OMNY Health, the leading healthcare ecosystem for compliant real-world data insights at scale, today announced it has become the first electronic health record (EHR) company to offer its real world data (RWD) dataset on Datavant Connect powered by AWS Clean Rooms through its Lighthouse Partner Program.
The pharmaceutical industry is rapidly embracing real-world evidence (RWE) to accelerate drug development and regulatory approvals. External control arms (ECAs), built using real-world data (RWD), are transforming clinical trials by offering an alternative to traditional placebo groups. By reducing recruitment burdens, increasing statistical power, and aligning with regulatory expectations, ECAs have the potential to redefine late-stage drug development.
OMNY Health is at the forefront of this shift, providing research-ready EHR datasets that seamlessly integrate into clinical trial designs. Our recent study demonstrates how EHR-derived control arms can effectively mirror traditional placebo groups, offering a robust and scalable solution for regulatory submissions.
To evaluate the feasibility of an ECA in a late-stage clinical trial, OMNY Health leveraged six specialty dermatology networks and six integrated delivery networks (2017-2024) from its real-world data platform. The study constructed an ECA for the Phase 3 POETYK PSO-1 trial, which evaluated deucravacitinib versus placebo for moderate-to-severe plaque psoriasis.
The ECA was built using precise patient selection criteria that ensured alignment with the trial’s placebo group. Patients were included if they met physician global assessment (PGA) score eligibility, ensuring comparable disease severity. Baseline treatment history was carefully controlled, and topical medication use was restricted prior to the index severity visit to reflect treatment-naïve status. By tracking patients longitudinally, we assessed week-16 outcomes using structured EHR data, mirroring the trial’s methodology.
While some demographic differences were observed—ECA patients were older, more likely to be female, and had a different racial distribution compared to the placebo arm—the disease severity and baseline clinical characteristics were well matched.
The real-world ECA demonstrated a significantly higher response rate compared to the traditional placebo arm, reinforcing its validity as a comparator.
One notable finding was racial disparities in achieving the primary endpoint within the ECA, suggesting that differences in patient demographics between the ECA and placebo group may have contributed to the observed differences in response rates. Further research could explore adjustments such as population weighting to refine ECA comparability even further.
These results confirm that OMNY Health’s real-world dataset can be used to generate ECAs that replicate clinical trial placebo groups, while also revealing new insights into patient diversity, treatment history, and long-term outcomes.
Traditional clinical trials face high recruitment costs, ethical concerns over placebo use, and long enrollment timelines. OMNY Health helps to eliminate these barriers by offering regulatory-grade EHR data that aligns with clinical trial endpoints.
With 85M+ patients, 1B+ encounters, and 4B+ unstructured clinical notes, our dataset provides a scalable and statistically powerful alternative to traditional control groups. By incorporating structured disease severity scores, prescribing patterns, and physician-reported outcomes, our ECAs offer more efficient and cost-effective alternative to prospectively collected placebo data.
Beyond reducing recruitment time, OMNY Health’s real-world ECAs improve trial generalizability, capturing diverse patient populations often underrepresented in traditional studies. As the FDA increasingly endorses RWD for regulatory decision-making, the ability to integrate ECA’s into pivotal trials is becoming a competitive advantage for pharmaceutical companies.
Pruritus, or chronic itch, is one of the most common symptoms reported in dermatology, yet real-world treatment patterns remain poorly characterized. While topical therapies are typically the first-line approach, severe cases often require systemic interventions. But how do clinicians determine when to escalate therapy? OMNY Health conducted a real-world evidence study leveraging research-ready EHR data from six specialty dermatology networks to examine how itch intensity, a critical but underutilized measure, influences real-world prescribing patterns. By integrating structured and unstructured clinical data, OMNY provides new insights into the relationship between symptom severity and treatment decisions.
While pruritus is a symptom, its severity can significantly impact quality of life and treatment choices. This study focused on patients with a documented 10-point itch intensity score, captured through physician assessments and patient-reported outcomes. The dataset included 7,330 patients with 8,115 encounters, capturing the following structured severity measures:
By leveraging EHR-derived severity assessments, the study provides a more granular understanding of how treatment decisions align with symptom burden.
Findings revealed a clear relationship between itch severity and systemic therapy use, while topical therapies were prescribed at consistent rates across all levels of severity.
The increasing use of sedative antihistamines in severe cases suggests a reliance on limited systemic options, leaving a gap in alternative therapies for patients with refractory pruritus.
The underutilization of structured itch severity scores in real-world studies has historically limited the ability to quantify treatment impact. Our findings reinforce why itch intensity should be a standard measure in both clinical decision-making and drug development. For clinicians, understanding real-world prescribing trends tied to symptom severity can optimize treatment pathways and inform escalation decisions. For researchers and trial sponsors, itch intensity scores provide an opportunity to refine patient segmentation, support cohort identification, and assess real-world treatment responses. For drug developers, the limited use of alternative systemic therapies highlights a need for novel treatments, particularly for patients with refractory pruritus.
