SYSTEM AND METHOD FOR OPTIMIZING THE FREQUENCY OF DATA COLLECTION AND THRESHOLDS FOR DETERIORATION DETECTION ALGORITHM

• US 20150297078A1
• Filed: 11/25/2013
• Published: 10/22/2015
• Est. Priority Date: 12/03/2012
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Gross, Brian David, Frassica, Joseph James
• Granted Patent: US 10,039,451 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• 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 5/082 Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath A61B5/083, A61B5/091 take precedence
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• 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: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method of monitoring a patient includes receiving patient data from one or more sensors (22) a patient monitoring system (10), comparing the received patient data with preselected thresholds indicative of patient status, determining a patient status from comparing the received patient data with the preselected thresholds, and automatically adjusting a sampling frequency of the one or more sensors (22) based on the determined patient status.

Claims

1. A patient monitoring system comprising:

one or more sensors which sample patient data of a patient at a sampling frequency;

a controller configured to receive the patient data from the one or more sensors, the controller programmed to;

determine a patient status with the patient data

determine at least one of a predisposition for a deterioration event and a probability of deterioration which are utilized to optimize the sampling rate of the one or more sensors; and

automatically adjust the sampling frequency of the one or more sensors based on the determined patient status.

2. The patient monitoring system according to claim 1, wherein the controller is further programmed to determine at least one of a predisposition for a deterioration event and a probability of deterioration which are utilized to optimize the sampling rate of the one or more sensors.

3. The patient monitoring system according to claim 1, wherein the patient data includes at least one of currently monitored physiological data and inputted clinical data.

4. The patient monitoring system according to claim 1, wherein the controller is further programmed to determine a patient clinical profile based on the patient data and the at least one of a predisposition for a deterioration event and a probability of deterioration.

5. The patient monitoring system according to claim 4, wherein the controller is further programmed to adjust the sampling rate of one or more predetermined sensors which measure parameters of interest according to the patient clinical profile.

6. The patient monitoring system according to claim 1, wherein the controller is further programmed to:

determine a baseline of the patient data;

calculate a propensity score for deterioration and probability thresholds based on the baseline of the patient data; and

calculate an initial probability curve from the propensity score and the probability thresholds.

7. The patient monitoring system according to claim 1, wherein the patient status is determined by comparing the received patient data against previously received patient data.

8. The patient monitoring system according to claim 1, wherein the controller is further configured to receive clinical data, such as electronic medical records, from a patient information system and is further programmed to:

determine the patient status from the clinical data.

9. The patient monitoring system according to claim 8, wherein the clinical data includes electronic medical records.

10. A method of monitoring a patient, the method comprising:

receiving patient data from one or more sensors a patient monitoring system;

receiving clinical data from a patient information system;

comparing the received patient data with preselected thresholds indicative of patient status;

determining a patient status from comparing the received patient data with the preselected thresholds and clinical data;

determining at least one of a predisposition for a deterioration event and a probability of deterioration; and

automatically adjusting a sampling frequency of the one or more sensors based on the determined patient status.

11. The method according to claim 10, wherein the patient data includes at least one of currently monitored physiological data and inputted clinical data.

12. The method according to claim 10, further including:

determining a patient clinical profile based on the patient and clinical data and the at least one of a predisposition for a deterioration event and a probability of deterioration.

13. The method according to claim 12, further including:

adjusting the sampling rate of one or more predetermined sensors which measure parameters of interest according to the patient clinical profile.

14. The method according to claim 10, further including:

determining a baseline of the patient data;

calculating a propensity score for deterioration and probability thresholds based on the baseline of the patient data and clinical data; and

calculating an initial probability curve from the propensity score and the predetermined thresholds.

15. The method according to claim 10, wherein the patient data includes at least one of currently monitored physiological data and inputted clinical data and the patient status is determined by comparing the received patient data against previously received patient data.

16. A computer readable medium containing software which, when loaded into a processor, programs the processor to perform the method according to claim 10.

17. A patient monitoring station comprising:

one or more sensors via which physiological data is received; and

one or processors programmed to perform the method according to claim 10.

18. A patient monitoring system comprising:

one or more sensors which sample patient data of a patient at a sampling frequency;

a deterioration detection system which receives the patient data from the one or more sensors, determines a patient status with the patient data, and automatically adjusts the sampling frequency of the one or more sensors based on the determined patient status.

19. The patient monitoring system according to claim 18, wherein deterioration detection system further determines at least one of a predisposition for a deterioration event and a probability of deterioration to optimize the sampling rate of the one or more sensors.

20. The patient monitoring system according to claim 18, wherein deterioration detection system further determines a clinical profile based on the patient data and the at least one of a predisposition for a deterioration event and a probability of deterioration.

21. The display according to claim 20, wherein deterioration detection system further adjusts the sampling rate of one or more predetermined sensors which measure parameters of interest according to the clinical profile.

22. The patient monitoring system according to claim 18, wherein the patient data includes at least one of currently monitored physiological data and inputted clinical data and the patient status is determined by comparing the received patient data against previously received patient data.