Updated: Jul 25, 2019
The basic definition of LagrangeAI, it is an algorithm that sifts through historical data, runs thousands of simulations to guide program directors to better allocate resources.
But what does this mean for you?
We use data, different variables to calculate ratings, specifically, Quality Incentives and Star ratings for MLTC plans.
We can project ahead of time Quality Incentives points and Star-ratings using the latest results released by the state.
Why is it important to have these results ahead of time?
1. To make changes accordingly to your goals and expectations to be ready for the following measurement periods.
2. With a high level of confidence allocate your resources in an efficient way.
3. To have a full understanding of calculations processes, recent and future results on Quality Incentives and Star-ratings.
4. Identification of borderline measures results in order to take advantage of those measures and improve.
5. Identify variables that will help your plan to improve Quality Incentives and Star ratings as denominators, dropouts, and more.