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.
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.