and the data value.

33. The system of claim 25, wherein the processor is configured to send an indication signal indicating the reason that the alarm signal is generated when the alarm signal is generated.

34. The system of claim 25, wherein the processor is configured to establish the mathematical model based on characteristics of the patient that are stored in a database.

35. A method for providing guidance relating to treatment of a patient using a computing device, comprising:

monitoring the patient with a medical monitor using a data acquisition device;

inputting physiological data from the data acquisition device relating to the patient to the computing device; and

determining an appropriate treatment based on the physiological data using a mathematical model wherein the mathematical model does not require anatomic features to be incorporated for an appropriate suggestion to be generated.

36. The method of claim 35, wherein the mathematical model comprises a physiological mathematical model.

37. A patient physiologic monitoring assembly comprising:

a sensor generating a real-time physiologic data stream; and

a controller receiving said real-time physiologic data stream, said controller including a logic adapted to

generate a simulated physiologic data stream in response to a simulated treatment procedure simulated on a physiologic mathematical model;

receive said real-time physiologic data stream in response to a physical treatment procedure;

compare said real-time physiologic data stream to said simulated physiologic data stream; and

generate an alarm when said real-time physiologic data stream diverges from said simulated physiologic data stream.

38. A patient physiologic monitoring assembly as described in claim 37, wherein said alarm is generated when said real-time physiologic data stream crosses a hard threshold relative to said simulated physiologic data stream.

39. A patient physiologic monitoring assembly as described in claim 37, wherein said alarm is generated when said real-time physiologic data stream moves in a direction opposite said simulated physiologic data stream.

40. A patient physiologic monitoring assembly as described in claim 37, wherein said logic is further adapted to coordinate said simulated treatment procedure with said physical treatment procedure.

41. A patient physiologic monitoring assembly as described in claim 37, wherein said logic is further adapted to incorporate a plurality of patient attributes into said physiologic mathematical model.

42. A patient physiologic monitoring assembly as described in claim 37, further comprising an event monitor in communication with said controller, said event monitor signaling the initiation of said physical treatment procedure.

43. A method of patient physiologic monitoring comprising:

generating a simulated physiologic data stream in response to a simulated treatment procedure simulated on a physiologic mathematical model;

receiving a real-time physiologic data stream in response to a physical treatment procedure;

comparing said real-time physiologic data stream to said simulated physiologic data stream; and

generating an alarm when said real-time physiologic data stream diverges from said simulated physiologic data stream.

44. A method of patient physiologic monitoring as described in claim 43, further comprising:

developing said physiologic mathematical model; and

generating a simulated treatment procedure on said physiologic mathematical model.

45. A method of patient physiologic monitoring as described in claim 43, further comprising coordinating said simulated treatment procedure with said physical treatment procedure.

46. A method of patient physiologic monitoring as described in claim 43, further comprising generating a prediction of a physiologic response in response to a proposed treatment procedure.