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Risk Adjustment

A Five-Part Series by Will Stabler

About This Series

I wrote this article series in five parts over two months during early 2017 when there was much discussion of what was termed “value-based care.” This series examines risk adjustment and the role it can play in such systems.

Articles in This Series

As America’s healthcare system transitions toward payment models that reward what many call value-based care, risk adjustment is playing an increasingly important role. For many health plans, it is an integral part of operations.
 
In this article I look at how risk was modeled in the Medicare Advantage program and by the ACA before diving into more advanced risk adjustment concepts.
 
Risk adjustment models and their reporting requirements continue to evolve. With this evolution, it becomes critical for us to appreciate how risk adjustment, quality and care management measures can work together for success.
 
4. Overcoming Risk Adjustment Shortfalls Requires a Wider Net
In achieving accurate risk adjustment results there are two main issues where plans fall short: not properly identifying the illness burden of the population, and not closely monitoring and managing their data submissions.
 
In risk adjustment, variation can be the enemy. It can also provide opportunities if properly managed. The point of care is one place where we can do that.
 

Overcoming Risk Adjustment Shortfalls Requires a Wider Net

By Will Stabler

First published on March 6, 2017

Since the beginning of this series I have emphasized that the goal of effective risk adjustment systems is ensuring plans are accurately and fully reimbursed for the risk inherent in their populations. For every lofty goal there are obstacles. In achieving accurate risk adjustment results there are two main issues where plans fall short: not properly identifying the illness burden of the population, and not closely monitoring and managing their data submissions.

It’s a quality and process improvement challenge, and the answer is simple, right? You just need a bigger and better system for collecting and processing data. Whether your quality improvement process is initiated with a clinical, financial, administrative, IT or leadership angle, there is always a lot of data that needs to be collected and processed, and it needs to be done without error.

Not so fast.

The People Aspect in Risk Adjustment

Yes, well-functioning data management systems are vital to your success, but in the case of efficient risk adjustment, the system has to operate in the context of its strengths and weaknesses. As in any quality improvement project in healthcare, the people aspect is the most important to improving the system. And the most important part of the people aspect is who you involve. Everything flows from there. Every “missing person” who should be involved, but who is left out of the process, becomes a lost opportunity to substantially improve risk adjustment efficiency and effectiveness.

In the previous article I touched on the need for a holistic, team approach among plans and providers for adjusting risk. This includes conducting prospective and retrospective review, complying with regulatory requirements and acquiring and managing data more efficiently.

The opportunities for improvement in not properly identifying the illness burden of the population and not closely monitoring and managing data submissions comes from all of the aforementioned clinical, financial, administrative, IT and leadership angles. These opportunities and their potential benefits also cross business lines and organizational boundaries among providers, plans and regulators. So there is no one “angle” or viewpoint from which to initiate improvement.

For health plans, creating and executing an annual risk adjustment strategy that takes aim at these two important issues is essential to improving their risk scores and reimbursements. But they can’t do it from that one viewpoint. They need partnerships. Obviously, partnering among plans and providers to accurately identify illness burden and ensure accurate data submissions can financially benefit both types of organizations directly. As a big bonus though, working together to integrate timing and processes to streamline data collection for both clinical quality reporting and encounter data reporting purposes can create opportunities for eliminating significant redundancy and rework.

Because of MACRA Quality Payment Program, Star ratings, and other current value-based reporting guidance from CMS, plans need to operate with a value-based perspective. They also need to understand the relationship between what their associated providers are reporting to CMS for quality purposes and what the plans are reporting to CMS for risk adjustment. The mechanics of all of this data collection and reporting also need to be well understood so that partnerships among them result in streamlining these increasing burdens on both plans and providers.

The strategy involves plans diving deep into their member profiles, provider performance, and condition-specific analysis to identify opportunity and tailor efficient, effective and superior outcomes. Best practices in these areas mean crossing traditional lines in order to increase provider engagement, and improve member contact.

In the next and final installment of this series, I will put this all together to look at a future forecast and alternate states for risk adjustment.