Redacted article courtesy of – The Conversation
Imagine it’s 2030 – and a typical day in a Nigerian healthcare setting. In earlier decades, when a patient walked in, they could see piles of folders and a clutter of pens scattered all over the office. They’d have a long wait before being seen by a medical professional. Today, clinicians use technology to navigate easily through a system that’s centred on the patient.
So what has changed? Information in physical folders and files has been captured and used. A connected healthcare system has become a reality, driven by machine learning. Machine learning is basically getting a computer programme to perform a task without giving it explicit instructions.
Thanks to machine learning, patient care in 2030 has changed for good. Machine learning can now look at complex data to identify patterns and make timely predictions about the onset of disease and clinical outcomes. It does so by aggregating the huge amount of information from clinical notes, pathology results, sensor readings and medical images.
For decades, 97% of the data in these sources was unused, trapped in stacks of paper. In 2030, the Nigerian healthcare system can deliver proactive, predictive healthcare that is widely accessible and affordable.