Project Tide in a nutshell

What’s the big problem you’re trying to solve?

The lack of accurate and reliable healthcare diagnostics in resource poor settings.

 

What’s your experience with that problem? (why are you doing this)

Each team member has digital health experience. Cyan is a founder of the digital healthcare agency Incuna, whose product – Incuna ePatient – is a framework for building patient adherence apps, and is used by thousands of patients across the world to track their conditions; he has also worked closely with the University of Oxford, to design and build The Global Health Network, the world’s largest online community of clinical trial professionals, (http://tghn.org). Matthew Ellen is a cross-disciplinary software developer specislaising in digital signal processing, he has previously worked at medical device manufacturer, Oxford Instruments.  Anant is a scientist by training and has been working across Europe with healthcare payers and providers for the past four years to help them design and implement high value healthcare systems; he is a co-founder of the Value Based Healthcare Programme at the University of Oxford.  We are also working in close collaboration with Dr. Stephen Lawn at the London School of Hygiene and Tropical Medicine, who is a global expert on Tuberculosis diagnostics.

 

What’s your solution?

An app that improves accuracy and impact of healthcare diagnostics.

 

How will this impact the lives of millions?

The first disease we are tackling is tuberculosis (TB).  According to the WHO, TB is the second greatest infectious disease killer worldwide and in 2013 it is estimated that 9 million people fell ill with TB and over 1.5 million people died from TB with over 95% of TB deaths occurring in low and middle income countries.  In 2011, Dr. Stephen Lawn and colleagues showed that an inexpensive diagnostic test strip (TB LAM) could be used at the point of care to help diagnose patients with TB.  While TB LAM provides many advantages over traditional diagnostics, it has only moderate accuracy in positively identifying TB patients, which can leave many infected patients undiagnosed  (Lawn, SD et al Lancet Infect Dis); our app will be designed to help improve the diagnostic accuracy of TB LAM.

 

How can people help/get involved? (ie we’re looking for teachers/carers/landlords/medical experts to do… )

If you are a medical expert working on digital diagnostics using mobile technology we would like to hear from you!