Abstract: A system and method for reducing adverse healthcare events for an ailment. First, data is processed from at least one source. The data is fed to a predictive model to obtain a set of predicted patients. These patients are predicted to experience an adverse healthcare event for an ailment within a specified time frame. Thereafter, a message is delivered to the predicted patients. The message relates to preventing future adheres healthcare events for an ailment.

Abstract: We disclose a system (human interaction, process, software and a device) that analyzes health maintenance options emanating from expert panels in relationship to age, race/ethnicity and gender, family history and genetic susceptibility, lifestyle as well as historical information entered by the consumer, develops a personalized health maintenance plan and assists the consumer in implementing such a plan. The system allows a consumer, not necessarily a health professional, to develop a personalized plan that would otherwise require complex analysis and medical training. The system is automated and updatable, capable of learning from experience and allows potential interface with Electronic Medical Records.