New Clinical Data Tool Aims to End Rare Disease Diagnostic Odyssey

ROSEMONT, Ill. – February 25, 2026 – For the millions of people living with a rare disease, the path to a correct diagnosis is often a grueling, years-long journey fraught with uncertainty and missteps. In a significant move to shorten this "diagnostic odyssey," clinical data intelligence firm IMO Health announced today, in recognition of Rare Disease Day, that it is integrating a massive, research-grade rare disease knowledge base directly into frontline clinical workflows.

The company has operationalized the Mondo Disease Ontology, a comprehensive global standard for disease definitions, within its widely used clinical terminology platform. This advancement allows clinicians to document patient conditions using familiar language while seamlessly linking that information to a precise, structured, and computable data standard behind the scenes. The integration promises to bring new levels of clarity and consistency to a field long hampered by fragmented and ambiguous data, potentially accelerating diagnoses and advancing research.

The Decades-Long Search for a Name

An estimated 300 million people worldwide live with one of over 7,000 identified rare diseases. For many, the journey to a diagnosis is a profound challenge. Studies have shown the average time from symptom onset to a confirmed diagnosis is a staggering 4.7 years. During this period, patients may see numerous specialists, undergo countless tests, and endure significant emotional and financial strain. A European survey highlighted the severity of the issue, revealing that 60% of rare disease patients are initially misdiagnosed with another physical or psychological condition.

A primary driver of these delays is the inadequacy of standard medical coding systems. For instance, the widely used ICD-10 system contains specific codes for fewer than 500 rare diseases, leaving thousands without a clear digital footprint in electronic health records (EHRs). This lack of granularity makes it incredibly difficult for health systems to identify, track, and analyze patient populations, hindering both clinical care and research efforts. Clinicians often resort to documenting symptoms in unstructured free-text notes, which are difficult to search and analyze at scale.

This new initiative aims to solve that problem at the source: the moment of clinical documentation.

Bridging the Gap Between Clinic and Code

The collaboration between IMO Health and the Monarch Initiative, creators of the Mondo ontology, translates complex, research-grade knowledge into a tool that is practical for busy clinicians. The Mondo ontology acts as a universal translator for disease definitions, harmonizing terms from various sources like Orphanet, OMIM, and the National Cancer Institute Thesaurus into a single, unified structure.

By embedding this intelligence within EHRs, clinicians can continue to document in their preferred, intuitive terms. The system then automatically maps these terms to the corresponding, highly specific Mondo identifier. This creates a dual benefit: the clinician's workflow remains efficient, while the underlying data becomes structured, standardized, and primed for analysis. The initial rollout includes nearly 5,000 new rare disease diagnoses and over 25,000 updated terms mapped to Mondo.

"Rare disease patients often experience years of uncertainty before receiving an accurate diagnosis," said Dr. Melissa Haendel, a co-founder of the Monarch Initiative and Director of Precision Health and Translational Informatics at the University of North Carolina School of Medicine. "By bringing standardized, high-quality rare disease definitions into clinical workflows, IMO Health is helping ensure that patients, clinicians, and researchers are working from the same shared understanding – an essential foundation for effective diagnostics and care."

This shared understanding is critical. It ensures that a diagnosis for a specific genetic condition in one hospital is recorded in the same computable way as in a research database across the globe, creating data continuity that has been historically elusive.

From Data Points to Diagnoses: Early Evidence Shows Promise

The potential impact of this enhanced terminology is not merely theoretical. Early research from leading institutions has demonstrated the power of using more precise clinical lexicals for patient identification. A pivotal study at Cincinnati Children's Hospital Medical Center, a leader in genomic medicine, provides compelling evidence.

"Our research at Cincinnati Children's found that using IMO Health's terminology for rare disease patient identification in electronic health records identified 5.5 times more diseases and 20% more patients compared to standard ICD-10 coding systems," stated Dr. Jing Chen, PhD, an associate professor of pediatrics and biomedical informatics at the University of Cincinnati College of Medicine. Her work focuses on leveraging EHR data to improve the understanding of genetic disorders.

Dr. Chen added that the direct integration of Mondo is projected to yield even greater results. "With the Mondo integration, coverage for rare genetic disease diagnoses will expand from 51% to 75% in Mondo while maintaining over 99% precision. These findings suggest that enhanced clinical terminologies can help healthcare systems identify rare disease patients more efficiently and accurately, potentially reducing diagnostic delays and improving outcomes."

For health systems, these improvements translate into tangible operational benefits. More accurate patient identification reduces the need for time-consuming manual chart reviews, streamlines the process of cohorting patients for clinical trials, and provides a clearer picture of the patient population's needs, enabling better resource planning and care management.

Fueling the Future of Precision Medicine

Beyond improving individual diagnoses, the widespread adoption of this technology could create a foundational data layer that accelerates the entire field of rare disease research. For decades, progress has been slowed by data that is siloed, unstructured, and inconsistent. By capturing standardized, computable data at the point of care, health systems and life sciences organizations gain access to a shared, high-fidelity understanding of disease.

This unified data stream is the fuel for modern precision medicine. It enables more accurate cohort identification for clinical trials, strengthens feasibility analysis for new drug development, and supports the generation of real-world evidence to understand treatment efficacy outside of controlled studies. As this rich data becomes the norm, it will also provide the high-quality input required for advanced healthcare analytics and artificial intelligence models designed to uncover new patterns, predict disease progression, and identify potential therapeutic targets.

By embedding deep rare disease knowledge directly into the tools clinicians use every day, this initiative brings visibility to a patient population that has often been invisible to the digital healthcare infrastructure. This new precision in data capture is a critical step toward unlocking novel research opportunities and generating insights that could lead to the next generation of treatments for some of medicine's most complex and underserved conditions.