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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.
 
2. A Little Risk Adjustment History
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.
 
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.
 

A Little Risk Adjustment History

By Will Stabler

First published on Feb. 9, 2017

In the first installment of this examination I looked at the fundamentals and early history of risk adjustment in healthcare. In this article I want to look at how risk was modeled in the Medicare Advantage program and by the Affordable Care Act before diving into more advanced risk adjustment concepts and some of the shortcomings and successes.

ThE Early Evolution of Risk adjustment Models

As I mentioned in the first article in this series, the original risk adjustment model used for Medicare payment determinations by the Centers for Medicare and Medicaid Services (CMS) was the Adjusted Average Per Capita Cost (AAPCC), which explained only a tiny fraction (about 1 percent) in individual variation in Medicare expenditures. It was faulted for under-compensating plans with sicker beneficiaries and those that specialized in treating certain chronic diseases or high levels of functional impairment.

In 2000, AAPCC was replaced with the Principal Inpatient Diagnostic Cost Group (PIP-DCG) risk adjustment model, The PIP-DCG model was an improvement over the AAPCC payment methodology. The model used readily available and reliable inpatient diagnostic data, but this was one of its major faults, because its predictive analysis was based only on illnesses that resulted in hospital admissions. There was little incentive for managed care organizations to keep patients healthier and reduce admissions.  The PIP-DCG model was eventually replaced after the Benefits Improvement Protection Act (BIPA 2000) began requiring ambulatory diagnoses to be included in Medicare risk adjustment.

In 2004, Hierarchical Condition Categories (HCC) were introduced in what was called the CMS-HCC model, which is the one in use today. CMS-HCC takes thousands of diagnosis codes and classifies them into 805 diagnostic groups, each representing a specified medical condition. The diagnosis groups are then combined into 189 condition categories, and then only a subset of the condition categories that best predicts Medicare inpatient and outpatient medical expenditures is employed. Then, among related condition categories, hierarchies are imposed, and a person is coded for only the most severe manifestations among related diseases.

The CMS-HCC model and its reporting requirements continue to evolve today, creating both opportunities and challenges for Medicare Advantage Organizations (MAOs) who need to keep up to speed. One of those opportunities lies in gaining an understanding and appreciation of how all of the risk adjustment, quality and care management measures can come together in the overall success equation for the organization.

I believe the most effective MAO risk adjustment programs consist of a fully integrated risk adjustment and quality program. This approach creates opportunities in a couple of ways. It not only helps streamline collection processes for both HCC-related risk adjustment measures and Healthcare Effectiveness Data and Information Set (HEDIS) quality measures, it also sets the stage for more robust analytics that can cross strategic business lines.

Risk Adjustment Helps the Affordable Care Act (ACA) Change the Landscape

Risk adjustment also plays an important role in healthcare reform. When the ACA took effect on January 1, 2014, insurers were no longer able to charge higher premiums or deny coverage for preexisting conditions, and tax credits were given to low- and middle-income people to help them afford health insurance. Risk adjustment, which served to redistribute funds from plans with lower-risk enrollees to plans with higher-risk enrollees, was one of the key factors—along with reinsurance and risk corridors—that helped spread risk throughout the markets. Risk adjustment discouraged insurers from deliberately self-selecting a disproportionate share of healthy enrollees, and encouraged plans to compete based on efficiency and value.

Reinsurance affords payment to plans with higher-cost enrollees, with the intent of protecting against premium increases by offsetting the higher expenses of those individuals. Risk corridors are designed to limit losses and gains within an acceptable range, and were meant to stabilize premiums and premium-setting during the critical initial years of the ACA.

There is considerable debate about whether the “Three R’s” of risk adjustment, reinsurance and risk corridors are having their desired effect in reforming healthcare, and all you have to do is turn on the news to gauge the current anxiety and uncertainty around the ACA. Even with all of this, one thing is sure: risk adjustment will continue to play a front-and-center role in the future of reimbursement and operations for healthcare insurers.

In the next installment, I will explore advanced risk adjustment concepts and what they mean for the future.