Abstract: Artificial Intelligence (AI) based systems and methods are disclosed for implementing patient-specific medical adherence intervention. An AI model is trained on a first set of data comprising (1) patient data defining a plurality of medical patients having respective prescribed medications and (2) intervention communication data. During a first iteration of a medication adherence session, a second set of data comprising patient data of a new or existing medical patient is received and input by the AI model to generate a medical adherence intervention prediction defining at least a preferred intervention channel specific to the new or existing medical patient. An electronic medical adherence intervention communication, is generated, and related correspondence is sent, to the new or existing medical patient based on (1) the medical adherence intervention prediction and (2) an intervention template corresponding to the preferred intervention channel.

Abstract: Artificial Intelligence (AI) based systems and methods are disclosed for implementing patient-specific medical adherence intervention. An AI model is trained on a first set of data comprising (1) patient data defining a plurality of medical patients having respective prescribed medications and (2) intervention communication data. During a first iteration of a medication adherence session, a second set of data comprising patient data of a new or existing medical patient is received and input by the AI model to generate a medical adherence intervention prediction defining at least a preferred intervention channel specific to the new or existing medical patient. An electronic medical adherence intervention communication, is generated, and related correspondence is sent, to the new or existing medical patient based on (1) the medical adherence intervention prediction and (2) an intervention template corresponding to the preferred intervention channel.