Improved Risk Adjustment Solution Can Increase Exchange Market’s Stability

Improved Risk Adjustment Solution Can Increase Exchange Market’s Stability

Risk Adjustment is an Affordable Care Act (ACA) provision designed to eradicate the impact of risk choices on premiums. It requires federal/state exchanges to transfer funds from insurance coverage with healthier registrants to the sicker registrants.

The Risk Adjustment Solution is meant to encourage health insurance issuers who offer a variety of benefits to enrollees at an affordable premium. A precise and accurate risk adaptation model enables health plans to compete with cost, quality, and health management plans in accordance with suitable compensation.

In 2014, the ACA introduced three premium risk stabilization programs to assist insurance plans to stabilize themselves in the health insurance market. The three programs, generally referred to as 3Rs, have been designed to offset variables influencing the quality of care and population size enrolled in the insurance market.

1. Reinsurance It provides coverage to insurers that register people with high costs.

2. Risk Corridors It limits losses and profits over an allowed range.

3.Risk Adjustment It redistributes funding from plans with lower-risk registrants to those plans with higher-risk registrants.

The existing risk adjustment solution model used in solo practice and small group markets has numerous limitations in terms of accuracy, for instance:  The exchange population differs from the big employer population considered for the model The present risk adjustment solution is based on data from self-funded, big corporate employer claims. This big employer market is often different from the exchange markets in terms of demography and health condition. The exchange population tends to move in and out of coverage in a year. These variations indicate that the usage and cost projections of registrants in each market will deviate from the model’s projections resulting in ambiguous transfers across plans.

Solution: The predictive accuracy can be achieved by exploring techniques to estimate a model based on commercial population and exchange groups.  The diseases added in the model to indicate cost do not represent the population's health requirements.

The model typically uses diagnostic codes to generate risk scores instead of additional healthcare data utilization, for instance, drug prescription for diagnosis or to determine disease severity. Thus, plans for high-cost medication enrollees remain consistently undercompensated.

Solution: Reassessment of indicators for ailments added in the model.  The model underpays for part-time registrants Many people are registered for a short span of time in exchange for health plans, and often cost substantially more than their risk scores

suggest. The HCC Coding conditions are neglected while generating risk scores of such exchange plans.

Solution: Increasing options for such registrants to generate one or more risk scores could lead to payments accuracy in exchange markets.