SYSTEM AND METHOD FOR STEERING CARE PLAN ACTIONS BY DETECTING TONE, EMOTION, AND/OR HEALTH OUTCOME

1 . A method for electronically generating a care plan, the method comprising:

comparing a first data structure with a second data structure, wherein the first data structure comprises a set of health artifacts pertaining to a first condition of the patient, and the second data structure pertains to the patient and the first condition of the patient, and the second data structure comprises a subset of the set of the health artifacts;

responsive to the comparing, generating the care plan comprising another subset of the set of health artifacts; and

modifying the another subset of the set of health artifacts in the care plan based on a detected tone of the patient, a detected emotion of the patient, a medical outcome desired by a physician, or some combination thereof.

2 . The method of claim 1 , further comprising modifying the another subset of the set of the health artifacts in real-time or near real-time.

3 . The method of claim 1 , further comprising detecting the detected tone of the patient based on words spoken by the patient, text entered by the patient, or some combination thereof.

4 . The method of claim 1 , further comprising detecting the detected emotion of the patient based on words spoken by the patient, text entered by the patient, a detected facial expression of the patient, or some combination thereof.

5 . The method of claim 1 , further comprising causing the care plan including modifications to the another subset of the set of the health artifacts to be presented on a computing device.

6 . The method of claim 1 , further comprising modifying the another subset of the set of the health artifacts in the care plan based on the medical outcome desired by the physician by receiving instructions from a computing device of a physician to select a health artifact that corresponds to the medical outcome and to include the health artifact in the another subset of the set of the health artifacts.

7 . The method of claim 1 , further comprising:

generating a net promoter score based on the detected tone of the patient, the detected emotion of the patient, or both in response to the patient interacting with the care plan; and

updating a machine learning model based on the net promoter score being below a threshold value to obtain an updated machine learning model that outputs different health artifacts for subsequent patients having the condition.

8 . The method of claim 1 , further comprising including, in the care plan, action instructions pertaining to the another subset of the set of the health artifacts, wherein the action instructions are directed toward a medical personnel, the patient, or both.

9 . The method of claim 1 , further comprising:

receiving input from a computing device, wherein the input specifies a number and a type of health artifacts in the set of the health artifacts the patient selects to manage; and

selecting, based on the comparing, the another subset of the set of the health artifacts in the first data structure by selecting the another subset based on the number and the type of health artifacts specified by the patient.

10 . The method of claim 1 , wherein:

the subset of the set of the health artifacts correspond with actions already performed by the patient, and the another subset of the set of the health artifacts correspond with actions that have not yet been performed by the patient;

the comparing further comprises projecting the second data structure onto the first data structure; and

the first data structure is a knowledge graph, and the second data structure is a patient graph.

11 . A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:

compare a first data structure with a second data structure, wherein the first data structure comprises a set of health artifacts pertaining to a first condition of the patient, and the second data structure pertains to the patient and the first condition of the patient, and the second data structure comprises a subset of the set of the health artifacts;

responsive to the comparing, generate a care plan comprising another subset of the set of health artifacts; and

modify the another subset of the set of health artifacts in the care plan based on a detected tone of the patient, a detected emotion of the patient, a medical outcome desired by a physician, or some combination thereof.

12 . The computer-readable medium of claim 11 , wherein the processing device is further to modify the another subset of the set of the health artifacts in real-time or near real-time.

13 . The computer-readable medium of claim 11 , wherein the processing device is further to detect the detected tone of the patient based on words spoken by the patient, text entered by the patient, or some combination thereof.

14 . The computer-readable medium of claim 11 , wherein the processing device is further to detect the detected emotion of the patient based on words spoken by the patient, text entered by the patient, a detected facial expression of the patient, or some combination thereof.

15 . The computer-readable medium of claim 11 , wherein the processing device is further to cause the care plan including modifications to the another subset of the set of the health artifacts to be presented on a computing device.

16 . The computer-readable medium of claim 11 , wherein the processing device is further to modify the another subset of the set of the health artifacts in the care plan based on the medical outcome desired by the physician by receiving instructions from a computing device of a physician to select a health artifact that corresponds to the medical outcome and to include the health artifact in the another subset of the set of the health artifacts.

17 . The computer-readable medium of claim 1 , wherein the processing device is further to:

generate a net promoter score based on the detected tone of the patient, the detected emotion of the patient, or both in response to the patient interacting with the care plan; and

update a machine learning model based on the net promoter score being below a threshold value to obtain an updated machine learning model that outputs different health artifacts for subsequent patients having the condition.

18 . A system comprising:

A memory storing instructions;

A processing device communicatively coupled to the memory, the processing device capable of executing the instructions to:

compare a first data structure with a second data structure, wherein the first data structure comprises a set of health artifacts pertaining to a first condition of the patient, and the second data structure pertains to the patient and the first condition of the patient, and the second data structure comprises a subset of the set of the health artifacts;

responsive to the comparing, generate a care plan comprising another subset of the set of health artifacts; and

modify the another subset of the set of health artifacts in the care plan based on a detected tone of the patient, a detected emotion of the patient, a medical outcome desired by a physician, or some combination thereof.

19 . The system of claim 18 , wherein the processing device is further to:

generate a net promoter score based on the detected tone of the patient, the detected emotion of the patient, or both in response to the patient interacting with the care plan; and

update a machine learning model based on the net promoter score being below a threshold value to obtain an updated machine learning model that outputs different health artifacts for subsequent patients having the condition.

20 . The system of claim 18 , wherein the processing device is further to:

modify the another subset of the set of the health artifacts in the care plan based on the medical outcome desired by the physician by receiving instructions from a computing device of a physician to select a health artifact that corresponds to the medical outcome and to include the health artifact in the another subset of the set of the health artifacts;

detect the detected tone of the patient based on words spoken by the patient, text entered by the patient, or some combination thereof; and

detect the detected emotion of the patient based on words spoken by the patient, text entered by the patient, a detected facial expression of the patient, or some combination thereof.