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Author: Jenessa Mozdy

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Characterizing Latent Tuberculosis and Screening Among Individuals Diagnosed with Active Tuberculosis Disease in the United States © 

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

Tuberculosis (TB) has been a continuous public health challenge in the United States. Even though there are numerous screening and treatment options available, the burden of active TB disease still rises. Almost 80% of TB cases reactivate latent TB infection (LTBI). Timely identification of at-risk individuals and understanding their screening patterns is primarily important to reduce disparities in care.  

Building the Study: From EHR Data to Insights 

Our research team at OMNY Health conducted a retrospective, observational study using the OMNY Health Real-World Data Platform (2020–2024), which integrates electronic health records (EHRs) from multiple U.S. health systems. The goal was to describe individuals diagnosed with respiratory TB and evaluate patterns of TB screening and latent TB diagnosis before the onset of active TB disease. 

Study Design and Methods 

OMNY Health dataset identified the patients with respiratory TB (ICD-10-CM: A15). The earliest date of respiratory TB diagnosis was considered the index date. Demographic characteristics and social determinants of health (SDoH) were summarized at the index date or during the pre-index period. 

Utilization of TB screening procedures (CPT: 86480, 86481, 86580; ICD-10-CM: Z11.1) or diagnosis of latent TB (ICD-10-CM: Z22.7, Z86.15) was evaluated during the pre-index period. Descriptive statistics were reported for all variables of interest. 

Results: Identifying Patterns in Screening and Latent TB 

Between the years 2020-2024, total 6,538 cases of respiratory TB were diagnosed. Among these cases, 238 had a latent TB diagnosis code before the index date and 20% showed evidence of TB screening prior to diagnosis. 

TB testing was significantly higher among females and younger people, whereas it was lower among nonwhite and Hispanic groups. There had been more latent TB recorded among Hispanic individuals. This is consistent with high-risk profiles often seen among overseas-born populations or the ones travelling to counties where it is common. 

Approximately 5% of the population had data available on social health determinants, which revealed certain transportation and education barriers impeding prevention measures or treatment adherence. 

Figure 1. TB Prevention Pathway 

Figure 2. Study Population Demographics Characteristics, by TB Status 

Figure 3. Percentage of Affirmative Responses Across Social Determinants of Health Domains, by TB Status 

Why It Matters: Addressing Gaps in TB Prevention 

The study emphasizes early detection and screening to better prevent TB reactivation. The differences identified in screening rates indicate that demographic and social factors play a vital role to prevent TB. More targeted interventions can be developed to reduce inequities and improve outcomes if proper identification of populations (with limited access to screening and care) is done. 

Looking Ahead 

OMNY Health leverages real-world EHR data to better understand patient journeys enhancing preventive care. Future research is aimed to expand the SDoH integration into predictive modeling and public health decision-making. This will be helpful to bridge the gap between data and actionable outcomes. 

References 

  1. Centers for Disease Control and Prevention. National Data: Reported Tuberculosis in the United States, 2023. Reported Tuberculosis in the United States, 2023. 2024 Nov 7. Accessed February 10, 2025. https://www.cdc.gov/tb-surveillance-report-2023/summary/national.html​ 
  1. US Preventive Services Task Force. Screening for Latent Tuberculosis Infection in Adults: US Preventive Services Task Force Recommendation Statement. JAMA. 2023;329(17):1487–1494. doi:10.1001/jama.2023.4899C. 

 

© 2025 OMNY Health 

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Product

Unlocking the Hidden Details: Why Unstructured Clinical Notes Are Crucial for Life Sciences 

In the world of life sciences, data is king. For decades, the focus has largely been on structured data, including neatly organized tables, registries with predefined fields, clinical trial results captured in clinical report forms (CRFs), and insurance claims data. While undeniably valuable, this structured data often tells only part of the story. 

The real goldmine, often overlooked and underutilized, lies within unstructured clinical text. These free-text narratives – physician notes, discharge summaries, pathology reports, and radiology findings, to name a few types – contain a wealth of detailed, nuanced, and patient-specific information that rows and columns simply cannot capture fully. 

For life sciences companies, understanding and extracting insights from this unstructured data is no longer a luxury, but a necessity.

