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How to survive and improve in New York: Importance of being well rated in the MLTC performance data

Updated: Jun 30, 2020

During the last 15 years, MLTC programs have increased their number of members all over the state of New York. The number of MLTC enrolees nearly tripled in the period 2010-2012, and it keeps growing. With these results, MLTC programs represent opportunities for new plans to enter the New York market.

When we analyze the data carefully, we find that the growth rate has been decreasing at a rapid pace since 2012. The enrolment growth rate for all plans in New York was high in 2012 because of the implementation of new laws in the state related to Healthcare, but it has been decreasing since.

The number of plans entering the MLTC market was almost 42% more between 2014 and 2015 than in previous years. During this time there were 74 plans, but in the latests measurement period there are only 57 plans participating in MLTC programs.

The variation on the number of plans responds to a tough market in New York. In general, around 30 plans have remained in the MLTC programs since 2014. The other plans either merge with other companies, they do not participate in this program anymore or simply closed doors.

New York is a tough market and acquiring new members is vital for plans. The competition is fierce, and surviving for a long time seems very complicated.

MLTC star-rating seems a perfect place where potential new clients can go and research information about MLTC. It is a semi-annual evaluation of the plans by New York state and all the information is public. The state condensates all the information it collects (different type of measures, survey-based or population-based measures across all plans in the MLTC program) the results are reported by the end of each semester, and there is a process where, depending on the results of these measures, a final rating is assigned to each plan (1 to 5 stars).

These results and ratings are vital for plans since all of them are evaluated on the quality of care they provide and on enrolees’ satisfaction [1].

Getting good results and being rated with the highest possible number of stars is an opportunity to improve the enrolment of plans.

MLTC: measures, domains, and stars

New York state qualifies a lot of measures, but not all of them are included in the MLTC star-rating of plans. The information considered by the state are the following: 18 measures grouped in 12 domains, these domains grouped in 4 quality areas.

Sample of measures, domains and quality areas the state of New York considers to rate plans.

Initially the state performs measurements across all plans in the MLTC program, collects the data and reports the results of these measures. For example, in the case of Influenza Vaccination measure, corresponds to the percentage of members who received an influenza vaccination in the last year or the measure Rating of Health Plan is the risk-adjusted percentage of members who rated their managed long-term care plan as good or excellent.

Obtaining a good result in this first process is vital. These results are processed statistically and then a number of stars is assigned.

Overall star-rating

Distribution of overall star rating vs. the total of stars in all the domains. The limits for the assignment of stars are defined by dashed lines: less or equal to 28 stars corresponds to 1 overall star (salmon), less or equal to 33 stars corresponds to 2 overall stars (yellow), less or equal to 38 stars corresponds to 3 overall stars (green) , less or equal to 42 stars corresponds to 4 overall star (sea green) and less or equal to 60 stars corresponds to 5 overall stars (blue). The black solid line represents the average of total stars corresponding to 36.

The maximum number of total stars is 60. But in the latest results, we notice that none of the plans reached that number. Nevertheless, the upper limit for the distribution of stars is set by one plan who obtained 51 total of stars, and the plan who sets the lowest limit obtained 24 stars.

The process

There are two different types of measurement data, based-population, and survey-based measures. The difference between these two impacts directly on the assignment of stars. In the case of population-based measures, the number of members qualifying for a specific measure is considered (denominator). Survey-based measures, on the other hand, are independent of the number of members. Both considerations are important at the moment of assigning the stars.

The statistical process the state carries on it is described in the MLTC Consumer guide [2]. Essentially it is a 7 step process, nevertheless, we are going to focus on the first 2: i) Standardizing measure scores (transforming initial results of the measures) and ii) Measure Limits.

Here, we present an example of the initial results the state releases.

These measures, correspond to two domains in the MLTC star rating process during the measurement year 2018. Plan name Statewide represents the result of the whole state, and this number will help us to standardize the measure result per plan to assign the stars.

Why your plan should care about results?

For many of the plans, we observe they got good results, but this is not enough. After the standardization of measures, we have to pay attention to where a specific plan is in comparison to the rest of the plans. For purposes of example, we will show two measures” Urinary Continence Stable or Improved (population-based measure) and Rating of Health Plan (survey-based measure).


The standardization process has to be carried out following the formulas

where for these two measures, statewide rate corresponds to 80 for Urinary Continence Stable or Improved (population-based measure) and 87 for Rating of Health Plan (survey-based measure).

The standardization process, seen it as formulas might not give us a lot of information. But when we present the information in a different fashion, we can have a better understanding of this process.

Measure Rating of Health Plan after the standardization process for all plans. The limits for the assignment of stars for this domain are represented by the dashed-lines: 1-star salmon, 2 stars yellow, 3 stars (green), 4 stars sea green and 5 stars blue. The red-solid lines represent the lower and upper limits of the distribution, and the solid-black line is the average of the standardized measure scores in this domain.

Measure Urinary Continence Stable or Improved after the standardization process for all plans. The limits for the assignment of stars for this domain are represented by the dashed-lines: 1-star salmon, 2 stars yellow, 3 stars green, 4 stars sea green and 5 stars blue. The black-solid lines represent the lower and upper limits of the distribution and the average of the standardized measure scores in this domain.

We can see a correspondence of the result against the standardization, but also the distribution of such standardization among the plans. The distribution of the standard results gives us where a specific plan is with respect to the rest of the plans. The dashed lines indicate us how "far away" or "close" a certain plan is from getting one less star or one more.

How can we help?

All these processes of information might be overwhelming, but we are here to help you to understand better MLTC ratings. Our team is immersed in knowing exactly the impact of the results in the final assignment and on your plan.

Why do you need a good result?

As we have explained, being able to get new members is vital to surviving in a tough market. Being able to improve and maintain a good rating will help you to capture new members.

Where do you need to improve and invest resources?

Most of the companies already have implemented many initiatives to improve these results. We will give you the information you need to allocate those resources in the best way, analysing trends of your plan and your competitors.

Our team has in place a recommender system that will tell you which is the best path to follow in order to improve your results, domain ratings and overall.

We can contact you today!

For more information check all the classes and information we have available for you in our YouTube channel, playlist LagrangeAI-MLTC

[1] Managed-Long-Term-Care-Performance-Data.

[2] MLTC Consumer Guide Domains

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