Patient tracking and dynamic updating of patient profile
Medical services are offered by various facilities near a patient's residence. The number of facility options continues to grow and the patients can now receive various different health care services. One example method of operation provides receiving updated patient information at a patient profile server, identifying a patient medical profile stored in memory associated with the updated patient information, and updating a patient status based on the updated patient information received, and modifying a patient schedule associated with the at least one patient status and storing the patient schedule in the patient medical profile.
1. A method, comprising:
receiving, via a server device, a first type and a second type of sensor data corresponding to a patient from a plurality of hardware sensors that communicate with the server device through a network, wherein the first type is different than the second type;
triggering a timer in response to the first type of sensor data being received;
stopping the timer when the second type of sensor data is received;
identifying a gap between when the first type of sensor data and the second type of sensor data are received;
comparing the gap to current baseline values that establish a currently expected length of the gap and when sensor data is to be received;
establishing new baseline values based on the gap and the second type of sensor data;
creating a sensor trigger pattern based on the new baseline values;
identifying behaviors of the patient based on the first type of sensor data and the sensor trigger pattern;
using the sensor trigger pattern, identifying a new symptom of the patient based on a comparison of the first type of sensor data and the second type of sensor data;
calculating selection scores for a plurality of physicians from physician information comprising portions of anatomy, pain types, chronic conditions, and emergency status of the new symptom;
identifying a physician, of the plurality of physicians, having a highest selection score above a relevancy threshold, wherein the relevancy threshold is based on a relevancy of a level of skill of the physician compared to the new symptom;
in response to the physician being identified, automatically sharing sensor data with a computing device of the physician;
receiving, from the computing device via the server device, a course of action;
modifying, by the server device, a previously scheduled activity in a schedule to a different time based on the course of action; and
triggering, via the server device, a notification to a user device that the previously scheduled activity has been modified.
2. The method of claim 1 , wherein the sensor data comprises information about at least one of:
patient consciousness, patient unconsciousness, patient location, patient eating status, patient vital sign status, and patient moving status.
3. The method of claim 1 , wherein the method comprises:
generating updated patient information based on data obtained via at least one of:
a location sensor, a movement sensor, a patient vital sign measurement sensor, and user-submitted preference information.
4. The method of claim 1 , further comprising:
receiving a plurality of updated patient information messages over an interval of time;
identifying at least one patient behavioral pattern associated with the updated patient information messages; and
modifying an already-scheduled activity within the schedule based on the at least one patient behavioral pattern.
5. The method of claim 4 , wherein the already-scheduled activity comprises at least one of:
a patient meal delivery, a patient medication being administered, a patient blood drawing session, and a patient interface session.
6. The method of claim 1 , further comprising:
retrieving a plurality of patient preferences; and
applying the plurality of patient preferences to the schedule of the patient.
7. The method of claim 6 , wherein the plurality of patient preferences include at least one of:
a meal preference, a sleep schedule, an entertainment preference, and a medication administering time.
8. A server, comprising:
a memory storing instructions; and
a processor that, when executing the instructions, is configured to:
receive a first type and a second type of sensor data corresponding to a patient from a plurality of hardware sensors that communicate with the server device through a network, wherein the first type is different than the second type,
trigger a timer in response to the first type of sensor data being received,
stop the timer when the second type of sensor data is received,
identify a gap between when the first type of sensor data and the second type of sensor data are received,
compare the gap to current baseline values that establish a currently expected length of the gap and when sensor data is to be received and;
establish new baseline values based on the gap and the second type of sensor data;
create a sensor trigger pattern based on the new baseline values;
identify behaviors of the patient based on the first type of sensor data and the sensor trigger pattern;
using the sensor trigger pattern, identifying a new symptom of the patient based on a comparison of the first type of sensor data and the second type of sensor data;
calculate selection scores for a plurality of physicians from physician information comprising portions of anatomy, pain types, chronic conditions, and emergency status of the new symptom,
identifying a physician, of the plurality of physicians, having a highest selection score above a relevancy threshold, wherein the relevancy threshold is based on a relevancy of a level of skill of the physician compared to the new symptom;
in response to the identification of a physician, automatically sharing sensor data with a computing device of the physician;
receive, from the computing device, a course of action;
modify a previously scheduled activity in a schedule to a different time based on the course of action; and
trigger transmission of a notification of the modified patient schedule to a user device.
