Rare diseases are notoriously difficult to diagnose and document. Their complexity, low prevalence, and gaps in coding systems often leave patients undercounted and underserved. In a recent webinar, experts from the University of North Carolina (UNC) at Chapel Hill, Johns Hopkins Medicine, and IMO Health explored how ontological tools, structured models of medical knowledge, are reshaping diagnostics and research for rare conditions.
Keep reading for highlights from the webinar or click here to watch the on-demand webinar in full.
Why ontologies matter for rare disease care
Jonathan S. Berg, MD, PhD, a Bryson Distinguished Professor in the Departments of Genetics and Medicine at UNC, explained that ontologies help clinicians and researchers clearly define what they’re talking about, even when the same condition has multiple names or varying levels of specificity.
This kind of clarity eliminates ambiguity in diagnostics and makes research data more consistent and reliable.
The challenge of coding rare diseases
Traditional systems like ICD-10-CM cover only a fraction of rare diseases, leaving most without clear representation. As Ada Hamosh MD, MPH, a Dr. Frank V. Sutland Professor of Pediatric Genetics at Johns Hopkins Medicine explained, this lack of visibility has real consequences for patients.
Without accurate codes, patients are hard to identify, clinical outcomes can’t be tracked, and new therapies struggle to reach the right populations. Ontologies help fill this void by providing a structured way to classify and capture rare conditions.
Lumping, splitting, and IMO Health’s approach
One recurring challenge in rare disease classification is deciding whether to “lump” related conditions under one umbrella or “split” them into distinct subtypes. Ontologies support both perspectives, but for clinicians, flexibility is critical.
Patrick McCormick, MD, Staff Terminologist at IMO Health, explained how this principal shapes IMO Health’s work:
By operationalizing both approaches, IMO Health ensures clinicians can document with precision, while researchers still have a framework supporting broader analysis.
Building research-ready data
Ontologies also enable researchers to generate structured datasets that accelerate discovery. By standardizing identifiers across institutions, patients with the same rare condition can be identified and connected to studies, something essential in a field where every data point matters.
Dr. Berg explained the value of this approach:
“If you’re interested in discovering new genes, you could use [an ontology-based code] that says this is a patient who’s had in-depth genetic analysis and no one has found the answer. Pull those patients together and let’s get them into research studies.”
From tracking natural history to powering clinical trials, ontologies turn fragmented records into research-ready data.
A vision for the future
Looking ahead, the panelists described the ideal integration of ontologies into healthcare. Moderator and Chief Clinical Informaticist at IMO Health, Amol Bhalla, MD, M.Sci, MHSA, MBA, framed the challenge clearly: “The role of us at IMO Health is to stitch both your worlds, Dr. Hamosh, and Dr. Berg’s world, into something that is tangibly utilizable from a provider workflow.”
That vision includes structured family history, detailed phenotyping, and genomic data that flows seamlessly into EHRs, powering decision support, clinical management, and research simultaneously. With these tools in place, clinicians could more easily recognize rare patterns, patients would no longer be invisible to the system, and researchers could generate insights from every data point.
