Milliman PRM Analytics® offers a suite of tools that help prioritize comprehensive, coordinated care efforts that raise the level of quality and efficiency.
Patient Flow explores the connections observed between healthcare providers as they deliver care. Using traditional medical claims sources, potential connections between providers are identified when a patient visits two providers within a short period of time. The specific connections included in the results are nuanced by provider specialty to focus on plausibly causal connections (e.g. primary care physicians generate many connections while laboratories do not). The resulting web of relationships can be used to understand how patients are flowing through the healthcare system.
Conditions to Consider uses machine learning to understand the disease state of a population. Results can be used to analyze HCC risk scores or to identify patients at heightened risk of developing chronic diseases. The Point of Care Dashboard is focused for use in a point of care setting.
Conditions to Consider identifies and leverages similarities between patients within a population to ensure appropriate patient morbidity is reflected in risk-based contracts. Similarity is defined based on a patient’s demographic information, medical conditions, and prescription history. It uses collaborative filtering analytics, a common approach among online retailers that leverages these elements like purchase history to identify similar shoppers. The Financial Dashboard focuses on financial impacts.
The Care Coordinator Report provides care managers with a comprehensive view of recent patient clinical and claims activity, making management more efficient and effective. The Care Coordinator Report allows care managers to strategically select and manage patients for the best opportunity to reduce potentially avoidable cost.
The Cost Model Dashboard is a financial utilization tracking tool to identify trends in spending and utilization. The Cost Model Dashboard allows users to 'slice and dice' financial data across multiple data dimensions.