Abstract: A computer-implemented process receives unstructured patient data pertaining to a patient. Furthermore, the computer-implemented process eliminates redundant words from the unstructured patient data. Additionally, the computer-implemented process generates a numerical representation of the unstructured patient data and a context-specific textual representation of the unstructured patient data. The computer-implemented process classifies, via the machine learning engine, one or more potential portions of the context-specific textual representation of the unstructured data in a risk stratification category. Additionally, the computer-implemented process determines that one or more potential corresponding portions of the numerical representation is also classified in the risk stratification category. Finally, the computer-implemented process outputs, in real-time, an enhancement to the risk stratification category based on the numerical representation also being classified in the risk stratification category.

Abstract: A patient list is provided to a medical provider. The medical provider may be prompted to review particular patients on the list or they may review these patients on their own. In any case, a patient is selected from the list and the provider determines if a medical metric associated with the patient is accurate or complete. The provider may then selectively enter self-report data concerning the accuracy or completeness of the medical metric. A provider assessment (e.g., score) is recalculated based at least in part on the self-reported data as well as the data that has already been collected. The re-calculated score may be provided to the medical plan.

Abstract: A patient list is provided to a medical provider. The medical provider may be prompted to review particular patients on the list or they may review these patients on their own. In any case, a patient is selected from the list and the provider determines if a medical metric associated with the patient is accurate or complete. The provider may then selectively enter self-report data concerning the accuracy or completeness of the medical metric. A provider assessment (e.g., score) is recalculated based at least in part on the self-reported data as well as the data that has already been collected. The re-calculated score may be provided to the medical plan.