Decision support tool for managing autoimmune inflammatory disease

• US 10,586,617 B1
• Filed: 10/10/2018
• Issued: 03/10/2020
• Est. Priority Date: 01/10/2012
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: McNair, Douglas S.
• Primary Examiner(s): Vo, Tuyen K
• Application Number:
  US16/157,013
• Time in Patent Office: 517 Days
• Field of Search: 235375
• CPC Class Codes: G06F 16/90 Details of database functions independent of the retrieved data types
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06F 21/6245 Protecting personal data, e.g. for financial or medical purposes
• CPC Class Codes: G06Q 50/22 Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 10/65 stored on portable record carriers, e.g. on smartcards, RFID tags or CD
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Decision support technology is provided for use with patients who may experience respiratory deterioration. A mechanism is provided to determine whether a patient is experiencing (or is likely to experience at a future time) an autoimmune inflammatory event, which may include performing a spectral analysis on a time series of nocturnal or axillary temperatures for the patient to determine a spectrum slope or intercept. The time series may be demeaned, detrended, and apodized before performing the spectral analysis. A comparison of the slope or intercept with a baseline value is used to determine an indication of the patient'"'"'s likely condition or future condition regarding the autoimmune inflammatory event. Based on the comparison, an intervening action may be invoked, such as alerting a caregiver, providing a recommendation or modified treatment, or determining and recommending a tailored prescription of medicine for the patient.

Claims

1. A system for providing decision support for an autoimmune inflammatory condition, comprising:

a wearable temperature sensor having a radio frequency (RF) beacon for wirelessly communicating temperature information collected from the temperature sensor;

a monitoring device that receives the temperature information from the RF beacon;

at least one processor; and

computer storage memory having computer-executable instructions stored thereon which, when executed by the at least one processor, implement a method comprising;

receiving the temperature information from the monitoring device, the temperature information comprising a plurality of temperature measurements determined using the wearable temperature sensor;

determining a time series from the received temperature information;

performing a spectral analysis on at least a portion of the time series to determine at least one of a spectrum slope and an intercept in a frequency passband;

comparing at least one of the spectrum slope to a baseline spectrum slope value and the intercept to a baseline intercept value; and

based on the comparison, invoking one or more actions for the autoimmune inflammatory condition.

2. The system of claim 1, further comprising:

extracting from the time series a set of temperature measurements that includes a number of most recent temperature measurements of the plurality of temperature measurements; and

appending a current temperature measurement to the extracted set of temperature measurements, wherein the portion of the time series that the spectral analysis is performed on includes the extracted set of temperature measurements and the current temperature measurement.

3. The system of claim 1, further comprising determining the baseline spectrum slope value and the baseline intercept value from at least one of:

a historical set of temperature information for an individual associated with the wearable temperature sensor; and

a population not having the autoimmune inflammatory condition.

4. The system of claim 1, wherein the monitoring device is a mobile device running an application, the mobile device including the at least one processor and the computer storage memory.

5. The system of claim 1, wherein the temperature information is determined at a sampling rate of at least one temperature measurement per minute.

6. The system of claim 1, wherein the comparison is performed using quantile regression of the determined power spectra.

7. The system of claim 1, wherein the one or more actions comprise at least one of:

adjusting a medication regimen for the autoimmune inflammatory condition, modifying a care program for treating the autoimmune inflammatory condition, automatically scheduling interventions or consultations with specialist caregivers, and generating a notification.

8. The system of claim 1, wherein the portion of the time series that the spectral analysis is performed on comprises at least 8,000 temperature measurements, and wherein the at least 8,000 temperature measurements are determined over a time frame of at least 21 days.

9. One or more non-transitory computer storage media having computer-executable instructions stored thereon that, when executed, facilitate a method of providing clinical decision support for an autoimmune inflammatory condition, the method comprising:

receiving temperature information, the temperature information comprising a plurality of temperature measurements determined using a wearable temperature sensor;

determining a time series from the received temperature information;

performing a spectral analysis on at least a portion of the time series to determine at least one of a spectrum slope and an intercept in a frequency passband;

comparing at least one of the spectrum slope to a baseline spectrum slope value and the intercept to a baseline intercept value; and

based on the comparison, invoking one or more actions for the autoimmune inflammatory condition, the one or more actions including adjusting a medication regimen for the autoimmune inflammatory condition, modifying a care program for treating the autoimmune inflammatory condition, automatically scheduling interventions or consultations with specialist caregivers, and generating a notification.

10. The media of claim 9, wherein the temperature information is received from a monitoring device in communication with a radio frequency (RF) beacon of the wearable temperature sensor.

11. The media of claim 9, wherein the spectral analysis is performed using at least one of Fast Fourier Transform and Wavelet Transform.

12. The media of claim 9, further comprising:

extracting from the time series a set of temperature measurements that includes a number of most recent temperature measurements of the plurality of temperature measurements; and

appending a current temperature measurement to the extracted set of temperature measurements, wherein the portion of the time series that the spectral analysis is performed on includes the extracted set of temperature measurements and the current temperature measurement.

13. The media of claim 9, wherein the baseline spectrum slope value and the baseline intercept value are determined from at least one of:

a historical set of temperature information for an individual associated with the wearable temperature sensor; and

a population not having the autoimmune inflammatory condition.

14. The media of claim 9, wherein the comparison is performed using quantile regression of the determined power spectra.

15. The media of claim 9, wherein the portion of the time series that the spectral analysis is performed on comprises at least 8,000 temperature measurements, and wherein the at least 8,000 temperature measurements are determined over a time frame of at least 21 days.

16. The media of claim 9, wherein the temperature information is determined at a sampling rate of at least one temperature measurement per minute.

17. A computer-implemented method for providing clinical decision support for an autoimmune inflammatory condition, the method comprising:

receiving, at one or more processors, temperature information, the temperature information comprising a plurality of temperature measurements determined using a wearable temperature sensor;

determining, at the one or more processor, a time series from the received temperature information;

performing, at the one or more processor, a spectral analysis on at least a portion of the time series to determine at least one of a spectrum slope and an intercept in a frequency passband;

comparing, at the one or more processor, at least one of the spectrum slope to a baseline spectrum slope value and the intercept to a baseline intercept value; and

based on the comparison, adjusting, at the one or more processor, a treatment regimen for the autoimmune inflammatory condition.

18. The method of claim 17, wherein the temperature information is determined at a sampling rate of at least one temperature measurement per minute.

19. The method of claim 17, wherein the portion of the time series that the spectral analysis is performed on comprises at least 8,000 temperature measurements, and wherein the at least 8,000 temperature measurements are determined over a time frame of at least 21 days.

20. The method of claim 17, wherein the comparison is performed using quantile regression of the determined power spectra.