Abstract: Disclosed herein are systems, methods, and machine readable media for implementing a service for facilitating user engagement and behavior to improve health outcomes. In many populations associated with a shared health insurance plan or Health Maintenance Organization (HMO), members may become less healthy over time, or may remain at a suboptimal state of health. Individual members and the population as a whole may be nudged toward improved health outcomes with various types of interventions. Described herein are embodiments of systems and methods for associating appropriate interventions with populations who are likely to benefit from them, resulting in improved health outcomes for the group.

Abstract: A method for updating a forecast model is disclosed. The forecast model includes parameters that receives collected data representing historical dependent and causal data. The collected data are in different units of measure from one another. Based on the collected data, the forecast model is applied to determine a total error value from a calculation performed on the parameters in the forecast model. To update the forecast model, additional parameters are added, existing parameters are modified, or parameters are removed from the forecast model to determine a modified total error value. The modified total error value is then compared to the original total error value. The parameters are also converted to normalized values to be in a common unit of measure to facilitate the application of the forecast model to determine a total error value.

Abstract: A method for updating a forecast model is disclosed. The forecast model includes parameters that receives collected data representing historical dependent and causal data. The collected data are in different units of measure from one another. Based on the collected data, the forecast model is applied to determine a total error value from a calculation performed on the parameters in the forecast model. To update the forecast model, additional parameters are added, existing parameters are modified, or parameters are removed from the forecast model to determine a modified total error value. The modified total error value is then compared to the original total error value. The parameters are also converted to normalized values to be in a common unit of measure to facilitate the application of the forecast model to determine a total error value.