Abstract: In some examples, structured and unstructured data is analyzed to determine whether a user is at risk for a certain condition. The results of this analysis can be included in a risk assessment. In some examples, structured and unstructured data is analyzed to determine whether a particular event has taken place. Once detection of occurrence of the event has taken place, a notification is generated that a correct recipient is identified. In addition, it is determined if and how the notification should be escalated.

Abstract: In some examples, systems, methods, and devices are described that generate contextual suggestions for patients. Generation of the contextual suggestions is triggered by certain events performed by a medical professional with respect to a patient (e.g., updating a patient record). The contextual suggestions are related to addressing health conditions of the patient and represent tasks or considerations which the medical professional should be made aware. The contextual suggestions are generated in a way that is considerate of patient context, medical professional context, and contexts of similar patients. The contextual suggestions can be presented to the medical professional for selection and execution.

Abstract: In some examples, systems, methods, and devices are described that generate contextual suggestions for patients. Generation of the contextual suggestions is triggered by certain events performed by a medical professional with respect to a patient (e.g., updating a patient record). The contextual suggestions are related to addressing health conditions of the patient and represent tasks or considerations which the medical professional should be made aware. The contextual suggestions are generated in a way that is considerate of patient context, medical professional context, and contexts of similar patients. The contextual suggestions can be presented to the medical professional for selection and execution.

Abstract: In some examples, systems, methods, and devices are described that generate exposure evaluations for dependent users. First data associated with a user and including objective values is accessed. Second data associated with the user and including subjective observations is accessed. The first data and the second data is used as input to evaluate one or more evaluation rules. Based on the evaluation, an exposure evaluation is generated. A notification is generated to include the exposure evaluation, which is provided to one or more destination entities.