Here’s why: 

The Limitations of Structured Data 

Imagine trying to understand a complex patient journey solely from a checklist. Structured data, by its very nature, simplifies and categorizes. It’s excellent for tracking demographics, diagnosis codes, medication lists, and lab results. However, it often misses: 

  • Nuance and Context: The why behind a diagnosis, the specific symptoms a patient described, or the subtle changes in their condition over time.  A coded diagnosis of “headache” doesn’t reveal if it’s a throbbing migraine, a dull ache, or accompanied by visual disturbances.  In fact, most initial visit notes contain a History of Present Illness (HPI) that document the seven cardinal features of the patient’s reason for the encounter: 
    • Onset: When did the symptoms start? (The beginning time/date). 
    • Location: Where on the body is the symptom? Does it radiate or travel anywhere else? 
    • Duration: How long does the symptom last when it occurs? (e.g., seconds, hours, constant). 
    • Character (or Quality): What does it feel like or look like? (e.g., sharp, dull, throbbing, crushing, burning). 
    • Aggravating/Alleviating Factors: What makes it better or worse? (e.g., movement, rest, food, medication). 
    • Radiation (or Related Symptoms): Does the symptom move to another part of the body (Radiation)? Or are there any other symptoms that occur with the primary one (Associated Symptoms)? 
    • Timing (or Temporal characteristics): When does it occur? (e.g., constantly, intermittently, only in the morning, with exertion). 
    • Severity (or Scale): How bad is the symptom? (Usually rated on a scale, such as 1-10 for pain). 
  • Patient History Beyond Codes: Family history details, lifestyle factors, or environmental exposures that might not fit into a predefined field. 
    • Family History: Particularly important for oncology and cardiovascular disease, involves identifying which nuclear/extended family members had related conditions. 
    • Lifestyle Factors: Smoking, alcohol usage, illicit drug use, living situation, social determinants of health, and sexual health are known to be important risk factors but often omitted from structured data. 
    • Occupational / Environmental Exposures: Extra information that sheds light on risk factors for diseases including cancer and asthma.   
  • Treatment Rationale and Adjustments: Why a particular treatment was chosen / switched to / switched from / discontinued, how a patient responded to it, and subsequent modifications. 
  • Rare Disease Insights: For conditions with limited structured data such as their own ICD-10 codes, the narrative of clinical notes becomes even more critical. 

Four Applications of Unstructured Data 

Now that we have established how notes can be delivered to researchers, how exactly can they be used to enhance clinical knowledge?   

After de-identification, the possibilities are endless.   Below we describe four common applications. 

  • Extraction of Disease Severity: As opposed to the clinical trial world in which key outcomes are dutifully and regularly recorded, in the real-world researchers are reliant on physician record-keeping to identify the waxing and waning of disease progression.  And often, these outcomes, also known as severity measures, are found in free-text notes.  Learn more about how researchers at OMNY Health have been extracting information about disease severity from Notes since 2022 with the use of transformer-based pipelines and more recently with large language models (LLMs).   
  • Identifying Reasons for Treatment Discontinuation: Rollouts of newly developed drugs cost pharmaceutical companies millions of dollars; with that amount of investment, it becomes imperative to know more about why new drugs are being discontinued by patients/physicians, and which drugs are taking their place.  At OMNY Health, we have built various pipelines for extracting this information from clinical notes, again using both transformer-based methods and LLMs.   
  • Researching Rare Diseases: For rare diseases, clinical note repositories can be particularly useful in pooling large numbers of patients having such diseases and establishing basic clinical knowledge about them – e.g. What patients are at risk?  Why do some patients experience flares?  What treatments work best? An example is work that OMNY Health completed in partnership with a life sciences company on generalized pustular psoriasis (GPP).   Notes can also be used to find patients exhibiting symptoms or characteristics that might be consistent with undiagnosed rare diseases.  Clinical Notes can help identify patients that are candidates for genetic tests that could potentially validate a rare disease diagnosis. 
  • Training AI Models: In the age of Generative AI and LLMs, it is becoming more important than ever to find reputable sources of healthcare data (read: not the Internet) with which to train healthcare-specific LLMs that can reason without harmful biases.  Need a proven source of de-identified clinical notes from diverse populations and provider mixes with which to train your LLM?  We have made it possible.   

Learn More about OMNY Notes – Contact Us! 

At OMNY Health, we would love to discuss how our OMNY Notes product combined with our structured data offerings can support your clinical research initiatives and ultimately improve health outcomes.  Please contact us at info@omnyhealth.com.  We look forward to hearing from you! 

Categories
Product

Powering Research with LLMs and OMNY Health’s De-identified Clinical Notes in Cystic Fibrosis 

OMNY Health Notes when used in tandem with publicly accessible large language models can generate novel insights that previously were only accessible with labor– intensive chart reviews.   