This EHR-based study provides new insights into how structured itch intensity measures correlate with real-world prescribing behavior. By integrating structured severity assessments with prescribing data, OMNY Health’s research-ready datasets offer a unique lens into treatment trends, patient stratification, and disease burden.
Every patient’s story extends beyond structured medical records. Social determinants of health (SDoH), such as economic insecurity, often go unrecorded in traditional coding systems, leaving critical gaps in understanding patient needs. A recent study utilizing OMNY Health’s real-world data platform showcases the power of unstructured clinical notes in identifying financial hardship among psoriasis patients—insights that structured EHR data alone did not capture.
The OMNY Health Platform was used to access electronic health record (EHR) data for patients with International Classification of Diseases, Tenth Revision (ICD-10) codes related to economic insecurity. These codes, outlined in Table 1, include classifications for financial instability, lack of adequate food and safe drinking water, extreme poverty, low income, and material hardship. However, structured data alone failed to capture the full scope of patient struggles.
By applying natural language processing (NLP) to unstructured clinical notes from five specialty dermatology networks (2017-2019), researchers uncovered 686 patients with financial hardship indicators that would have otherwise gone undetected. These were patients whose struggles—such as insurance challenges, difficulty affording medications, and financial stress impacting care decisions—were only documented in free-text notes, never coded in structured fields.
At a probability threshold of 0.91, the model achieved a 91% precision rate, though manual review found that 60% of flagged sentences were true positives. This highlights the need for continued refinement while demonstrating how clinical notes provide deeper, more patient-centric insights than structured data alone.
Traditional structured EHR data often fails to capture the full scope of social determinants of health (SDoH), creating critical blind spots in patient care. Many healthcare decisions—such as delaying treatments, switching medications, or discontinuing care altogether—are influenced by social and financial challenges that remain undocumented in structured records.
For example, economic insecurity is a major yet often invisible factor shaping healthcare journeys. By analyzing clinical notes, researchers have identified patients facing financial hardship that was not reflected in coded data, underscoring the need for a more comprehensive approach to SDoH research. But financial instability is just one piece of a much larger puzzle.
OMNY Health’s dataset goes beyond economic hardship, capturing a wide range of social determinants that impact health outcomes, including:
By incorporating unstructured clinical notes into SDoH research, OMNY Health’s data helps:
As healthcare organizations seek to advance health equity, leveraging unstructured data provides a more complete view of patient experiences—ensuring that social determinants are not just acknowledged, but actively addressed in care strategies and policy development.
This study is just the beginning. Researchers are expanding NLP-driven approaches to explore other SDoH domains, including housing instability and undereducation. With continued model refinement, these insights will help healthcare providers, researchers, and policymakers gain a more complete understanding of patient experiences beyond structured EHR limitations.
As healthcare shifts toward patient-centered solutions, unstructured clinical notes will be key to closing critical data gaps. The ability to capture these hidden patient struggles has the potential to transform care delivery and research.
In dermatology, real-world data plays a crucial role in understanding disease progression and optimizing treatment strategies. Actinic keratosis (AK), a common precancerous skin condition, requires tailored management approaches based on disease severity. OMNY Health’s vast dermatology dataset provides new insights into AK treatment patterns by leveraging structured electronic health records, including lesion count and patient-reported pain scores.
One of the unique aspects of OMNY Health’s dataset is the inclusion of real-world AK disease activity measures. Traditionally, treatment decisions for AK have been guided by lesion count, but OMNY’s data also incorporates pain scores using the 0-10 Visual Analogue Scale (VAS). This dual-measure approach provides a more comprehensive understanding of how AK severity impacts treatment decisions.
Analyzing data from six specialty dermatology networks within the OMNY Health platform (2017-2024), researchers examined how lesion count and pain VAS influence real-world treatment strategies. The study included 334,410 patients with 704,665 assessments, highlighting distinct trends in treatment selection.
Key findings include:
These findings emphasize the value of structured EHR measures in refining dermatological treatment strategies. By incorporating both lesion count and pain VAS, OMNY Health’s dataset enables providers and researchers to:
OMNY Health continues to enhance its dermatology RWD offerings by integrating unstructured clinical notes and refining disease activity metrics. Future analyses could leverage clinical notes to provide richer insights into treatment rationale and long-term outcomes.
As dermatology evolves, real-world evidence will be essential in bridging the gap between clinical research and everyday patient care. OMNY Health’s commitment to data-driven insights ensures that providers have access to the most comprehensive, research-ready EHR datasets to inform their decisions.
