System and method for generating feeback on physiometry analyzed during automated patient management

• US 20060253006A1
• Filed: 06/30/2006
• Published: 11/09/2006
• Est. Priority Date: 06/03/1999
• Status: Abandoned Application

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Bardy, Gust H.
• Application Number:
  US11/480,634
• Publication Number:
  US 20060253006A1
• 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: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0215 by means inserted into the body catheters A61M25/00
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/333 Recording apparatus specially adapted therefor
• CPC Class Codes: A61B 5/4878 Evaluating oedema
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 7/02 Stethoscopes acoustic details thereof G10K11/00
• CPC Class Codes: A61N 1/37258 Alerting the patient
• CPC Class Codes: A61N 1/37282 : characterised by communication with experts in remote locations using a network
• CPC Class Codes: A61N 1/39622 : Pacing therapy
• 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 40/67 : for remote operation
• CPC Class Codes: G16H 50/00 : ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y10S 128/92 : Computer assisted medical diagnostics

Abstract

A system and method for generating feedback on physiometry analyzed during automated patient management is described. A patient enrolled in automated patient care is identified, along with information including at least one of treatment profile and medical history. Collected device measures are received to provide raw physiometry for the patient that was regularly monitored and recorded by a medical device. Derived device measures are determined to provide derivative physiometry based on the collected device measures. The collected and derived device measures quantify feedback including an analyzed pathophysiology indicative of patient well being.

Claims

1. Stored feedback on physiometry analyzed during automated patient management, comprising:

information to identify a patient enrolled in automated patient care and comprising at least one of treatment profile and medical history;

collected device measures to provide raw physiometry for the patient that was regularly monitored and recorded by a medical device; and

derived device measures to provide derivative physiometry based on the collected device measures,

wherein the collected and derived device measures quantify feedback comprising an analyzed pathophysiology indicative of patient well being.

2. Stored feedback according to claim 1, further comprising:

at least one feedback message selected from the group comprising an interpretive patient status, a medical diagnosis patient notification, a medical diagnosis caregiver notification, and reprogramming instructions for the medical device.

3. Stored feedback according to claim 1, further comprising:

evaluation parameters to define a threshold for the pathophysiology in terms of the patient well being; and

a wellness indicator determined by analyzing one or more of the collected and derived device measures against the evaluation parameters.

4. Stored feedback according to claim 3, further comprising:

a trend indicator determined by evaluating a plurality of the wellness indicators to identify one of an absence, onset, progression, regression, and status quo of a physiological disorder.

5. Stored feedback according to claim 1, further comprising:

a baseline pathophysiology quantified by those of the collected and derived device measures associated with a fixed time period.

6. Stored feedback according to claim 1, further comprising:

quality of life measures to provide qualified voice feedback data electronically recorded by the patient contemporaneous to recordation of the collected device measures.

7. Stored feedback according to claim 1, further comprising:

an index physiological disorder determined by evaluating a plurality of the wellness indicators to order and prioritize multiple near-simultaneous physiological disorders.

8. Stored feedback according to claim 1, wherein the medical device comprises one of an implantable medical device and an external medical device.

9. A patient communicator for generating feedback on physiometry analyzed during automated patient management, comprising:

information comprising at least one of treatment profile and medical history for a particular patient enrolled in automated patient care;

collected device measures to provide raw physiometry for the patient that was regularly monitored and recorded by a medical device; and

derived device measures to provide derivative physiometry based on the collected device measures,

wherein the collected and derived device measures quantify feedback comprising an analyzed pathophysiology indicative of patient well being.

10. A patient communicator according to claim 9, further comprising:

at least one feedback message selected from the group comprising an interpretive patient status, a medical diagnosis patient notification, a medical diagnosis caregiver notification, and reprogramming instructions for the medical device.

11. A patient communicator according to claim 9, further comprising:

evaluation parameters to define a threshold for the pathophysiology in terms of the patient well being; and

a wellness indicator determined by analyzing one or more of the collected and derived device measures against the evaluation parameters.

12. A patient communicator according to claim 11, further comprising:

a trend indicator determined by evaluating a plurality of the wellness indicators to identify one of an absence, onset, progression, regression, and status quo of a physiological disorder.

13. A patient communicator according to claim 9, further comprising:

a baseline pathophysiology quantified by those of the collected and derived device measures associated with a fixed time period.

14. A patient communicator according to claim 9, wherein the medical device comprises one of an implantable medical device and an external medical device.

