The Business Value of Reducing Medicare Complaints with Big Data Predictive Analytics
In a previous post, “Big Data Predictive Analytics in Healthcare / Medicare,” we discussed the role of big data in helping insurers address members' issues before they boiled over into complaints to Medicare (CTM).
Star ratings were set up as a way to help members make data-driven and informed decisions when enrolling in Medicare Advantage plans.
The idea is that a plan with a higher overall star rating, which is composed of a weighted average of star ratings for several measures, would be a better-performing plan. If members believed in the ratings, then plans with higher stars would exhibit higher retention and enrollment. Recent data demonstrates that there is in fact a correlation between overall star ratings and attrition. Recent data also shows that higher-rated plans are pulling ahead in terms of enrolling new members.
This makes intuitive sense. However, attrition is still an outcome. To reduce the attrition, insurers need to better understand correlations between the individual measures that contribute to the overall star rating and attrition (each measure recieves its own star rating; all the ratings are combined to reach the overall star rating). Knowing which measures to focus on in order to make a meaningful impact will enable the insurer to take active steps to reduce attrition.
CTM and attrition: a strong correlation
HealthPocket recently published a study in which it analyzed 448 Medicare Advantage contract plans and found a strong correlation between the number of complaints and attrition. It also found that the correlation between complaints and attrition was stronger than the correlation between overall star ratings and attrition. In other words, as the number of complaints fell so did the attrition levels.
HealthPocket research found a strong correlation between complaint rates and attrition rates
The business value of fewer complaints
Apigee recently performed its own analysis on data from the Centers for Medicare and Medicaid Services (CMS) to quantify the impact of the correlation between CTM and attrition.
We made two interesting discoveries.
First, by correlating the C32 rating (the star rating that represents the rate of member attrition) with the CTM star rating, we found that the number of complaints decreased as the number of members choosing to leave the plan decreased. Keep in mind that a higher number of stars for CTM implies fewer complaints and a higher number of stars for C32 implies lower attrition.
Second, every one-star increase in the attrition star rating (C32) corresponded to a 3% reduction in attrition.
Putting this together, it means that as a plan starts to make meaningful progress in reducing complaints (for example, increasing its CTM star rating by a point), it is likely to see a drop in attrition of up to 3%.
Reducing CTM can make all the difference
For Medicare Advantage contract plans with sub-four star overall ratings that are faced with zero bonus payments starting in 2015, reducing CTM is a tangible step toward increasing overall star ratings, and, consequently, improving retention, financial performance, and the ability to attract new enrollees. For plans that cross the four-star threshold, reducing CTM is a tangible step toward retaining their relative rating as other plans continually improve their performance.
The best way to reduce CTM is to prevent complaints from occurring in the first place. Apigee Insights for CTM, a HIPAA compliant product, is designed to do just that. For more information, check out the Apigee Insights for CTM datasheet.