We at OMNY Health are thrilled to announce that the OMNY Health Platform has successfully achieved HITRUST e1 Certification, a landmark achievement in our ongoing commitment to foundational cybersecurity controls and information risk management in healthcare.
HITRUST e1 Certification focuses on foundational cybersecurity and the most critical set of controls for essential cybersecurity hygiene. This certification demonstrates that OMNY’s Ecosystem Platform has a comprehensive set of rigorous controls and best practices in place for essential for cybersecurity hygiene and protecting sensitive information.
“The HITRUST e1 Validated Assessment is a good tool for cyber-aware organizations like OMNY HEALTH that want to build assurances and progressively demonstrate due diligence around information security and privacy,” said Robert Booker, Chief Strategy Officer at HITRUST. “We applaud OMNY HEALTH for their commitment to cybersecurity and successful completion of their HITRUST e1 Certification.”
Achieving HITRUST Certification is no small feat. It represents countless hours of hard work, meticulous attention to detail, and an unwavering commitment to excellence from our entire team. This certification validates our robust approach to data security and privacy, covering 19 domains of information security.
“The HITRUST e1Certification is more than just a badge of honor – it’s a rigorous, comprehensive validation of our security practices,” said Dr. Maik Lindner, OMNY’s Chief Information Security Officer. “This achievement demonstrates that we’ve implemented a robust set of controls that meet the unique challenges of protecting sensitive healthcare data. It’s a reflection of our proactive approach to security and our commitment to staying ahead of evolving cyber threats in the healthcare industry.”
For our health system partners, the HITRUST Certification of our platform offers several key benefits:
“Achieving HITRUST certification is a testament to our unwavering commitment to data security and privacy in healthcare. This milestone reflects the dedication of our entire team and reinforces our position as a trusted partner in the healthcare data ecosystem. We’re proud to offer our health system partners the highest level of assurance in data protection, allowing them to focus on what matters most – improving patient outcomes,” said Dr. Mitesh Rao, CEO.
At OMNY, we view this certification not as a final destination, but as a milestone in our ongoing journey of excellence. We are committed to:
As we celebrate this achievement, we want to thank our dedicated team and our valued partners for their trust and support. We look forward to continuing our mission of advancing healthcare through secure, innovative data solutions.
Sickle cell disease (SCD) presents unique challenges for patients and healthcare providers alike. To better understand these challenges, OMNY Health analyzed real-world data (2017-2024), leveraging its unique ability to integrate structured EHR data with curated clinical measures to provide a comprehensive view of SCD patients. This study examined the demographics, healthcare utilization, and treatment patterns of 10,958 individuals diagnosed with SCD.
SCD remains a condition that disproportionately affects minority populations. Among the studied population:
Figure 1. Demographic Characteristics of Patient Population
API = Asian Pacific Islander
Note: Percentages were based on non-missing data
At the same time, these patients experience high levels of healthcare utilization:
These figures suggest that many individuals with SCD struggle with disease management, pain crises, and complications that lead to recurring hospital visits. The high frequency of inpatient admissions, even among younger adults, indicates that preventive strategies may not be reaching those who need them most. Many hospital stays are driven by acute complications, highlighting the importance of early intervention and better access to disease-modifying treatments that could reduce the need for emergency care.
Table 1: HCRU Among Individuals with SCD
| Inpatient Admissions | Emergency Visits | Outpatient Visits | |
|---|---|---|---|
| Mean (SD) | 4.3 (10.6) | 7.0 (15.4) | 34.1 (74.3) |
| Median (Q1, Q3) | 2.0 (1.0, 3.0) | 3.0 (1.0, 7.0) | 8.0 (2.0, 29.0) |
| Min, Max | 1, 185 | 1, 368 | 1, 1147 |
OMNY Health’s curated datasets capture a wide range of comorbidities, helping to identify broader clinical patterns that impact SCD progression. Among the most common conditions observed:
Figure 2: Top clinical comorbidities among individuals with SCD
URI: Upper respiratory infection; GERD: gastro-esophageal reflux disease without esophagitis
Despite available treatments, adoption remains low:
This raises concerns about barriers to access, including cost, provider awareness, and prescribing patterns. Through OMNY Health’s ability to track real-world prescribing trends and treatment adherence, stakeholders can better understand where interventions are needed to improve access.
By leveraging OMNY Health’s robust real-world data, we can provide critical insights into treatment patterns, healthcare utilization, and patient needs. OMNY Health’s curated data and clinical measures enable a more complete understanding of SCD care gaps, supporting efforts to inform policy changes, optimize treatment strategies, and enhance healthcare provider decision-making
For more information about OMNY Health’s product offerings, let’s connect!
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.
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:
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 |
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.
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.
