New MSSP Rule: Leveraging Analytics Best Practices to Measure and Predict ACO Performance

The Centers for Medicare & Medicaid Services (CMS) published its Medicare Shared Savings Program (MSSP) final rule in December 2018, and the final rule overhauls the MSSP and takes a new approach to transitioning providers to performance-based risk arrangements under accountable care models. A National Association of ACOs survey released in May 2018 indicated that 71 percent of the 82 ACOs that had been participating in Track 1 since 2012 or 2013 were likely to drop out of the MSSP before 2019, when they would be forced to enter a two-sided risk model (Track 1+, 2, or 3).

The proposed BASIC track would allow such long-standing Track 1 ACOs to remain in a one-sided risk model for up to an additional 18 months if they begin on July 1, 2019. Furthermore, the downside risk that these ACOs would have to take on in 2021 is less than what they would have had to assume previously. These ACOs wouldn’t have to take on risk equivalent to what is necessary in the current Track 1+ until 2023. Due to these reduced downside risk requirements, more longstanding Track 1 ACOs may be willing to continue their participation in the MSSP.

Impact on ACO Strategy

As healthcare leaders assess the impact of the new rule and the parameters on their ACO strategy, many are asking the following questions:

• What does my ACO attribution look like under the new rule?
• How is my ACO going to be defined under the glide path?
• What will be the financial impact of the rule on my current portfolio?
• How are indicators of future success based on my historical performance?
• What performance levers should we focus on to position us for sustainable success in the future?
• How can we leverage new waivers to better serve patients and maximize our bottom line?
• Should we continue down this path? Can we be successful in the long term given our market parameters?

Analytics Best Practices

The following are few best practice recommendations to leverage analytics to assess and quantify the impact of the new ruling and assist with strategic decision making.

1. Model estimated ACO beneficiary portfolio across all member constituents: The proposed rule offers new flexibility, including the ability to opt in to the prospective beneficiary assignment each year regardless of the current track the ACO is in. Whether or not your ACO decides to pursue levers such as prospective attribution or voluntary alignment, a thorough understanding of your ACO’s historical attribution is valuable. Leverage analytics to build out what future attribution compositions could look like.
2. Model your ACO potential performance in the glide path: The new rule lays out two key frameworks that allow ACOs to understand their glide path to downside risk. The first is the idea of “experienced” versus “inexperienced,” for which an ACO must understand the history of its participant providers in programs such as the Pioneer ACO, CEC model, and others. The second is the idea of “low revenue” versus “high revenue,” for which an ACO must understand the breakdown of its revenue by its participant list. The definition of the ACO by these two components defines the number of years the ACO can stay in the Basic track before having to move into the much steeper downside risk of the Enhanced track.
3. Assess historical performance to identify low- and high-performance levers: Leverage analytics to build historical performance models that identify high- and low-performance areas based on cost, quality, and risk performance.
4. Estimate how new waivers can be leveraged to serve patients and create a positive impact on the bottom line: One of the most talked about new provisions in the proposed rule is the ACO’s ability to offer beneficiary incentives to encourage medically necessary services. This, along with the increased access to telehealth and SNF waivers, prompts ACOs to identify patient segments that can benefit most from these new services. Leverage analytics to identify potential patient cohorts and calculate ROI and the impact to the bottom line of such investments.
5. Build financial models to predict future performance and ROI: Build financial models that predict net shared savings with 2% sequestration and take home (if 2.5% MSR is achieved) under various scenarios of cost, quality, and risk performance. This allows ACO leadership to develop an operational framework that must be activated to achieve financial ROI.