CLINICAL DECISION SUPPORT SYSTEM BASED TRIAGE DECISION MAKING

• US 20160328525A1
• Filed: 11/13/2014
• Published: 11/10/2016
• Est. Priority Date: 11/13/2013
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Gross, Brian David, Frassica, Joseph James, Salgo, Ivan
• Granted Patent: US 9,946,843 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2503/045 Newborns, e.g. premature baby monitoring
• 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 5/14542 for measuring blood gases A61B5/14551 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 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 2207/30104 Vascular flow; Blood flow; Perfusion
• CPC Class Codes: G06T 7/0014 using an image reference approach
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• 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: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A method includes obtaining an electrical signal that includes a set of at least two sensed physiologic measurements of a patient, comparing the at least two physiologic measurements with a predetermined physiologic measurement range, identifying data required to determine a probability and a severity of a condition of interest of the patient, in response to determining the at least two physiologic measurements do not satisfy the physiologic measurement range, receiving the identified data in electronic format, determining a first probability and a first severity of the condition of interest based on the received identified data, determining a recommended course of action for the patient based on the first probability and the first severity, resources of a healthcare facility, and an event guideline; and causing a display to visually present the first probability and first severity and the recommended course of action.

Claims

1. A method, comprising:

receiving an electrical signal that includes a set of at least two sensed physiologic measurements of a patient;

comparing the at least two physiologic measurements with a predetermined physiologic measurement range from a sensor output guideline, which is in electronic format;

identifying data required to determine a probability and a severity of a condition of interest of the patient based on a data guideline, in response to determining the at least two physiologic measurements do not satisfy the physiologic measurement range;

obtaining the identified data in electronic format;

determining a probability and a severity of the condition of interest based on the received identified data;

determining a recommended course of action for the patient based on the probability and the severity, resources of a healthcare facility, and an event guideline; and

causing a display to visually present the probability and first severity and the recommended course of action.

2. The method of claim 1, further comprising:

generating a control signal that controls an operation of an electronic device associated with healthcare for the patient based on the recommended course of action and the event guideline; and

controlling the operation of the electronic device with the control signal.

3. The method of claim 1, wherein the identified data includes image data.

5. The method of claim 3, further comprising:

receiving an image atlas of organ defects, wherein the determining the probability includes determining the probability and the severity of the condition of interest based on the image data and the image atlas of organ defects.

7. The method of claim 5, further comprising:

identifying other data likely to improve an accuracy of the probability and the severity of the condition of interest; and

updating the probability and the severity, based on the other data to generate an updated probability and an updated severity of the condition of interest.

12. The method of claim 1, wherein the condition of interest is a congenital cardiac defect of a newborn and the at least sensed physiologic measurements are blood oxygen concentrations, one sensed at a right foot of the newborn and the other sensed at a left hand of the newborn.

14. The method of claim 12, wherein comparing the at least two physiologic measurements includes taking a difference between the at least two physiologic measurements and determining a difference blood oxygen concentration value, comparing the difference blood oxygen concentration value with the measurement range from the sensor output guideline, and determining blood is being shunted around the lungs.

4. (canceled)

6. (canceled)

8. (canceled)

9. (canceled)

10. (canceled)

11. (canceled)

13. (canceled)

15. A system, comprising:

a computing system, including;

at least one computer processor;

input/output; and

computer readable storage medium encoded with a triage module

wherein

the input/output is configured to receive an electrical signal that includes a set of at least two sensed physiologic measurements of a patient; and

the at least one computer processor is configured to execute instructions of the triage module, said instructions including;

comparing the at least two physiologic measurements with a predetermined physiologic measurement range from a sensor output guideline, which is in electronic format;

identifying data required to determine a probability and a severity of a condition of interest of the patient based on a data guideline, in response to determining the at least two physiologic measurements do not satisfy the physiologic measurement range;

obtaining the identified data in electronic format;

determining a probability and severity of the condition of interest based on the received identified data; and

determining a recommended course of action for the patient based on the probability and the severity, resources of a healthcare facility, and an event guideline; and

causing a display to visually present the probability and the severity and the recommended course of action.

16. The system of claim 15, wherein the at least one computer processor is configured to control an operation of at least one electronic device based on the recommended course of action.

17. The system of claim 16, wherein the at least one computer processor is configured to further determine the probability and the severity based on image data and an image atlas of organ defects.

18. The system of claim 17, wherein the at least one computer processor is configured to further determine the probability and the severity based on physiologic sensor data, demographics, observations, and clinical data.

20. The system of claim 15, wherein the recommended course of action includes transporting the patient to another healthcare facility better equipped for the condition of interest.

21. The system of claim 20, wherein the recommended course of action further includes suggested healthcare to mitigate worsening of the condition of interest before the patient is transported.

22. The system of claim 15, wherein the recommended course of action includes suggested healthcare to mitigate worsening of the condition of interest at the healthcare facility using the resources available at the healthcare facility.

19. (canceled)

23. (canceled)

24. (canceled)

25. A non-transitory computer readable storage medium encoded with computer readable instructions, which, when executed by a processer, cause the processor to:

receive an electrical signal that includes a set of at least two sensed physiologic measurements of a patient;

compare a difference value of the at least two physiologic measurements with a predetermined physiologic measurement range from a sensor output guideline, wherein the at least two physiologic measurements correspond to blood oxygen concentration levels respectively sensed at a right foot of the patient and a left hand of the patient;

identify an ultrasound imaging procedure for acquiring data to determine a probability and a severity of a condition of interest of the patient, in response to determining the difference value falls outside of the physiologic measurement range;

obtain image data from a scan based on the identified ultrasound imaging procedure;

determine the probability and the first severity of the condition of interest based on the received image data;

identify other data likely to improve an accuracy of the probability and the severity;

update the probability and the severity in response to receiving at least a sub-set of the identified other data;

determine a recommended course of action for the patient based on the updated probability, the updated severity, resources of the healthcare facility, and an event guideline; and

visually present the updated probability and updated severity and the recommended of action.

26. The non-transitory computer readable storage medium of claim 25, wherein computer readable instructions further cause the processor to:

generate a control signal that controls an operation of an electronic device associated with healthcare for the patient based on the recommended course of action and the event guideline; and

control the operation of the electronic device with the control signal.

27. The non-transitory computer readable storage medium of claim 25, wherein the identified data includes imaging data.

28. The non-transitory computer readable storage medium of claim 27, wherein computer readable instructions further cause the processor to:

receive an image atlas of organ defects, wherein the determining the probability includes determining the probability and the severity of the condition of interest based on the image data and the image atlas of organ defects.

29. The non-transitory computer readable storage medium of claim 28, wherein computer readable instructions further cause the processor to:

identify other data likely to improve an accuracy of the probability and the severity of the condition of interest; and

update the probability and the severity, based on the other data to generate an updated probability and an updated severity of the condition of interest.

30. The non-transitory computer readable storage medium of claim 25, wherein the condition of interest is a congenital cardiac defect of a newborn and the at least two sensed physiologic measurements are blood oxygen concentrations, one sensed at a right foot of the newborn and the other sensed at a left hand of the newborn.