At OMNY Health, we believe that unlocking the full potential of healthcare data means going beyond structured fields in Electronic Health Records (EHRs). By combining EHR data with unstructured clinical notes, we can uncover insights that truly reflect the complexities of patient care—insights that are often hidden in claims or EHR data alone.
Our recent study on Inflammatory Bowel Disease (IBD) treatment patterns highlights the unique value of integrating EHR data with clinical notes. Using Large Language Models (LLMs), we analyzed over 10.6 million clinical notes from our health systems to explore why IBD patients switch or discontinue biologic treatments. This approach gave us a comprehensive, real-world view of treatment decisions. We identified 7 distinct reasons for treatment alteration across 7 biologics.
Key Findings: Uncovering the Real Reasons for Treatment Changes
While traditional EHRs track structured data like medication prescriptions and diagnoses, they often miss the “why” behind treatment decisions. Our study revealed seven key reasons why biologic treatments are altered, based on unstructured notes that provide deeper context:
- Adverse Drug Events (16-28%)
- Finance-Related Reasons (4-24%)
- Patient-Related Factors (2-9%)
- Lack of Efficacy (1-14%)
- Symptom Resolution (1-4%)
- Drug-Disease Interactions (1-3%)
- Obstetric Concerns (0-2%)
Figure 1. Reasons for Biologic Switching in IBD
| Biologic | Adverse Drug Event (%) | Drug-Disease Interaction (%) | Symptom Resolution (%) | Finance Related (%) | Patient Related (%) | Not Effective (%) | Obstetric (%) |
|---|---|---|---|---|---|---|---|
| Infliximab | 28.26 | 1.92 | 2.87 | 24.42 | 8.62 | 14.37 | 0.48 |
| Adalimumab | 26.82 | 2.87 | 1.44 | 12.93 | 8.14 | 2.87 | 1.92 |
| Golimumab | 0.96 | 0 | 0.48 | 1.44 | 0.48 | 0 | 0 |
| Certolizumab | 1.92 | 0 | 0 | 0.96 | 0 | 0 | 0 |
| Vedolizumab | 16.28 | 0.96 | 4.31 | 7.18 | 6.70 | 1.44 | 1.92 |
| Ustekinumab | 11.01 | 0.48 | 0 | 3.83 | 2.39 | 0 | 0 |
| Risankizumab | 0.96 | 0 | 0 | 0 | 0.48 | 0 | 0 |
Transforming IBD Care: From Data to Insight
By analyzing clinical notes, OMNY Health’s AI models identified reasons for treatment alterations with 94.5% accuracy. This level of insight isn’t typically captured in structured EHR fields, and it has significant implications for improving patient care.
Understanding the real-world reasons behind treatment changes is essential for refining treatment strategies, improving adherence, and ultimately achieving better patient outcomes. For IBD patients, this means more personalized care tailored to their unique circumstances—whether that’s a financial hurdle, an adverse drug reaction, or a need for a more effective therapy.
The Future of Healthcare Data: A New Era of Personalized Care
At OMNY Health, we’re excited about the future of healthcare data. By integrating EHRs with unstructured clinical notes and leveraging the power of AI, we can identify patterns that were previously overlooked. This approach not only improves our understanding of IBD treatment but also has the potential to transform how we approach care across a wide range of conditions.