Using Predictive and Prescriptive Analytics to Manage the Health Impacts and Cost of Chronic Conditions

The pandemic has underscored the importance of care management for chronically-ill patients. It is widely known that those with chronic conditions are at increased risk of severe illness or mortality if they are to contract Covid-19. Moreover, there is now mounting evidence that many individuals have deferred care during the pandemic, with studies showing that more than 75 percent of adults who have delayed or foregone care had one or more chronic conditions.  Learn how using leading-edge data science and a variety of artificial intelligence (AI) techniques is enabling health plans and their value-based provider partners to identify, stratify, and predict high-cost patients and conditions to target timely interventions to high-risk, rising-risk, and the most impactable members.

• Learn how a series of analytic models were designed to manage the health impacts and costs of chronic conditions
• Understand the type of data used in the models and important variables that led to highly accurate predictions
• Examine the key findings surrounding predictive models for many common and costly chronic conditions, including predicting the onset of type 2 diabetes, type 2 diabetes-related complications, complications of heart failure, and complications of hypertension
• Hear case examples of how plans prioritized care management resources based on the predictive models
• Discover best practices for integrating analytics into population health initiatives, including involving clinicians in model creation, integrating data and insights into a care management platform, using models to determine gaps in care management offerings, and more