Tag Archives: Jason Petroske

The “Rxisk” of adjustments in 2018 ACA risk adjustment

The Centers for Medicare and Medicaid Services (CMS) is adding a new prescription drug category classification system to the 2018 risk adjustment model. Starting in 2018, a condition will be identified through a Hierarchical Condition Category with associated medical diagnosis codes, a prescribed medication, or both—each one affecting the final risk member score differently. This paper by Milliman consultants approximates the likely CMS mapping based on the publicly available information to date.

Maximize ACA risk adjustment with EDGE server action plan

Effective management of information entered into an External Data Gathering Environment (EDGE) server may save health plans millions of dollars in risk adjustment transfer payments. In this paper, Milliman’s Jason Petroske and Alan Vandagriff outline best practices that issuers should consider as part of their annual EDGE server submission cycles to maximize risk adjustment results.

Here’s an excerpt:

Complete and accurate data is a critical element in capturing—and, more importantly, in receiving compensation for—a health plan’s true level of risk. While navigating the first two years of EDGE submissions, we have mapped out a comprehensive action plan focused on three main areas that any issuer can integrate into its data management framework:

Establish a robust review and reconciliation process: Create a continuous process for reviewing and reconciling EDGE submissions to internal data sources. Identify key metrics for data completeness and use the test environment to ensure each EDGE submission passes these standards before finalizing in production.

Prioritize error corrections: Not all errors are created equal, so have a strategic plan for correcting errors and improving data quality. Understand the economics of risk adjustment to help effectively deploy and allocate resources.

Track data quality and establish benchmarks: Track and benchmark data quality and submission results over time. Look for patterns in errors or outliers from prior submissions as these can be signals of systemic weaknesses in the overall data management process.

Evaluating risk adjustment transfer payments

Risk adjustment transfer payments continue to have financial implications on insurers in the commercial individual and small group marketplaces. In this analysis, Milliman consultants provide an overview of 2015 transfer payments, comparing them against 2014 results. The authors also explore the following conclusions from their report.

• Total risk adjustment transfer payments at the national level remained at about 10% of premium in the individual market and 6% of premium in the small group market.
• Roughly one in four issuers offering plans in a given state or market in both 2014 and 2015 switched between payer and receiver status.
• Statewide risk scores rose more year-over-year than the movements in market demographics and average plan benefit richness would have suggested.
• Where available, the interim risk adjustment report did not provide a reliable indication of the ultimate value of the 2015 risk score.

Does risk adjustment affect ACA profit volatility?

Risk adjustment may influence insurers’ profitability in the health insurance marketplace, and the volatility of profit results may be highly linked to insurers’ plan size. In this analysis, Milliman consultants examine how risk adjustment might influence profitability patterns and whether those patterns change with the size of a health plan. The authors also address main concepts behind two sets of proposals that have emerged to improve the risk adjustment program, with the aim of reducing financial volatility.

When adverse selection isn’t: Which members are likely to be profitable (or not) in markets regulated by the ACA

What will happen to a health plan that enrolls a different mix of members in 2014 than anticipated? Beginning in 2014, when major provisions of the Patient Protection and Affordable Care Act (ACA) become effective, including guaranteed issue and community rating, many people with poorer health will have the opportunity to purchase insurance—some for the first time—and at premium rates the same as those charged to their healthier peers. Insurers are wary of the unknown financial impacts inherent in this market shift.

To address this risk, the federal government introduced the “three Rs” to help insulate insurers. In this paper, Jason Petroske and Jason Siegel explore the net impact of these programs, in particular risk adjustment, when members of varying characteristics are enrolled in a plan. The authors investigate the financial impact to a health plan of enrolling a membership base with different demographic and morbidity characteristics than those that were anticipated when developing rates.