Abstract:
The disclosed computerized system and method facilitates predicting the onset of diabetes or symptom progression in those patients already suffering from the disease. The computerized system and method applies steps to segment the population by predefined member characteristics. Once segmented, the computerized system and method applies a plurality of prediction models to the segmented population data to provide a ranking of members of the population that indicates the likelihood of onset or progression of diabetes for each member.
Abstract:
The disclosed computerized system and method facilitates predicting the onset of diabetes or symptom progression in those patients already suffering from the disease. The computerized system and method applies steps to segment the population by predefined member characteristics. Once segmented, the computerized system and method applies a plurality of prediction models to the segmented population data to provide a ranking of members of the population that indicates the likelihood of onset or progression of diabetes for each member.
Abstract:
The present invention is a method of predicting the likelihood that chronic kidney disease will result in end stage renal disease requiring dialysis. The method uses various indicators comprising information specific to an individual as well as information representing characteristics of a population including demographic information, health care and prescription insurance claims, and involvement in various programs designed to improve the health of a user. The method applies a predictive algorithm to these indicators in order to derive a risk score indicating an individual's risk of dialysis.