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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.

We know you already have strategies implemented inside your company, the advantage that we can give you is to know how those strategies are placing you among your competitors.

Where you are among your competitors is how high your incentives can be and the stars that you can receive per domain and overall.

Convert all your strategies and hard work into high-Quality Incentives and better Star-ratings this coming measurement period.

You can begin today!

For more details about Lagrange AI visit our YouTube channel a special playlist about MLTC plans.

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1 Comment

Harold Fisher
Harold Fisher
Sep 04, 2021

Appreciate you blogging thiss

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