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Why do you need "Lagrange AI Electoral Map report" now?

Updated: Dec 3, 2019



The Managed Long-Term Care Consumer Guide (MLTC Star Ratings) was published on March 2019. These results were reported according to a measurement period from January to June 2018.





In May, the state published the last measurement period that they performed for July-December 2018. With these results apparently, there are no MLTC star ratings based on this measurement period. But, why is it important to consider a projection using these results?


These results can tell us where the plans are not only in MLTC Star Rating, also for the Quality Incentives. How were they qualified in the last semester of 2018, and if there was a star rating, where would they have fallen or which tier they reached (i.e. money could they get)?





With these projections, we can detect if there was an improvement or if any of the plans fell into a lower rating or lower tier.


By analyzing the growth, we can make a fair prediction if any of the plans have the probability of closing doors, for example, or which plans are the ones that grew the most and even faster than the rest. Identify your competition!


After analyzing this, we can tell the plans where they should focus to improve the results of the measurements and / or the domains in the next measurement period, design their "Electoral Map".


All this information is beneficial for the plans because we are still in time to improve the measures and domains needed to be ready for the next measurement period.


With a fair prediction ahead and a clear "Electoral Map", we can help the plans to redirect efforts and resources to the correct domains and measures where they obtained bad results.


Do you want to know more? Read our blog or send me an email olivares@byteflows.com


I'll be happy to work with you!