9. The server of claim 8 , wherein the sensor data comprises information about at least one of:
patient consciousness, patient unconsciousness, patient location, patient eating status, patient vital sign status, and patient moving status.
10. The server of claim 8 , wherein the processor is further configured to:
generate the updated patient information based on data obtained via at least one of:
a location sensor, a movement sensor, a patient vital sign measurement sensor, and user-submitted preference information.
11. The server of claim 8 , wherein the processor is further configured to:
receive a plurality of updated patient information messages over an interval of time; identify at least one patient behavioral pattern associated with the plurality of updated patient information messages, and
modify the already-scheduled activity within the schedule based on the at least one patient behavioral pattern.
12. The server of claim 11 , wherein the already-scheduled activity comprises at least one of:
a patient meal delivery, a patient medication being administered, a patient blood drawing session, and a patient interface session.
13. The server of claim 8 , wherein the processor is further configured to:
retrieve a plurality of patient preferences; and
apply at least one of the patient preferences to the schedule of the patient.
14. The server of claim 13 , wherein the plurality of patient preferences include at least one of:
a meal preference, a sleep schedule, an entertainment preference, and a medication administering time.
15. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform:
receiving, via a server device, a first type and a second type of sensor data corresponding to a patient from a plurality of hardware sensors that communicate with the server device through a network, wherein the first type is different than the second type;
triggering a timer in response to the first type of sensor data being received;
stopping the timer when the second type of new-sensor data is received;
identifying a gap between when the first type of sensor data and the second type of sensor data are received;
comparing the gap to current baseline values that establish a currently expected length of the gap and when sensor data is to be received;
establishing new baseline values based on the gap and the second type of sensor data;
creating a sensor trigger pattern based on the new baseline values;
identifying behaviors of the patient based on the first type of sensor data and the sensor trigger pattern;
using the sensor trigger pattern, identifying a new symptom of the patient based on a comparison of the first type of sensor data and the second type of sensor data;
calculating selection scores for a plurality of physicians from physician information comprising portions of anatomy, pain types, chronic conditions, and emergency status of the new symptom;
identifying a physician, of the plurality of physicians, having a highest selection score above a relevancy threshold, wherein the relevancy threshold is based on a relevancy of a level of skill of the physician compared to the new symptom;
in response to the physician being identified, automatically sharing sensor data with a computing device of the physician;
receiving, from the computing device via the server device, a course of action;
modifying, by the server device, a previously scheduled activity in a schedule to a different time based on the course of action; and
triggering, via the server device, a notification to a user device that the previously scheduled activity has been modified.
16. The non-transitory computer-readable storage medium of claim 15 , wherein the sensor data comprises information about at least one of:
patient consciousness, patient unconsciousness, patient location, patient eating status, patient vital sign status, and patient moving status.
17. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further cause the processor to perform:
generating updated patient information based on data obtained via at least one of:
a location sensor, a movement sensor, a patient vital sign measurement sensor, and user-submitted preference information.
18. The non-transitory computer-readable storage medium of claim 15 , wherein the instructions further cause the processor to perform:
receiving a plurality of updated patient information messages over an interval of time;
identifying at least one patient behavioral pattern associated with the plurality of updated patient information messages; and
modifying an already-scheduled activity within the schedule based on the at least one patient behavioral pattern.
19. The non-transitory computer-readable storage medium of claim 18 , wherein the already-scheduled activity comprises at least one of:
a patient meal delivery, a patient medication being administered, a patient blood drawing session, and a patient interface session.
20. The non-transitory computer-readable storage medium of claim 15 , wherein the processor is further configured to perform:
retrieving a plurality of patient preferences; and
applying the plurality of patient preferences to the schedule of the patient,
wherein the plurality of patient preferences include at least one of:
a meal preference, a sleep schedule, an entertainment preference, and a medication administering time.