Aid for Medical Care Dispatch

A system for assisting with medical care dispatch comprising:

• a server including a memory and at least one processor communicatively coupled to the memory and configured to:
• receive a request for a patient to receive medical care including, at least, patient symptoms and patient personal medical history;
• receive availability information of at least one medical care provider;
• determine if the patient is experiencing a medical emergency based at least in part on the patient symptoms and the patient personal medical history;
• wherein the determining if the patient is experiencing the medical emergency includes parsing the request,
• providing one or more elements of the parsed request to a machine learning model,
• determining if the request contains at least one critical symptom which corresponds to a critical illness based on an output of the machine learning model,
• assigning a weighted risk value to one or more general symptoms based on the output of the machine learning model, and
• determining if a sum of the weighted risk values for the one or more general symptoms exceeds a threshold value;
• recommend that the patient seek emergency medical services in response to determining that the request contains at least one critical symptom or determining that the sum of the weighted risk values exceeds the threshold value;
• and
• in response to determining the request does not contain at least one critical symptom and the sum of the weighted risk values does not exceed the threshold value, recommend a medical care provider to visit the patient based at least in part on the availability information of the medical care provider.

An apparatus for assisting with medical care dispatch comprising:

• means for receiving a request for a patient to receive medical care including, at least, patient symptoms and patient personal medical history;
• means for receiving availability information of at least one medical care provider;
• means for determining if the patient is experiencing a medical emergency based at least in part on the patient symptoms and the patient personal medical history;
• wherein the determining if the patient is experiencing the medical emergency includes parsing the request,
• providing one or more elements of the parsed request to a machine learning model,
• determining if the request contains at least one critical symptom which corresponds to a critical illness based on an output of the machine learning model,
• assigning a weighted risk value to one or more general symptoms based on the output of the machine learning model, and
• determining if a sum of the weighted risk values for the one or more general symptoms exceeds a threshold value;
• means for recommending that the patient seek emergency medical services in response to determining that the request contains at least one critical symptom or determining that the sum of the weighted risk values exceeds the threshold value;
• and
• means for recommending, in response to determining the request does not contain at least one critical symptom and the sum of the weighted risk values does not exceed the threshold value, a medical care provider to visit the patient based at least in part on the availability information of the medical care provider.