There are valuable insights hidden deep within healthcare. The healthcare eco-system is reliant upon one-off statistical studies to answer health and business questions, delivering insights using deep domain epidemiological and statistical expertise.
Answering such questions requires software and analytical skills across several different platforms, as well as vast amounts of person-hours to extract and analyse the insight. Those studies typically take weeks and cost hundreds of thousands of dollars each. How can we speed up the analysis of this data to provide a quick and cost effective alternative to insight and foresight generation as a stepping stone towards deep dive studies?
So, put quite simply, the opportunity is:
“How can we ask questions and get deep domain insight and foresight from health data in real time?”
How can we leverage ML models for day to day use? How can we make them accessible through questions in natural language? How can we answer the ‘why’ and ‘what’ questions in layman terms and help people to make better decisions with this information? e.g. Why are patients with rare disease misdiagnosed in the UK? What mutations occur? In what percentages? Which sites are in need of my drug? How can we enable the healthcare eco-system to go beyond the insight and the foresight and help their patients and healthcare providers to act on the insights without getting lost in jargon? How can we enable the healthcare industry to bring validation and utilisation together in the life science industry?
In OKRA’s words:
“How can we help to simply ask questions and get evidence based answers in real time?”