Our xAI Solution is designed for senior health plan leaders to support strategic decision making, providing analytics & insights on the influence of different verticals toward enrollment growth.

Why xAI?

Traditional research tools have been widely accepted till now, but the future is data-driven. While traditional market research helped identify important attributes, xAI enables the identification of the attribute significance. Simultaneously, xAI provides a numeric value to support that significance, making it an invaluable method for any payor who wants to gain a competitive edge in this highly contested market.
xAI bridges the gap between business application & mathematics – two sides that are equally important to any business. Our xAI platform collects and harmonizes data from various sources, processes it through advanced xAI models, and provides payors with actionable insights at the most granular level. xAI methodologies allow you to ignore the complexities of AI/ML algorithms and interpret results automatically, enabling businesses to make more informed strategic decisions.
The xAI program leverages multiple data sources to evaluate and determine market influence. This includes publicly available CMS files, our Provider Network repository, third-party marketing spend and performance data, and various other sources. By harmonizing this data into a single ecosystem and passing each variable through our xAI models, payers obtain a holistic view of their market and the specific actions which can optimize their product, provider, and marketing to improve plan performance.

What Do We Deliver?

Our xAI solution breaks down the enrollment influence of four verticals in each market; Product, Network, Marketing, and Brand. Payors can choose to focus attention on any verticals independently or combined by diving deeper into the respective vertical reports to uncover additional insights.

How Does It Work?

Machine learning algorithms have been historically labeled “black box” models because of their inscrutable inner workings. However, what makes these traditional models accurate is also what makes their predictions difficult to understand: complexities in the data and variable impact by market. xAI assists data scientists by decoding and interpreting these results, hence bridging the gap between business application and mathematics.

In short, the xAI program is an advanced correlation analysis that collects and processes data, generating in-depth market analysis not uncovered by standard research or models. The result is actionable intelligence to enable business optimization.

Executive Level

The ability to quickly analyze a market to identify the strength of position and opportunities for growth is vital to any business. The xAI Executive Scorecard provides an overview of each market on the competitive ranking for each organization. The ranked measures include Product Design, Provider Network, Marketing Analytics, Brand Influence, and a cumulative HealthWorksAI Score. Results can also be segmented for more refined views for various cuts, including $0 Premium vs non-$0 Premium, HMO vs PPO, and more.

Vertical Breakdown

In the second level of analysis, more profound insights for each vertical, those that determined the overall score, are accessed through the independent scorecard reports of Product, Network, and Marketing. These reports not only provide analysis at a more granular level (PBP/Network/Marketing Channel), but they also explain how the various attributes associated with each vertical are categorized and ranked by significance. For example, identifying the benefits with the highest statistical correlation to enrollment gain, determining which NPI’s are most impactful when expanding a network, or identifying the most appropriate marketing channel spend based on successful campaigns of competitors.

Attribute Deep Dive & Simulation

The deepest level of granularity in the xAI analysis further defines the minor nuances and impact of the significant factors in each market. The attribute deep dive is unique to each payor, based on organizational focus and competitive opportunity in their present or expansion markets. This custom analysis measures the sub-factors influencing the significance of each attribute and allows for the simulation of predicted enrollment change after proposed changes to vertical attributes. Examples include:

  • Determining the copay for a specific benefit based on price elasticity.
  • Simulating enrollment change with the introduction of new supplemental benefits.
  • Understanding the impact on network marketability with the addition of a new hospital system.

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