Featured Archives - OMNY Health

ATLANTA, GA — May 18, 2026 — OMNY Health today announced a major expansion of its healthcare data ecosystem, now representing more than 175 million de-identified longitudinal patient lives. This milestone — containing nearly half of the U.S. population — solidifies OMNY Health as the nation’s largest, most representative commercial source of first-party, provider-led clinical Real-World Data (RWD).

This growth is powered by targeted expansions across Integrated Delivery Networks (IDNs), community hospitals, Academic Medical Centers (AMCs), and large multi-state specialty groups. By capturing data directly from the point of care, OMNY provides the healthcare and life sciences industry with unparalleled access to diverse patient journeys at a national scale.

Bridging the “Why” Gap in Cancer Research

In tandem with this network expansion, OMNY has launched OMNY Foundation: Oncology, a specialty product suite designed to bridge critical data gaps in cancer research. While traditional datasets often lack pre-diagnosis and post-treatment context, OMNY’s solution provides deep insights from the full patient journey for over 10 million oncology patient journeys (2017–Present).

Consistent with OMNY’s other therapeutic-specific solutions, the oncology product uniquely integrates downloadable structured EHR data and holistic administrative claims data with de-identified clinical notes and diagnostic reports (e.g., radiology, pathology). This allows researchers to peer into the “narrative” of care — capturing physician rationale, therapy selection strategies, and the nuances of treatment planning that structured fields alone miss.

Regulatory-Grade Depth for External Control Arms

The OMNY Foundation: Oncology suite was engineered to meet the FDA’s stringent “Fit-for-Purpose” criteria, making it a viable asset for regulatory submissions and External Control Arms (ECAs). Key features include:

“Whole-Patient” Visibility: Seamlessly links oncology records with cardiovascular, metabolic, and primary care data to monitor pre-diagnosis history, comorbidities, and long-term survivorship.
Precision Variables: Direct access to granular data including tumor staging, treatment plans, mutation data, and molecular biomarkers (e.g., EGFR, ALK, PD-L1).
Auditability & Provenance: A transparent digital “paper trail” connects every data point to its source clinical event, ensuring the rigorous transparency required for high-stakes regulatory evidence.
Integrated Outcomes: Pre-linked 3rd-party administrative claims and mortality information provide a comprehensive view of care delivery, in addition to treatment response variables and long-term survival.

“Our goal is to transition the industry from ‘big data’ to ‘deep data,'” said Mitesh Rao, MD, CEO of OMNY Health. “By capturing the modern era of oncology screening and care across our more than 175 million patients, we provide the scale of a national aggregator with the clinical nuance usually possible in a specialty registry. We are delivering the high-resolution evidence required to answer the most complex questions in medicine today.”

About OMNY Health

OMNY Health is a premier healthcare data ecosystem that facilitates the secure exchange of clinical real-world data (RWD). By bridging the gap between healthcare providers and the life sciences community, OMNY accelerates medical breakthroughs and improves patient outcomes. In addition to its new Oncology product suite, OMNY maintains specialized RWD products in Dermatology, Ophthalmology, Gastroenterology, Respiratory, Cardiology, and Neurology therapeutic areas.

For more information, visit: www.omnyhealth.com

Media Contact: media@omnyhealth.com

By Lawrence Rasouliyan, Amanda G. Althoff, and Danae A. Black | OMNY Health

Understanding the Role of Lung Function in Asthma Management

Lung function monitoring is important in the management of asthma, and it provides valuable information to clinicians on disease control and patient response.

Pulmonary function tests are common tests conducted in clinical settings, yet they are infrequently documented as measurements in free-text notes or tabulated sources of real-world data.

Meanwhile, disease severity and acute exacerbations are usually available based on the diagnosis codes such as the ICD-10.

However, the association between coded severity and measured indices of lung function has not been well characterized in routine clinical care data on a large scale.

This gap was filled by our team at OMNY Health, which analyzed the relationship of lung function measures with severity and exacerbation status in subjects with persistent asthma.

Study Overview

Using electronic health record (EHR) data from 2017 to 2024, we analyzed information from three integrated delivery networks included in the OMNY Health real-world data platform.

Patients were included if they had an ICD-10 code for persistent asthma classified as mild, moderate, or severe—either with or without an acute exacerbation. The relevant ICD-10 codes used for classification are shown below.

To be included, patients also needed at least one documented lung function measurement—specifically, forced expiratory volume in one second (FEV₁) percent predicted (pp), forced vital capacity (FVC) pp, or FEV₁/FVC pp—associated with an asthma-related encounter.

Key Findings

Out of approximately one million patients identified with an asthma ICD-10 code indicating severity and exacerbation status, 14,003 patients (across 31,463 encounters) had corresponding lung function data available.

Across all severities, lung function metrics declined with increasing asthma severity, and patients experiencing exacerbations consistently had lower lung function compared to those without exacerbations.

What the Data Suggests

Findings have shown a considerable decrease in mean lung function values because asthma severity increased—regardless of exacerbation status.

Patients experiencing exacerbations had consistently lower FEV₁, FVC, and FEV₁/FVC metrics as compared to the ones with no exacerbations.

Most interestingly, when we compared ICD-10–coded severity to typical clinical cutoffs for lung function, the correspondence was not strong enough.

This undoubtedly suggests that ICD-10 coding alone may not fully capture physiological severity, emphasizing the importance of integrating structured and unstructured lung function data into real-world datasets.

Why It Matters

By leveraging structured EHR data, this study highlights the potential to better understand asthma progression and treatment outcomes across real-world populations.

The results reinforce the value of using lung function metrics—not just diagnosis codes—to assess disease burden and guide more precise asthma management strategies.

References

Levy ML, et al. NPJ Prim Care Respir Med. 2023;33(1):7.

Firoozi F, et al. Thorax. 2007;62(7):581–7.

Gronkiewicz C, et al. Chest. 2015;147(4):1152–1160.

Xie F, et al. JMIR AI. 2025;4:e69132.