System and method for analyzing a patient status for congestive heart failure for use in automated patient care

• US 20040230127A1
• Filed: 06/24/2004
• Published: 11/18/2004
• Est. Priority Date: 11/16/1999
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Bardy, Gust H.
• Granted Patent: US 7,972,274 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• CPC Class Codes: A61B 2505/03 Intensive care
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• 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 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• 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 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/076 Permanent implantations telemetry using implanted circuitry A61B5/0031; implanted stimulators for therapy A61N1/3605, A61N1/362, A61N1/372
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• 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 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/486 : Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/686 : Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• 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 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 : Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• 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 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y10S 128/923 : by comparison of patient data to other data

Abstract

A system and method for providing diagnosis and monitoring of congestive heart failure for use in automated patient care is described. At least one recorded physiological measure is compared to at least one other recorded physiological measure on a substantially regular basis to quantify a change in patient pathophysiological status for equivalent patient information. An absence, an onset, a progression, a regression, and a status quo of congestive heart failure is evaluated dependent upon the change in patient pathophysiological status.

Claims

1. A system for analyzing a patient status for congestive heart failure for use in automated patient care, comprising:

a server system receiving a set of one or more physiological measures relating to patient information recorded on a substantially continuous basis or derived therefrom;

a database module storing the physiological measures set into a patient care record for an individual patient into a database; and

an analyzer analyzing one or more of the physiological measures in the physiological measures set relative to one or more other physiological measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of congestive heart failure.

2. A system according to claim 1, further comprising:

the analyzer analyzing the physiological measures in the physiological measures set relative to the other physiological measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of diseases other than congestive heart failure.

3. A system according to claim 1, further comprising:

the server system receiving a set of one or more quality of life measures relating to patient information recorded on a substantially continuous basis or derived therefrom;

the database module storing the quality of life measures set into the patient care record for the individual patient into the database; and

the analyzer analyzing the quality of life measures in the physiological measures set relative to the other quality of life measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of congestive heart failure.

4. A system according to claim 1, further comprising:

the server system receiving a set of one or more baseline physiological measures relating to patient information recorded during an initial time period or derived therefrom;

the database module storing the baseline physiological measures set into the patient care record for the individual patient into the database; and

the analyzer analyzing the physiological measures in the physiological measures set relative to the baseline physiological measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of congestive heart failure.

5. A system according to claim 1, further comprising:

a comparison module retrieving the other physiological measures from measures sets for at least one of an individual patient, a peer group, and a overall patient population.

6. A method for analyzing a patient status for congestive heart failure for use in automated patient care, comprising:

receiving a set of one or more physiological measures relating to patient information recorded on a substantially continuous basis or derived therefrom;

storing the physiological measures set into a patient care record for an individual patient into a database; and

analyzing one or more of the physiological measures in the physiological measures set relative to one or more other physiological measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of congestive heart failure.

7. A method according to claim 6, further comprising:

analyzing the physiological measures in the physiological measures set relative to the other physiological measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of diseases other than congestive heart failure.

8. A method according to claim 6, further comprising:

receiving a set of one or more quality of life measures relating to patient information recorded on a substantially continuous basis or derived therefrom;

storing the quality of life measures set into the patient care record for the individual patient into the database; and

analyzing the quality of life measures in the physiological measures set relative to the other quality of life measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of congestive heart failure.

9. A method according to claim 6, further comprising:

receiving a set of one or more baseline physiological measures relating to patient information recorded during an initial time period or derived therefrom;

storing the baseline physiological measures set into the patient care record for the individual patient into the database; and

analyzing the physiological measures in the physiological measures set relative to the baseline physiological measures to determine a pathophysiology indicating an absence, an onset, a progression, a regression, and a status quo of congestive heart failure.

10. A method according to claim 6, further comprising:

retrieving the other physiological measures from measures sets for at least one of an individual patient, a peer group, and a overall patient population.

11. A computer-readable storage medium for a device holding code for performing the method according to claim 6.