AstraZeneca
Exploring digital solutions to help shorten the diagnostic pathway for rare diseases.
The Challenge
Our challenge was to develop a digital solution to help shorten the diagnostic pathway for rare diseases. There are over 7000 known rare diseases, 80% of which are classified as very rare. While case loads for individual rare diseases are extremely small, their combined impact affects over 3.5M people in the UK alone.
By definition, rare diseases are very difficult to recognise and diagnose. Most physicians have limited knowledge and experience with rare diseases, encountering few, if any such cases during their entire career. In addition, the differential diagnostic protocol, employed by physicians as standard practice, follows a process of elimination of the most common (or likely) conditions rather than focus on the rare. And with rare diseases often presenting with “commonplace” symptoms, recognising a rare condition becomes extremely challenging.
As a result, it takes up to seven years (on average) to successfully identify and diagnose a rare disease, during which time patients often go untreated, get “lost in the system” or significantly lose quality of life.
What We Did
We explored the diagnostic journey through depth-interviews with GPs, specialist physicians, rare disease patients and patient advocacy groups. Research and analysis explored the social, medical and institutional dynamics and challenges at play in the diagnostic process, to identify opportunities for re-thinking current pathways and improving outcomes.
Result
Our solution was based on crowd sourcing the expertise of rare disease “sub-specialists” while leveraging the motivation of patients experiencing chronic, undiagnosed illness. We developed a novel diagnostic protocol that links patient data directly with the sub-specialist community to bypass blockages in the system and facilitate timely global access to rare disease expertise – leading to faster diagnosis.
The concept was prototyped and tested with patients and specialists. Following refinements based on user feedback, a refined prototype was delivered for further development.
consulted together with: Digitas