Automated intervention system based on channel-agnostic intervention model

• Main Authors: Shah, Pritesh J, Bothra, Amit K, Flynn, Bradley D, Lehmuth, Christopher G
• Format: Patent
• Language: English
• Published: 28.11.2023
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS

A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with one of the principal components, selecting features of the training set most closely correlated with the principal components, performing a regression analysis on the selected features to determine a subset of the selected features that are most closely correlated with a model target, training a machine learning model with the subset, verifying the trained machine learning model with a verification set, and saving the verified trained machine learning model as the intervention model. The method includes determining an intervention expectation indicating a likelihood that the user will take action in response to an intervention being execute, determining a likelihood of a gap in care for the user, selecting and scheduling an intervention for execution based on the care gap likelihood and the intervention expectation.