Data Paralysis in Health Plans: How Behavioral Science Can Lead the Way to CMS Star Rating Success

In the world of CMS Star Ratings, data is the lifeblood of success. CMS operates on data-driven insights, and health plans must match this approach to stay competitive. Beyond meeting CMS’s guidelines, robust data allows health plans to stop guessing and start making informed decisions. With millions of members under their care, even a slight improvement in how data is collected or used can lead to monumental shifts in outcomes.
But there’s a catch: the very abundance of data that drives innovation also poses a challenge. Data paralysis—a well-known phenomenon in various industries—is particularly dangerous for health plans, where failing to act can jeopardize both member outcomes and Star Ratings. A recent research by Oracle found that while 83% of business leaders consider access to data essential, 85% also struggled with “decision distress” due to the overwhelming volume of data.
Why Does Data Paralysis Happen in Health Plans?
Health plans generate a vast amount of data, far more than most industries. It should come as no surprise, then, that 82% of surveyed healthcare finance leaders believe their organizations should make better use of data. What is surprising, however, is that over 60% state that their organization uses outdated tools for this critical task. This sheer volume and the complexity of health plan operations create a perfect storm for data paralysis.
Here’s why:
- Scale: Some health plans serve millions of members, each generating countless data points over time. To be exact, a single patient generates nearly 80 megabytes annually in imaging and electronic medical record data alone, and this number grows exponentially.
- Complex Member Journeys: Each member interacts with the plan across multiple touchpoints, creating a fragmented but interconnected data trail.
- Shifting CMS Guidelines: As CMS updates its Star Rating requirements, new data becomes relevant while the weight of existing metrics shifts.
- Dynamic Member Behavior: Member preferences, needs, and feedback evolve, bringing new engagement opportunities and challenges.
- External Data Sources: Public health indexes, local data, research, and other external resources add complexity to data management.
- Medical Advancements: Emerging treatments and medical insights introduce new variables to consider.
- Performance Feedback Loops: Data on the effectiveness of engagement strategies and content adds yet another layer to analyze and optimize.
The result? Health plans are drowning in data but often lack a clear strategy for tying it all together into a coherent, actionable picture. This can lead to critical data being overlooked, misunderstood, or misused, jeopardizing operational efficiency and Star Rating success.
How Behavioral Science-Based Tools Solve Data Paralysis
Behavioral science-based tools, like those offered by MedOrion, are designed to cut through the noise of overwhelming data and focus on what matters most. These tools help health plans act with precision, transforming raw data into strategic action.
Here’s how they do it:
- Identifying Barriers to Adherence: By analyzing member behavior, these tools uncover why certain decisions are made and what stands in the way of healthier choices.
- Predicting Market Trends and CMS Needs: Advanced modeling helps health plans anticipate changes in CMS guidelines and member expectations.
- Turning Data Into Insights: Behavioral science bridges the gap between raw data and actionable insights, focusing on what drives member behavior.
- Automating Workflows and Engagement: Tools streamline processes by creating and delivering personalized communications, ensuring members receive relevant messages at exactly the right moment.
- Iterative Improvement: Real-time performance tracking allows for continuous refinement of engagement strategies, ensuring better results over time and preventing minor issues from becoming big problems.
- Balancing Broad Data With Personalization: These tools integrate large-scale data pools for group trends while zeroing in on individual behaviors for personalized action.
- Prioritizing Impactful Changes: By identifying significant opportunities, health plans can focus on strategies that will have the most significant effect on member behavior and Star Ratings success.
While the complexity of modern health data can paralyze even the most prepared plans, behavioral science-based tools offer a clear path forward. AI-powered behavioral science technology isn’t overwhelmed by data because it thrives when there’s lots of relevant information to consider—data fuels AI.
These technologies transform overwhelming information into a competitive advantage by helping health plans understand, prioritize, and act on data. The result is better member outcomes, improved operational efficiency, and stronger Star Ratings. It’s time to say goodbye to analysis paralysis and start making smarter use of this incredible resource.