Despite the high value of member engagement, 37% of all members and nearly 50% of pre-boomers and boomers had 0% engagement with their health plan in 2020.
Join industry experts and explore how health plans can leverage and augment existing resources to improve member engagement and satisfaction. Panelists discuss:
- Examples of real-world strategies used to engage members across all risk tiers.
- How to optimize the critical first point of contact.
- Insights around active support and advocacy for targeted rising- and high-risk members.
- How to demonstrate increased value to employers.
- Understand data and variables that deliver highly accurate predictions
- Examine key findings for models that predict the onset of type 2 diabetes, and models that predict complications of diabetes, heart failure and hypertension
- Hear an example of how a plan prioritized care management resources based on analytics
- Discover six best practices for integrating analytics into population health initiatives
Machine Learning Week
Build more models faster:
An automated machine learning pipeline to predict the onset of major chronic diseases
Speaker: Zhipeng Liu, Principal Data Scientist, Geneia
Recorded on May 25, 2021
Duration: 12 minutes
Join Zhipeng for a live review of Geneia’s automated pipeline for building machine learning models from healthcare claims data with little or no manual intervention.
- The pipeline’s conception,
- How it speeds model production by ~100 times while maintaining accuracy and interpretability, and
- An application: a series of models to predict major chronic disease onset.
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