Limited insight into a health plan’s performance data and projections led to sub-optimal resource allocation and strategic planning, which affected the plan’s quality measures and put its star rating at risk.
Investigate: ZS helped the health plan collect, coordinate and cleanse four years of performance data across multiple contracts.
Predict: ZS worked with the health plan to develop and validate an AI-driven model that could forecast any adjustment in the plan’s full-year star rating using partial-year data.
Intervene: ZS identified root causes that were impacting the health plan’s key quality measures, then created a set of plans that aimed to improve performance in these specific measures and recommended priority areas for investment.
Better insight: Pilot programs for high-impact, low-effort interventions allow health plans to understand the impact on member access and experience.
Improved forecasting: The health plan achieved 98% accuracy for more than 10 HEDIS and PDE measures forecast under the new model.
Influence: The project established buy-in for investing in the plan’s data landscape and increased access to advanced analytical tools to monitor the program.
Risk management: Sophisticated models enabled the organization to assess the financial risk of future changes that could influence star ratings.
Increased revenue potential: By assessing root causes at the level of specific CMS quality measures and providing road maps to address these causes, ZS positioned the client to improve its star rating and ultimately its revenue potential.