NHS hospital uses robot receptionists that are eight times more efficient than human staff
- Used at Ipswich hospital, run by East Suffolk and North Essex NHS Trust
- Has ’employed’ three virtual workers to allow staff more time with patients
- System has been running since July and has saved more than 500 hours of work
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An NHS hospital trust has become the first to use AI robots as secretaries in an effort to cut costs.
Ipswich Hospital, run by East Suffolk and North Essex NHS Trust, has ’employed’ three virtual workers to free up staff from ‘mundane and repetitive tasks’, such as submitting scans and blood test results.
This is thought to allow real medical secretaries more time to focus on patient care, with the system being eight times more productive than human staff, the trust claims.
The system has been running since July and has saved more than 500 hours of work, according to the trust’s deputy director of ICT Darren Atkins.
Over the next nine months, the AI programme will save them £220,000, he added.
Ipswich Hospital, run by East Suffolk and North Essex NHS Trust, has ’employed’ three virtual workers to free up staff from ‘mundane and repetitive tasks’, such as submitting scan results
The software, built by the automation technology company Thoughtonomy, monitors incoming referrals from GPs throughout the day.
It deciphers the reason for referral and supporting information, such as blood test results.
The robots then put all this information in a single document, which is flagged to the lead consultant for review.
Prior to the AI programme, medical secretaries were responsible for referrals, as well as downloading and printing documents, which they then scanned into a new file.
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The trust deals with around 2,000 referrals a week.
Mr Atkins claims the robots have already cut the time taken to process the first stage of each GP referral from 15-to-20 minutes down to just five minutes.
He added that within the first three months of the programme, the trust has saved more than 500 hours of medical secretaries’ time.
The AI programme is initially being used in five specialist units – neurology, cardiology, urology, nephrology and haematology.
‘We’re delighted with the results we’ve realised so far and are hugely excited about the potential benefits of automating more processes across our trust,’ Mr Atkins said.
‘When you look at the time and cost savings we’ve already banked within just one specific area of our operations, you start to get an idea of how intelligent automation can drive transformation on a huge scale within the NHS.’
HOW DOES ARTIFICIAL INTELLIGENCE LEARN?
AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn.
ANNs can be trained to recognise patterns in information – including speech, text data, or visual images – and are the basis for a large number of the developments in AI over recent years.
Conventional AI uses input to ‘teach’ an algorithm about a particular subject by feeding it massive amounts of information.
AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn. ANNs can be trained to recognise patterns in information – including speech, text data, or visual images
Practical applications include Google’s language translation services, Facebook’s facial recognition software and Snapchat’s image altering live filters.
The process of inputting this data can be extremely time consuming, and is limited to one type of knowledge.
A new breed of ANNs called Adversarial Neural Networks pits the wits of two AI bots against each other, which allows them to learn from each other.
This approach is designed to speed up the process of learning, as well as refining the output created by AI systems.
He added the technology mimics the way humans work on a computer so staff are freed up from ‘mundane and repetitive’ tasks.
The robots’ actions are auditable and safeguards are built into the system, he said.
‘I’ve been probably overcautious in the way this is being introduced… as we don’t want a referral to be mislaid,’ Mr Atkins added.
If a robot receives a duplicate referral from a GP after it has processed the first, it emails the medical secretary team ‘rather than just stopping working’.
The technology uses the same information governance system as human staff, according to Mr Atkins.
‘It’s the same level of security and data protection – no information leaves the trust site,’ he said.
The system has been running at the hospital since July and has saved more than 500 hours of work, according to the trust’s deputy director of ICT Darren Atkins
If the virtual workers had to be shut down, human secretaries ‘would just go back to what they normally do’.
The AI system has allowed secretaries to ‘spend more quality time on the phone with their patients and to answer the phone more of the time’, according to Mr Atkins.
The trust is considering rolling the programme out to other areas and has received enquiries from up to 30 other trusts and local councils, he said.
‘Lots of NHS trusts are on the verge of doing this.’
Dr Petr Pokorny, a staff grade neurologist at Ipswich Hospital, added: ‘It allows for a more efficient, fluent flow of work, as it’s easier to deal with five new referrals every morning rather than a huge pile of 35 referrals once a week.
‘What’s more, we now have our medical secretaries fully focused on the things that make a real difference to our staff and patients.’
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