How Can Electronic Health Records Help Improve Mental Healthcare?

What you need to know

• Electronic health records contain valuable real-world data that can help improve mental healthcare delivery and outcomes
• Advanced analysis of health records from over 560,000 patients reveals important patterns in mental health treatment
• Natural language processing helps extract meaningful clinical insights from doctors’ written notes

The Power of Real-World Healthcare Data

Imagine having access to detailed health information from hundreds of thousands of people receiving mental healthcare - not from controlled research studies, but from real-world clinical settings. What could we learn about what treatments work best for different conditions? What patterns might emerge about why some people respond better to certain approaches than others?

This is now possible through the careful analysis of electronic health records (EHRs). While traditional clinical trials remain important, they typically include small, carefully selected groups of patients followed for short periods. In contrast, EHR data reflects the messy reality of how mental healthcare actually happens in the real world.

A New Way to Learn from Clinical Experience

The NeuroBlu platform described in this paper provides secure access to anonymous mental health records from over 560,000 patients across 25 U.S. healthcare providers spanning 21 years. This includes information about diagnoses, medications, symptoms, and outcomes.

What makes this particularly powerful is the use of natural language processing (NLP) - computer algorithms that can analyze doctors’ written notes to extract meaningful clinical information. Rather than just relying on checkbox data, NLP allows researchers to tap into the rich observations that clinicians document in their narrative notes.

Key Findings from the Data

Analysis of this large dataset has already revealed several important insights:

• People with substance use disorders (28.1% of patients) are at higher risk for psychiatric hospitalization and don’t respond as well to antidepressants
• Depression with anxiety or substance use is harder to treat than depression alone
• Adding antipsychotic medications to antidepressants is more common in severe depression
• Different mental health conditions show distinct patterns in how symptoms manifest and respond to treatment

The platform also enables development of tools to predict treatment response and support clinical decision-making.

Technology Meets Clinical Care

The technical infrastructure behind NeuroBlu illustrates how modern computing can be applied to healthcare while maintaining patient privacy. All identifying information is removed before analysis. The data is stored securely in the cloud, allowing approved researchers to analyze it through a web interface without ever accessing the raw records.

This creates a “trusted research environment” where the valuable insights from clinical experience can be extracted while protecting patient confidentiality. The platform includes both user-friendly visualization tools and advanced statistical capabilities.

What This Means for You

For patients and families, this kind of large-scale healthcare data analysis could lead to:

• More personalized treatment recommendations based on what has worked for similar patients
• Better prediction of which approaches are most likely to help specific individuals
• Earlier identification of people at risk for serious mental health issues
• More efficient matching of patients to the most appropriate care

While the system currently focuses on research, the goal is to eventually incorporate these insights directly into clinical care to help doctors and patients make more informed decisions about treatment.

Conclusions

• Real-world healthcare data analysis represents a powerful new tool for improving mental health treatment
• Combining traditional clinical data with analysis of doctors’ narrative notes provides richer insights
• The ultimate goal is to translate these research findings into better care for individual patients