Behavioral Health Has A Data Problem. Health Plans Are Sitting On The Solution

Health plans have been pouring resources into data analytics for years. They’ve mapped chronic disease trends, pored over prescription data, and chased cost-savings across every corner of the healthcare system. But when it comes to behavioral health, those same health plans are often flying blind. 

It’s not that the data isn’t there. Health plans are already sitting on years of claims, pharmacy, and clinical data that can tell them who’s at risk for serious behavioral health disorders, who’s currently being treated for them, and what actually works. The problem is how health plans are looking at all that data.  

Or, more importantly, what it’s trying to tell them.

Behavioral health has long been an afterthought of the healthcare system. It’s been carved out, reorganized, and deprioritized over decades. Now, the U.S. finds itself in the midst of a behavioral health crisis that even massive pandemic-era investments in mental health access couldn’t curb. It’s a crisis that’s particularly acute among young people, and one that doesn’t seem to be going away. 

That’s because access on its own isn’t enough to get people the care they need. Health plans have plenty of programs and benefits designed specifically to address the mounting behavioral health crisis. What they have historically lacked is the ability to identify, measure, and interpret the data from those programs across populations. Without that, health plans are stuck in neutral in the face of an ongoing crisis that’s costing them and their members dearly. 

In 2024 alone, behavioral health conditions drove an estimated $3.5 billion in excess ED utilization. That’s not a sign of a functional system. It’s a symptom of a data interpretation problem. 

This isn’t a new healthcare problem

Two decades ago, pharmaceutical companies were facing a similar challenge: they had products that could help specific patient groups, but they were relying almost entirely on doctors to connect the dots. The consumer wasn’t even part of the equation – sales reps were the primary messengers, delivering drug information to clinicians in the hopes that prescriptions would trickle down. 

When regulations shifted, pharma pivoted. The industry embraced a direct-to-consumer model that centered on understanding precisely who needed treatment, exactly where they were in their journey, and what message would motivate them to seek a script. 

Today, a newly-diagnosed patient with rheumatoid arthritis sees a different message than someone who has been managing the condition for 30 years. This sophisticated segmentation model has transformed how healthcare organizations engage people. The goal is no longer broadening access. It’s to drive action.  

Health plans can bring that same approach and precision to understanding behavioral health trends in their member populations responsibly and ethically – not to market, but to help their members engage with services they already have access to, through benefits they’re already paying for. 

Health plans have all the data necessary to understand which members need help, when, and which programs or benefits are best suited to meet member needs. They don’t need any more data. They need ways to extrapolate, arrange, and interpret it. They need ways to turn the data they already have from claims, charts, prescriptions, wearables, and other sources into intelligence. Members already expect their plan to analyze their data for medication interactions or refill reminders. The same expectation extends to behavioral health.

Think of it this way: every other aspect of health has been rigorously analyzed, to the point where complications, hospitalizations, and costs can be predicted accurately. But when it comes to behavioral health conditions, most health plans and providers stop analyzing after the screening stage. 

For example, if a diabetes management program had high enrollment by only a 50% medication adherence rate with steadily climbing emergency department visits, wouldn’t that signal an underlying or undetected social determinant or behavioral issue? Depression is a hidden driver of non-compliance, whereas an analytics engine, powered by AI, could identify risk cohorts and pool data to better understand blind spots over time.

Additionally, an annual depression screening completion rate, for example, is often considered a measure of success. But mental health isn’t an annual phenomenon. It’s dynamic, fluid, prone to fluctuate based on social and environmental factors.

I could get a screening today and raise no red flags with my health plan or primary care doctor. My world could turn upside down tomorrow, and neither would have a clue. This is happening right now, in communities across the country; people are developing depression days, weeks, or months after their last screening, and the healthcare system has no idea. 

But people share their healthcare information constantly, in ways that go far beyond questionnaires. We log our moods and lifestyles with apps, we wear devices that track our health and fitness metrics, we have doctor’s appointments outside of our annual physicals. All of that data, stitched together, presents a full picture – or at least, full enough for health plans to connect the dots. 

The opportunity before health plans now isn’t about gathering more data. Rather, it’s about applying a strategic lens to the data they already have. 

Behavioral health intelligence is the missing layer in the analytics stack – one that makes it possible to see past annual screenings, intermittent hospitalizations, and one-off therapy appointments to surface the patterns that predict risk, reveal program gaps, and show what interventions actually work. Whether powered by traditional population health analytics, predictive modeling, or AI and machine learning, the tools to do this are readily available. What’s needed now is a willingness to apply them. 

The stakes are too high for behavioral health analytics to remain a black box. It’s time for health plans to begin treating it with the same analytical discipline as physical health.

Photo: pixelliebe, Getty Images

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.