Machine intelligence-based prioritization of non-emergent procedures and visits

Abstract

Embodiments of the present disclosure include systems and methods for generating a medical recommendation. Methods according to the present disclosure include receiving patient data associated with a first patient and receiving second patient data associated with a second patient. The methods further include inputting the first patient data and the second patient data into a trained machine-learning model to determine a first set of one or more risk values for the first patient and a second set of one or more risk values for the second patient. The methods further include comparing the first set of one or more risk values and the second set of one or more risk values to determine a priority for distributing care to the first patient and the second patient. In accordance with the determination that the first patient has priority, the system can generate a medical recommendation.