System and method for generating baseline data for automated management of cardiovascular pressure

• US 8,308,650 B2
• Filed: 11/03/2010
• Issued: 11/13/2012
• Est. Priority Date: 07/26/1999
• Status: Expired due to Fees

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Bardy, Gust H.
• Primary Examiner(s): Layno, Carl H.
• Assistant Examiner(s): MORALES, JON ERIC C
• Application Number:
  US12/938,686
• Publication Number:
  US 20110046493A1
• Time in Patent Office: 741 Days
• Field of Search: 600/508, 600/301
• US Class Current: 600/508
• 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 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/4884 inducing physiological or psychological stress, e.g. applications for stress testing
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/40 for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• 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 baseline data for automated management of cardiovascular pressure is disclosed. Collected device measures are accumulated to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period. Derived device measures are generated to provide derivative physiometry determined at least in part from the collected device measures. A patient status indicator is determined by analyzing the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo in cardiovascular pressure, wherein the collected and derived device measures and the patient status indicator originating from the initial observation period include baseline data.

Claims

1. A programmer for generating baseline data for automated management of cardiovascular pressure, comprising:

a memory to store device measures received from an implantable medical device, comprising;

collected device measures to record raw physiometry for a patient regularly monitored by the implantable medical device, beginning with an initial observation period; and

derived device measures to provide derivative physiometry determined at least in part from the collected device measures; and

a processor to determine a wellness indicator through analysis of the collected and derived device measures to diagnose a patient status indicative of at least one of a change and a status quo in cardiovascular pressure,

wherein the collected and derived device measures and the wellness indicator originating from the initial observation period comprise baseline data.

2. A programmer according to claim 1, wherein the analysis comprises one or more of:

a monitor to accumulate collected device measures and to derive derived device measures for use in determining the wellness indicator relating to cardiovascular pressure;

a patient well being analyzer to monitor patient well being in conjunction with at least one of potassium level, sodium level, hormonal level, and blood pressure; and

a programming interface to apply programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

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

an evaluator to process physiometric data conjunction with monitoring of the patient, wherein the physiometric data is selected from the group comprising;

analytic data recorded, collected, and stored for cardiovascular pressure evaluation;

alert data generated in response to significant events, wherein the alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

action data executed in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

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

physiometric data comprising one or more of the collected and derived device measures sensed through one or more of cardiovascular pressure, potassium level, sodium level, hormonal level, central nervous system injury, and central nervous system blood flow.

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

programming parameters, comprising at least one of;

monitoring parameters to monitor the patient while asleep; and

exclusion parameters to exclude physiometric data comprising one or more of the collected and derived device measures when the patient exhibits an increased respiratory rate due to exercise or activity level.

6. A programmer according to claim 1, further comprising:

programmed trigger conditions with corresponding actions, wherein the actions are executed by the processor based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in the raw physiometry measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.

7. An analysis system for generating baseline data for automated management of cardiovascular pressure, comprising:

a structured database, comprising;

collected device measures to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period; and

derived device measures to provide derivative physiometry determined at least in part from the collected device measures;

an analyzer to determine a wellness indicator through analysis of the collected and derived device measures to diagnose a patient status indicative of at least one of a change and a status quo in cardiovascular pressure; and

a processor to designate the collected and derived device measures and the wellness indicator originating from the initial observation period as baseline data.

8. An analysis system according to claim 7, wherein the structured database organizes processed data to reflect one or more of:

monitoring data comprising collected and derived device measures and a wellness indicator for cardiovascular pressure;

patient well being data monitored in conjunction with at least one of potassium level, sodium level, hormonal level, and blood pressure; and

programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

9. An analysis system according to claim 7, wherein the processor processes physiometric data in conjunction with monitoring of the patient, comprising at least one of:

database management comprising physiometric data recording, collection, and storage for cardiovascular pressure evaluation;

alert generation in response to significant events, wherein alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

action execution in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

10. An analysis system according to claim 7, further comprising:

physiometric data comprising one or more of the collected and derived device measures sensed through one or more of cardiovascular pressure, potassium level, sodium level, hormonal level, central nervous system injury, and central nervous system blood flow.

11. An analysis system according to claim 7, further comprising:

a programming interface to generate programming parameters, comprising at least one of;

monitoring parameters to monitor the patient while asleep; and

exclusion parameters to exclude physiometric data comprising one or more of the collected and derived device measures when the patient exhibits an increased respiratory rate due to exercise or activity level.

12. An analysis system according to claim 7, further comprising:

defined trigger conditions with corresponding actions that are executed based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in the raw physiometry measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.

13. A method for generating baseline data for automated management of cardiovascular pressure, comprising:

using an implantable medical device to accumulate collected device measures to record raw physiometry for a patient, wherein the patient is regularly monitored by the implantable medical device, beginning with an initial observation period;

generating derived device measures to provide derivative physiometry determined at least in part from the collected device measures; and

determining a wellness indicator by using a processor to analyze the collected and derived device measures to diagnose a patient status indicative of at least one of a change and a status quo in cardiovascular pressure,

wherein the collected and derived device measures and the wellness indicator originating from the initial observation period comprise baseline data.

14. A method according to claim 13, further comprising:

processing data, comprising one or more of;

monitoring data comprising collected and derived device measures and a wellness indicator relating to cardiovascular pressure;

monitoring patient well being in conjunction with at least one of potassium level, sodium level, hormonal level, and blood pressure; and

forming programming data to effect therapy modification selected from the group comprising device parameters, drug infusion parameters, and neural stimulation parameters.

15. A method according to claim 13, further comprising:

processing physiometric data in conjunction with monitoring of the patient, comprising at least one of;

recording, collecting, and storing data for cardiovascular pressure evaluation;

generating alert data in response to significant events, wherein the alert data is selected from the group comprising absolute measures, long term average measures, and short term average measures; and

executing actions in response to indications selected from the group comprising the significant events, ECG signals, activity level, temperature, pressure, and oxygen saturation.

16. A method according to claim 13, wherein physiometric data comprising one or more of the collected and derived device measures is sensed through one or more of cardiovascular pressure, potassium level, sodium level, hormonal level, central nervous system injury, and central nervous system blood flow.

17. A method according to claim 13, further comprising:

generating programming parameters, comprising at least one of;

defining monitoring parameters to monitor the patient while asleep; and

defining exclusion parameters to exclude physiometric data comprising one or more of the collected and derived device measures when the patient exhibits an increased respiratory rate due to exercise or activity level.

18. A method according to claim 13, further comprising:

executing trigger conditions with corresponding actions based upon the direct and derived device measures to cause activation of one or more of a therapy readout, alarm, or change in the raw physiometry measured,

wherein the trigger conditions are selected from the group comprising absolute measures, pattern matching, absolute differences between averaged measures, and comparisons of a current measure to another current measure or a previous measure.