The following is a guest post from David Costello, chief analytics officer at Verscend Technologies.
In the past, payers’ approach to data analytics was more tactical than strategic. Analytics were deployed in a siloed fashion to answer a question about a specific area of the business — an approach viewed as sufficient to drive results. Today, however, payers are putting analytics front and center, using advanced analytic methodologies to guide sound business decisions.
What is fueling the need for enterprise analytics? The major contributors are the disruptive changes happening in healthcare and the rate at which data is being produced and needs to be consumed. Patient populations are shifting dramatically, provider groups are constantly being scrutinized and their contracts with payers adjusted, and health plans are frequently being added and dropped by employers and government programs.
This marketplace volatility makes it extremely difficult for health plan CFOs and other key organizational decision-makers to be able to see far enough into the future to make sound business decisions. Powerful analytics, however, restore some of the lost predictability to their business. CFOs need to understand their costs trends. They must predict costs at the beginning of the year, and those predictions need to reflect the cost reality at the end of the year. However, without looking at enterprise-wide performance indicators and their often complex interplay, organizations risk playing “whack-a-mole” with their performance improvement efforts — in other words, they risk making decisions that positively influence one area while negatively affecting another.
Consider a Medicare Advantage health plan that focuses on both cost and quality to drive overall value. The plan has a financial revenue target to attain with a multitude of options to pursue to attain it, including care management, utilization management and coding initiatives. When selecting an approach, the plan must take into account the implications of a crucial component of Medicare Advantage revenue: the Quality Bonus Payment through the CMS star ratings system, which is designed to promote quality of care and enhanced patient experiences.
Say the plan focuses on decreasing inpatient length-of-stay through utilization management. An unintended consequence could be that it generates higher readmission rates and lower member satisfaction scores, both of which are components of star ratings. Conversely, if the plan steps up efforts to improve the member experience without a comprehensive understanding of members’ risk burden, it may improve its star ratings but generate lower net cost savings.
Enterprise-level analytics, presented through a visually meaningful executive-level dashboard, can help organizations understand how one initiative influences another, and lead to more informed investment decisions that effectively balance cost savings, revenue optimization and healthcare quality improvement.
The point, of course, is not to eliminate the department-level or functional-level measures that are currently in place, but to conceptualize a new set of integrated enterprise measures. Such measures should allow leadership to take the temperature of the organization, to understand where the business is strong and healthy and where it may have issues, and to identify which targets to chase. These measures should also help an organization understand whether, in attempting to remedy specific challenges, it might be throwing the overall organizational scorecard out of balance.
It is time for organizations to stop playing “whack-a-mole.” By leveraging enterprise-level analytics, payers can now access the right measures to make the right decisions at the right time. By granting organizational leadership the ability to effectively weigh benefits against costs, the investment in enterprise analytics is one that will truly pay off for payers, providers and — ultimately — healthcare consumers.