Machine Learning Systems For Surgery Prediction and Insurer Utilization Review

A method for performing insurer utilization review comprising:

• receiving, at an insurer system, a preauthorization request associated with a patient and a requested treatment;
• receiving, from the patient, a set of survey results;
• and
• applying at least one previously trained machine learning model to the survey results to generate a prediction output, wherein the prediction output includes a first confidence level associated with whether the patient is a surgical candidate for a surgical procedure;
• selectably denying or approving the preauthorization request based on the requested treatment and the prediction output.

A method for surgical prediction, the method comprising:

• training at least one machine learning model based on previously performed surgical procedures;
• generating a survey user interface;
• receiving, from a patient interacting with the survey user interface, a set of survey results;
• applying the at least one previously trained machine learning model to the survey results to produce a prediction output that includes (i) a first confidence level associated with whether the patient is a surgical candidate;
• and (ii) a set of second confidence levels associated with a respective set of surgical outcomes.