Abstract: An automated patient-management system for efficiently reporting patient information to clinicians, and a method of operation thereof is described. The system automatically collects and analyzes historic-physiologic data indicative of a patient's health from a myriad of sources. Based on the historic-physiologic data, the system automatically generates a health-risk score indicative of whether a patient will experience a serious-medical event in the near future (e.g., a predetermined time interval). The system uses a processing model that may rely on Hierarchical-Temporal Memory techniques and other models, for extracting and analyzing patient data. The system also generates an integrated synopsis of a patient's health condition, including the health-risk score. The synopsis is then presented (served) to a clinician in an organized, simplified, and effective manner via a client-side user interface.

Abstract: Methods and systems for active patient management are provided. A central system can receive data about one or more patients from sources such as implantable medical devices within the patient, healthcare providers, pharmacies, and insurance entities. The system may automatically identify anomalous data or trends in the data, and automatically alert a healthcare provider associated with the patient. The alert may provide additional contextual information related to the alert data. Thus, the healthcare provider need not manually analyze patient data on a regular basis. The system also may perform predictive modeling to identify when a patient may need additional healthcare.