The Vasculitis Patient Powered Research Network and the Vasculitis Foundation are proud to introduce a new, innovative study with the goal of reducing delays in diagnosis for new patients and improving clinical outcomes. Together, we are dreaming big for vasculitis research.

The Reality: Delays in Diagnosis for Patients with Vasculitis

Despite remarkable medical advances, diagnostic delays for patients with vasculitis remain extremely common and are a major cause of increased morbidity and mortality. This project directly responds to, and aligns with, the top research priorities of patients with vasculitis; specifically, to conduct research that will reduce the delay in diagnosis for new patients and improve clinical outcomes.

Why are there still delays in diagnosis?

The delays in diagnosis are frequently attributed to:

  • The rarity of the disease
  • Providers’ lack of awareness of the disease
  • Inadequate medical knowledge
  • Practice referral patterns

With recent increases in clinical and administrative demands on clinicians, there is often insufficient time to understand, gather or even piece together patients’ complex and often fragmented medical histories.

Each patient then becomes a data challenge with a vast amount of complicated information that is not always easily accessible for care providers.





Reducing these delays will improve disease outcomes, patients’ experience, and the quality of healthcare delivery.


Finding a New PATH with Pathways to Diagnosis:

An Innovative Approach to Reducing the Time to Diagnosis

With the goal of decreasing delays in diagnosis for patients with rare autoimmune diseases and specifically vasculitis, the Pathways to Diagnosis (P2D) project’s objective is to develop, train and validate diagnostic pathways (algorithms) in large healthcare administrative and patient-level data that predict a vasculitis diagnosis using predictive analytics and machine learning methods.

Testing a machine learning model to achieve a diagnosis

Machine learning capabilities and predictive analytics offer a potential solution by for assisting busy providers in sorting through an individual patient’s “big data” to establish accurate diagnoses and reduce delays.

P2D Objective

With the goal of decreasing delays in diagnosis for patients with vasculitis, the Pathway to Diagnosis (P2D) project’s objective is to identify diagnostic pathways (algorithms) that predict a vasculitis diagnosis using predictive analytics and machine learning methods .

Using ‘big data” to accurately predict a diagnosis of vasculitis by using predictive analytics and machine learning methods


Goal of P2D

The overarching goal of this project is to prospectively apply these generated predictive algorithms within healthcare systems to assist providers to more rapidly arrive at accurate diagnoses thus expediting therapies and improving clinical outcomes.


“We have the possibility and the ability to actually use artificial intelligence and prediction, or predictive analytics, to help us shorten the time to diagnosis and expedite diagnosis.” Principal Investigator for Pathways to Diagnosis, Dr. Antoine Sreih



Who is involved?

This project will bring together a variety of highly-involved stakeholders including patients and patient communities, PCORnet Patient-Partner Research networks (PPRNs), PCORnet Clinical Data Research Networks (CDRNs),partners in the biopharmaceutical industry, and a large number of academic investigators with subject matter and informatics expertise, and biostatistics.


How can you support early diagnosis research?

The Vasculitis Foundation’s 2018 Annual Appeal is focused on the critical need for early diagnosis of vasculitis. Your contribution to the 2018 Annual Appeal will help develop new and exciting ways to reduce delays in diagnosis.

Learn more and contribute today!