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Home » Patient care » Why AI in healthcare could motivate clinicians and improve patient outcomes

Ben Francis

Deputy CTO, Top Doctors

Properly regulated AI is set to transform healthcare. It won’t replace clinicians — but it will reduce their admin burden so that they can spend more time with patients.

There’s a misconception about the use of artificial intelligence (AI) in healthcare settings, says Ben Francis, Deputy CTO of Top Doctors, a data company that develops technology to benefit patients and clinicians alike.

Caring for patients more efficiently with AI

AI innovations are not designed to replace healthcare professionals or make decisions on their behalf. Instead, they can take the drudge work out of a clinician’s day and help them get on with the job of caring for people.

“Caring is why they came into this sector in the first place,” says Francis. “We want to remove the administrative burden they face and give it to a machine that can do it faster. That way, healthcare professionals will remain engaged and motivated because they’ll have the freedom to do what they do best: respond to the needs of patients and make clinical judgements. That’s something only a human can do well.”

There are several ways AI could make a difference in healthcare. Take the issue of diagnosis waiting times, which is currently a big challenge for the NHS. “There’s a real bottleneck in this area,” says Francis. “AI tools can speed up processes so that diagnoses can be made more efficiently.” What’s more, if siloed data can be centralised — and if AI is able to access and process it — medical research projects that once took five years could be completed in months.

If siloed data can be centralised — and
if AI is able to access and process it —
medical research projects that once took
five years could be completed in months.

Helping clinicians access patient data and improve outcomes

AI can also be used to support the work of clinicians in ICUs. One of Top Doctors’ products is an AI-powered physical touchscreen device that automatically connects to medical equipment and presents patient data when healthcare professionals need it.

“Interoperability — the ability of systems to connect and exchange information with each other — is something that everyone is talking about at the moment,” says Francis. “The interoperability of this device is excellent. We can take the information it gives us, put it into a clinical data lake, and get further insights very easily — which improves outcomes.”

It’s also equipped with a camera and microphone, enabling telehealth consultations with clinicians in other locations. As a result, patients in remote ICUs — or those needing out-of-hours care — can always have access to a specialist.

Patient-facing AI innovations include avatar interfaces, which can be installed in hospital entrances to direct people to their appointments. Top Doctors is trialling this technology, and Francis accepts that it may not be embraced by everyone. “It’s early days,” he says. “It may be that some patients will still prefer to speak to a person.”

Challenges around integration — and the importance of regulation

There are also AI chatbots, which can be used for data collection. “Normally, patients fill in web and paper questionnaires to give their feedback on the service they received,” says Francis. “This can include everything from hospital parking, waiting times and cleanliness. We’re now looking at using chatbots to get that data in a more open and friendly way. That’s very exciting.”

Naturally, there are challenges to consider. “One of the most significant ones is integrating this technology with hospital systems,” says Francis. “Also, these innovations are rapidly evolving, so we believe it’s really important to have regulations in place. At the moment, our AI isn’t making clinical decisions. However, if what everyone is saying is true, AI models could be capable of doing so in five years. This an area where we need to be careful to keep the trust of patients. After all, we put our clinicians through seven years of medical school, so we should apply the same rigour to artificial intelligence.”

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