The healthcare sector also presents unique obstacles for AI: data must flow freely through AI systems to achieve real results, but extracting data from handwritten patient files or PDFs is cumbersome for us, and difficult for AI. Despite technical and operational challenges, new research suggests that the arrival of the tech giants into the industry may provide the data and the capital required to digitize this fairly untapped market.
Where AI can help now
Severe fragmentation between different branches of healthcare, and life-threatening miscommunication within institutions (in 2016, ~10% of all US deaths were caused by medical errors), presents an opportunity for AI to ease the burden on doctors in more creative, less intrusive ways. Mabu is a humanoid robot developed by Catalia Health and the American Heart Association that helps patients keep on top of at home treatment for congestive heart failure. Acting as a personal health assistant, Mabu asks patients how they are feeling, makes activity suggestions and provides medication reminders. ‘There are key points we make sure Mabu covers,’ says Catalia Health founder Cory Kidd, ‘but the conversation is adaptive to what is going on with that patient at that moment,’ much like a home nurse’s visits might be scripted to a certain degree while relying on some human intuition.
Mabu is a promising step towards integrating AI into the healthcare system without disturbing doctors within facilities - the data Mabu gathers can be fed into Electronic Medical Records (EMRs) via email or text, and ‘daily conversations’ with the device mean that Catalia Health can collect patient information consensually ‘without depending on access to their medical data.’ The implementation of AI throughout healthcare institutions or an entire country will remain a huge task even for data-rich multi-nationals, but solutions like this may help to improve outpatient care and reduce readmission rates for long-term conditions without setting foot in a hospital.