Guest editorial: Data is the new scalpel

News
29 Apr 2019
Gabe Rijpma, Information Services SLA member and Sr. Director Health and Social Services Asia, Microsoft

When young computer scientist Katie Bouman co-wrote the algorithm that made capturing of the black hole image possible, it was one of those defining moments in our collective history proving that together, we can drive new discovery and do amazing things. The ongoing quest for innovation and finding better ways to do things drives us all. And as a species – given enough time and commitment – we are able to solve many intractable problems. 

Health is not short of intractable problems that need solving. According to WHO, to meet the needs of our worldwide population by 2030, we will be short of approximately 14 million doctors and nurses. We don’t even have the global capacity to teach and graduate enough students to fill that gap. So, we need to think differently about the kind of health system we have and what it needs to become. 

If we think the health system we have today is the health system we need tomorrow, we are going to have big problems. The great thing is, many micro improvements across the health system will enable us to achieve incredible outcomes.

Data is what will drive this change. 

The incredible advances being made in the area of artificial intelligence and machine learning over the past 10 years is enabling new innovation, which will literally amplify the ability of our health workforce. This is not about replacing doctors and nurses – it’s about enabling them to be even better at the magic they do every day. Take Dr. Tada from the University of Tokyo. He and his team of researchers have trained a deep learning model, now with over 16,000 endoscopy and colonoscopy videos, to detect erosions and ulcerations from the camera footage. What would normally take a trained eye over two hours to analyse can be completed by the deep neural processing in under two minutes. The latest research I have seen is they are already exceeding the human eye with less false positives, and better, earlier detection of abnormalities. 

The work happening at Microsoft’s Research Labs in Cambridge, led by Dr. Antonio Criminisi, is equally interesting. Microsoft Research says they are close to perfecting software that can accurately measure tumours in 3D, from normal Computerised Tomography (CT) scans. The job of determining the extent of tumours is currently done by hand, with limited accuracy. The ‘Inner Eye’ project could make the process 40 times quicker and also suggests treatments that could prove the most effective. It can take 40 minutes or longer to do this process by hand if you are a radiation oncologist today, and this new project will reduce that time to just seconds. 

No matter where we look in health right now, across the spectrum of challenges we face, data through the use of AI and ML are coming to life.  

Across the South Island Alliance, we too have made incredible strides in being able to capture more data digitally and also build repositories to ensure clinicians have a broader view of a patient across the health system; with presentations, labs, medications, family history and more. This is the beginning of our foundation to be able to use data more effectively to inform care; but ultimately, to be able to predict and intervene earlier for the better well-being of all New Zealanders. 

Our next challenge is to turn the data we collect into insight, and ultimately have it inform decision making. Given all the challenges we have with capacity, cost, timely access and a never-ending quest for improving quality of care, we have to act now. We need to empower our innovators across health to be able to leverage that data. Our own innovators, and it could be you, will define our future. You may start simply by using data to reduce the risk of re-admissions and enable more capacity, which means we can forecast the risk or benefit of discharging a patient earlier and provide better accuracy to make the right decision. You might use the data to be able to identify cohorts of patients at risk in a collective data set and drive proactive, early prevention in conjunction with primary care, so we reduce the risk burden on our health system.  

Whether it’s operational, clinical or truly deep and transformative change you want to see in the health system, data is the new scalpel and we should use it to perform surgery on our own health system for sustainable and lasting change.