- Most rare diseases lack unique codes – structured data fills the gap
- Standardized data unifies fragmented patient records
- Symptom-based insights reveal hidden diagnoses
- Clean data streamlines clinical trial recruitment
One in ten people lives with a rare disease. But the journey from initial symptoms to diagnosis is an arduous one, often taking four to five years – sometimes longer. Why?
“When you hear hoof beats, you think of horses,” Pam Gavin, CEO, National Organization for Rare Disorders (NORD), said. “But in the rare disease space, we say no, it could be a zebra.”
From delays in testing and referrals to insufficient insurance coverage or access to specialists, rare diseases can go unchecked for years. Plus, less than 10% of them have an FDA-approved therapy for their treatment, underscoring the importance of early, accurate diagnosis.
One of the core roadblocks is fragmented, incomplete, and vague diagnosis data. In contrast, structured clinical data at the point of care can help clinicians spot patterns faster, reduce diagnostic delays, and support patients more effectively.
A robust group of experts in informatics, clinical research, and care explored this topic at a recent rare disease panel discussion hosted by IMO Health. The experts included:
- Melissa Haendel, PhD, FACMI, Director of Precision Health and Translational Informatics at UNC – Chapel Hill, and co-founder/co-chair of the Monarch Initiative, which created and curates Mondo rare disease ontology
- Pam Gavin, CEO, National Organization for Rare Diseases (NORD)
- Amol Bhalla, MD, M. Sci, MHSA, MBA, Chief Informaticist, IMO Health
- Kerri Grizer (moderator), Director, Product Management, IMO Health
Read on for five ways structured data is reshaping rare disease care and research at the point of care.
1. Structured clinical data goes beyond basic codes
According to Haendel, around 80% of rare diseases lack unique ICD-10-CM codes, and those that do exist are frequently misapplied. Why?
- Incorrect codes may be used intentionally for insurance purposes
- Physicians may use vague or general codes
- Some diagnoses are not represented in standard code systems
Structured clinical data can help fill coding gaps by providing more context, including precise clinical symptoms and identifiers like Mondo terms, applied at the point of care.
2. It helps standardize documentation from multiple providers
Rare disease patients often seek opinions from various specialists, each with a unique perspective and documentation style. Bhalla noted that:
- Clinicians “fall back on [their] training”
- Different providers use different terminology
- This all results in “janky,” fragmented data scattered across EHRs, clinicians, and care settings
Gavin shared a personal anecdote: “My nephew was born with metachromatic leukodystrophy, but he wasn’t diagnosed with that right away,” she said. “As matter of fact, he had not just one inaccurate diagnosis, but multiple.”
Structured data normalizes disparate documentation styles, creating a more coherent patient story.
3. It surfaces patterns buried in the EHR
Many providers are not trained to link sets of symptoms to specific rare diseases because they don’t encounter them often. Leveraging structured data, Bhalla shared a case where he and a group of students successfully:
- Queried a large data warehouse based on symptomology
- Used structured phenotype-based descriptions in conjunction with Mondo to help determine diagnoses or possible diagnoses
- Identified patients with Ehlers-Danlos Syndrome
“You need to approach these patients with not just, ‘Hey, I think this is like this patient,’” Bhalla said. “You have to look at the symptoms behind the scenes.”
Structured symptom data enables more efficient and effective patient cohorting.
4. It connects clinicians to a reliable source of truth
Correctly spotting rare diseases at the point of care is difficult and, well, rare. But with Mondo integrated via IMO Health technology, clinicians can:
- Search within the EHR using natural language
- Link directly to resources such as OMIM and Orphanet
- Gain deeper context to inform better care decisions
“Mondo creates a global network of rare disease knowledge,” Haendel said.
Bhalla echoed this.
“The intersection of IMO Health and the Mondo piece is that if you think it is a possible rare disease type, you have the evidence at the point of care,” he said. “You can go extensively into the Mondo ecosystem and figure out that it’s the presentation of the patient in front of us… that’s extremely powerful.”
5. Precise data at the point of care enhances trial recruitment
Many rare disease clinical trials fail – not because the treatments are ineffective, but because the researchers can’t identify enough qualified patients. Haendel emphasized:
- Standard codes are not effective in cohort matching for rare diseases; other characteristics within the EHR must be used
- Health systems need to partner with pharma to coordinate with multiple health systems at once to identify appropriate patients
“For rare diseases, especially ultra-rare diseases, the whole [patient identification] strategy just falls apart,” Haendel said.
Structured, clean data enables faster and more effective patient identification and cohort matching, which can streamline the clinical trial process.
Transforming complexity into clarity
Rare diseases are complicated and confusing. Precise clinical data helps to simplify the journey, from point of care diagnosis to cohort matching to drug development.
No matter where you work along the path, better data informs smarter decisions, and smarter decisions lead to stronger outcomes.
