This article was originally published on The Guardian and is reproduced with permission from The Guardian.

 

As the use of artificial intelligence becomes increasingly widespread across the health industry, could machine-powered software help reduce illnesses?

Healthcare is on the brink of a technological revolution that will transform the way we think about medicine and how we care for ourselves.

Voice and digital assistants could one day detect suicidal tendencies in the speech patterns of users and refer them to therapy. Hospitals will use algorithms to analyse data about populations to understand when to expect a flu outbreak. Doctors will turn to artificial intelligence (AI) systems to help them prescribe the right drugs.

These innovations will be enabled by harnessing the abundance of data flowing from medical equipment, electronic health records, wearable devices, analysis of our DNA and even our digital communications.

For Femi Ladega, vice-president and chief technology officer at DXC Technology’s healthcare division, the advent of AI will offer new avenues for turning data into a medical tool that will be just as important as stethoscopes, scalpels and x-rays. “We are in a new wave of healthcare where the use of AI and machine learning will start to turn the deluge of data we have got into contextual specific insights that enable truly personalised care. That is where the industry is heading,” he says.

These new insights and knowledge from data will become vital – doctors won’t just access data about a patient. AI-powered software will also tell them about the implications of that data – to make them actionable. If they are about to prescribe drugs to a patient, the system would automatically recommend the best medicine for the patient, taking into account many more characteristics and factors than it would be possible for the doctor to consider. This would then be presented to the doctor to prescribe.

But for this new reality to come about, physicians and healthcare providers must first find effective technology that allows them to gather, share and analyse data.

As a step on the path to this digitally enabled health system, DXC has launched a new data platform that allows health providers to connect information from a range of sources such as care records and medical history. DXC Open Health Connect brings together data from hospitals, doctors’ surgeries and electronic medical records, and offers doctors context about the implications of that data. The system can help doctors identify at-risk patients and suggest preemptive measures to prevent them from getting ill, reducing the chance of them being admitted to hospital.

“We are trying to use the profile of an individual to give them a wellness programme,” says Ladega. In future, for instance, sophisticated software systems will analyse patient profiles to identify those who are at risk of developing diabetes, then target preventive programmes at them. If the outside temperature drops below a certain level, software could analyse a hospital’s local population to determine the number of people who are susceptible to lung disease or asthma at lower temperatures. That insight could be used to estimate hospital demand and predict that in the following hour or two, there is likely to be a rise in visits to A&E. The hospital could then put in place plans to cope with the rise in numbers.

Another way AI could improve healthcare is by using digital assistants to detect depression among users from the words they use when interacting with the assistants and from their tone of voice. Men are often reluctant to talk about their mental wellbeing, but they may be willing to open up to a robotic voice assistant. “The system converts the voice to text and picks out sensitive words that could highlight the risk of depression. Once you pass a threshold, the system will automatically book you an appointment or create a channel for you to talk to somebody,” explains Ladega.

DXC uses a model of data sharing called FHIR, pronounced “fire”, which stands for Fast Healthcare Interoperability Resources. This is a standard for sharing health information across IT systems. So, if someone is involved in a road traffic accident, the hospital could access their medical history and other relevant information from all their previous healthcare interactions. FHIR allows health providers to build APIs, pieces of software that allow different computer systems to share information.

“That model forces the democratisation of information in a standard way,” says Ladega. “In this day and age of big data, you have to work on open data, and this has got to be based on open architecture. That way, you remove any constraints to information sharing,” he adds.

He predicts that the 21st century will see the rise of a “genomic generation”, who use personal genomic services to analyse their own DNA data to understand their genomic makeup. This will influence their lifestyle choices, for instance avoiding sunbathing if they are genetically prone to skin cancer. Citizens will take greater responsibility for their own healthcare using data from wearables and fitness trackers.

“The genomic generation is going to bring a different dimension to the patient-provider relationship, and we will feel better for it. The trend I see is that health and wellness is going to be redefined in the next five to seven years,” says Ladega.

The new era of shared data will bring about improvements in health similar in significance to historic advances in medicine such as vaccines and penicillin.