optimizing healthcare analytics: how to choose the right predictive model
Healthcare providers understand that predictive analytics can resolve issues such as reducing patient readmissions and mortality rates. However, choosing which predictive model works best for these situations can be complicated. By using the correct predictive tool, healthcare companies can improve the accuracy with which they analyze their data.
Download EXL's white paper to learn
The strengths and weaknesses of different predictive models
How these models stack up to each other in a comparative case study
- Ways to achieve greater accuracy in targeting with predictive analytics
The shift from volume-driven treatment to value-based care has made predictive analytics essential to healthcare providers. Find out how to leverage analytics to drive insight in EXL’s white paper Optimizing Healthcare Analytics: How to choose the right predictive model.