15. An analysis system for generating feedback on physiometry analyzed during automated patient management, comprising:

a database to store patient records that each comprise;

information to identify a patient enrolled in automated patient care and comprising at least one of treatment profile and medical history; and

collected device measures to provide raw physiometry for the patient that was regularly monitored and recorded by a medical device;

an interface to periodically receive the collected device measures; and

a processing module, comprising;

a data processor to determine derived device measures based on the collected device measures to provide derivative physiometry; and

an analyzer to evaluate the collected and derived device measures to quantify feedback comprising an analyzed pathophysiology indicative of patient well being.

16. An analysis system according to claim 15, further comprising:

a feedback module to generate at least one feedback message selected from the group comprising an interpretive patient status, a medical diagnosis patient notification, a medical diagnosis caregiver notification, and reprogramming instructions for the medical device.

17. An analysis system according to claim 15, further comprising:

evaluation parameters to define a threshold for the pathophysiology in terms of the patient well being; and

a wellness indicator determined by analyzing one or more of the collected and derived device measures against the evaluation parameters.

18. An analysis system according to claim 17, further comprising:

a trend indicator determined by evaluating a plurality of the wellness indicators to identify one of an absence, onset, progression, regression, and status quo of a physiological disorder.

19. An analysis system according to claim 15, further comprising:

a baseline pathophysiology quantified by those of the collected and derived device measures associated with a fixed time period.

20. An analysis system according to claim 15, further comprising:

an index physiological disorder determined by evaluating a plurality of the wellness indicators to order and prioritize multiple near-simultaneous physiological disorders.

21. An analysis system according to claim 15, wherein the medical device comprises one of an implantable medical device and an external medical device.

22. A structured record to store feedback on physiometry analyzed during automated patient management, comprising:

structured data for a patient enrolled in automated patient care, comprising at least one of;

collected device measures to provide raw physiometry for the patient that was regularly monitored and recorded by a medical device;

derived device measures to provide derivative physiometry based on the collected device measures; and

quality of life measures to provide qualified voice feedback data electronically recorded by the patient contemporaneous to recordation of the collected device measures,

wherein the collected and derived device measures quantify and the quality of life measures qualify an analyzed pathophysiology indicative of patient well being.

23. A structured record according to claim 22, further comprising:

at least one feedback message selected from the group comprising an interpretive patient status, a medical diagnosis patient notification, a medical diagnosis caregiver notification, and reprogramming instructions for the medical device.

24. A structured record according to claim 22, further comprising:

a wellness indicator determined by analyzing one or more of the collected and derived device measures against evaluation parameters that define a threshold for the pathophysiology in terms of the patient well being.

25. A structured record according to claim 24, further comprising:

a trend indicator determined by evaluating a plurality of the wellness indicators to identify one of an absence, onset, progression, regression, and status quo of a physiological disorder.

26. A structured record according to claim 22, further comprising:

a baseline pathophysiology quantified by those of the collected and derived device measures associated with a fixed time period.

27. A structured record according to claim 22, further comprising:

an index physiological disorder determined by evaluating a plurality of the wellness indicators to order and prioritize multiple near-simultaneous physiological disorders.

28. A structured record according to claim 22, wherein the medical device comprises one of an implantable medical device and an external medical device.

29. A method for generating feedback on physiometry analyzed during automated patient management, comprising:

identifying a patient enrolled in automated patient care with information comprising at least one of treatment profile and medical history;

receiving collected device measures to provide raw physiometry for the patient that was regularly monitored and recorded by a medical device; and

determining derived device measures to provide derivative physiometry based on the collected device measures, wherein the collected and derived device measures quantify feedback comprising an analyzed pathophysiology indicative of patient well being.

30. A method according to claim 29, further comprising:

generating at least one feedback message selected from the group comprising an interpretive patient status, a medical diagnosis patient notification, a medical diagnosis caregiver notification, and reprogramming instructions for the medical device.

31. A method according to claim 29, further comprising:

specifying evaluation parameters to define a threshold for the pathophysiology in terms of the patient well being; and

determining a wellness indicator by analyzing one or more of the collected and derived device measures against the evaluation parameters.

32. A method according to claim 31, further comprising:

determining a trend indicator by evaluating a plurality of the wellness indicators to identify one of an absence, onset, progression, regression, and status quo of a physiological disorder.

33. A method according to claim 29, further comprising:

determining a baseline pathophysiology by quantifying those of the collected and derived device measures associated with a fixed time period.

34. A method according to claim 29, further comprising:

determining an index physiological disorder by evaluating a plurality of the wellness indicators to order and prioritize multiple near-simultaneous physiological disorders.

35. A method according to claim 29, wherein the medical device comprises one of an implantable medical device and an external medical device.

36. A computer-readable storage medium holding code for performing the method according to claim 29.