Large language models (LLMs) have advanced dramatically since they were first introduced to the mainstream public a few years ago.   When combined with large, nationally representative de-identified data sets like the OMNY Notes product they can deliver insights in just a few minutes that previously would have required months of effort, and also at a fraction of the cost.  Check out this brief demonstration on how today’s LLMs and OMNY Notes can be used together to enhance clinical research, using notes for patients treated with cystic fibrosis as a sample use case. 

Thank you for watching our demo.  Please contact us using the email address/link provided in the video to discover how your research team can harness novel insights using OMNY Notes. 

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Featured News

OMNY Health Chosen to Present at Venture Atlanta 2025, the Southeast’s Premier Tech Conference

Now in its 18th year, Venture Atlanta has helped launch 930 companies, raise more than $8 billion in funding, and achieve $20.8 billion in successful exits to date 

 ATLANTA – September 11th, 2025 – OMNY Health is proud to announce its selection as one of the Southeast’s most promising tech companies to present at Venture Atlanta 2025. The event, to be held October 15-16 at The Woodruff Arts Center and Atlanta Symphony Hall, brings together visionary startups and growth-stage companies with hundreds of the nation’s top-tier investors. As the Southeast’s premier platform for tech innovation, growth, and capital access, Venture Atlanta continues to be a launchpad for companies shaping the future. 

Now in its 18th year, Venture Atlanta has helped launch over 930 companies, facilitating over $8 billion in funding and $20.8 billion in successful exits to date. This year, the event has expanded to include new founder pathways, curated networking, and procurement programming to attract over 1,600 attendees, including 450 investment funds from across the U.S. 

“We are incredibly honored to be selected to present at Venture Atlanta 2025. This city has become a hub for health tech innovation, and Venture Atlanta is the premier platform where the future of the industry gets shaped. To be recognized among a peer group of such promising, high-growth companies is a testament to our team and the critical infrastructure we are building. We look forward to sharing how OMNY’s healthcare data ecosystem will fuel the next generation of life-changing innovation.” 

As in previous years, Venture Atlanta 2025 is anticipated to be a sold-out event. 

“Venture Atlanta is where companies come to get discovered,” said Venture Atlanta CEO Allyson Eman. “To be selected in a year as competitive as this one speaks volumes about the strength and potential of these startups. These companies didn’t just stand out—they’re poised to break out. With hundreds of investors in the room and a highly curated audience, the visibility companies get here often leads directly to the funding, partnerships, and momentum they need to thrive. We’re incredibly proud to help founders gain the exposure and support that accelerates their path to success.” 

This year’s Venture Atlanta will once again bring together the Southeast’s most promising technology companies and the investors eager to discover them. With applications from across the region—including Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Maryland, North Carolina, South Carolina, Mississippi, Tennessee, Texas, Virginia, and Washington, D.C.—the 2025 conference offers a rare opportunity to see the region’s top innovators all in one place. 

Venture Atlanta boasts a roster of highly successful alumni, including Bark, CallRail, Car360, Flock Safety, Florence Healthcare, ParkMobile, Salesloft, Kabbage, Bitcoin Depot, PrizePicks, Stax, SingleOps, Pindrop, Terminus, and many others. 

To learn more about OMNY Health, visit www.omnyhealth.com.  For additional information about Venture Atlanta, to register for the event, or to view the conference schedule, please visit www.ventureatlanta.org.  

 

About Venture Atlanta 

Venture Atlanta, the Southeast’s technology innovation event, is where the region’s most promising tech companies meet the country’s top-tier investors. As the Southeast’s largest investor showcase helping launch 930 companies and raise over $8 billion in funding to date, the event connects the region’s top entrepreneurs with local and national investors and others in the technology ecosystem who can help them raise the capital they need to grow their businesses. The annual nonprofit event is a collaboration of the Atlanta CEO Council, Metro Atlanta Chamber, and the Technology Association of Georgia (TAG). For more information, visit www.ventureatlanta.org. For updates, follow us on Twitter and LinkedIn, and visit our blog. 

 

About OMNY Health 

OMNY Health™ is the leading healthcare ecosystem for compliant real-world data insights at scale. OMNY Health connects patients, providers, and life sciences companies by transforming vast amounts of de-identified electronic health record data, clinical notes, and claims data into robust, research-ready insights. Leveraging proprietary AI, NLP, and LLM technologies, OMNY Health accelerates therapeutic innovation, optimizes clinical development, and enhances patient care. For more information, visit www.omnyhealth.com.