Cloud Technology Solutions chief technology officer, Stefan Hogendoorn, outlines the key benefits machine learning can provide to revolutionise the use of technology in the NHS
Stefan Hogendoorn believes machine learning technology holds the key to improving the NHS
The UK’s healthcare sector is under significant strain, as an ageing population and tight budgets combine to increase the challenge of maintaining service standards for patients.
In order to combat this, the UK should look to innovative new approaches that some European healthcare institutions have implemented to increase efficiencies.
Developments in machine learning have had a transformative effect on a diverse range of industries, and new initiatives at a number of European hospitals and medical centres have demonstrated that this impact can be replicated in the British healthcare sector.
One of the biggest drains on doctors’ time is the paperwork and time investment involved throughout the diagnosis process.
In a busy surgery schedule; patients must be diagnosed efficiently and effectively to avoid delays and repeat visits.
Developments in machine learning have had a transformative effect on a diverse range of industries, and new initiatives at a number of European hospitals and medical centres have demonstrated that this impact can be replicated in the British healthcare sector
It’s in this field of the medical sector that machine learning can be put to good use in streamlining processes and reducing the workloads faced by medical staff.
Leiden University Medical Centre (LUMC), a major hospital based in Leiden, Netherlands, noticed that much of the time spent with patients was being used typing up notes from the anamnesis – a series of standard questions doctors ask to effectively diagnose patients.
This information also had to be inputted into the patient medical record software.
In order to solve this problem, LUMC’s IT innovation team worked with CTS to implement a pilot programme that could streamline the diagnosis process.
In the programme, the doctor is provided with recording hardware - two microphones - and a Google Cloud Platform (GCP) based interface, allowing them to record the interview.
During diagnosis, the doctor asks the standard anamnesis questions.
Once they finish the interview, the programme analyses the speech and transcribes it.
Not only can machine learning improve the efficiency of medical institutions; it can also offer access to additional insights that may not have been available previously
The transcription is then analysed using Google speech-to-text technology, looking for keywords from both the patient and doctor, to sort different parts of the conversation into answers for the anamnesis questions.
Once completed, the doctor will be presented with the transcript and results.
This system cuts down on the time-intensive process of drafting extensive notes and sharing them across a department; delivering benefits that provide major efficiencies and long-term cost savings.
This could have a transformational effect on the NHS and help to ensure its long-term continuity.
Not only can machine learning improve the efficiency of medical institutions; it can also offer access to additional insights that may not have been available previously.
This holds the potential to have a big impact on the way the NHS is run, and unlock more-effective, cost-effective treatment methods.
One example of this is Nico.lab’s StrokeViewer technology, developed in partnership with Google and CTS.
A positive attitude towards innovation, and a willingness to learn from the developments of other institutions, can ensure the NHS continues to provide world-class healthcare long into the future
This ground-breaking system uses machine learning to enable fast and accurate image analysis, offering unprecedented insights into the severity and progression of strokes when combined with the information received from an MRI scan.
Cloud connectivity via Google Cloud Platform also means that any insights can be shared seamlessly between different medical institutions, improving collaboration and lowering the administration investment if a patient has to be transferred.
When a patient is suffering a stroke, establishing a diagnosis and beginning treatment in a timely fashion is vital to ensuring damage is minimised.
This technology means that informed decisions by senior medical staff can be made quickly and confidently during such a crisis, potentially saving lives and preventing long-term damage.
In order to unlock the potential within the NHS and weather the challenges on the horizon, while maintaining service levels, innovative new technology must be embraced.
And these case studies demonstrate that new technology has a key role to play in moulding the health service of tomorrow and can pay dividends for both patients and management.
A positive attitude towards innovation, and a willingness to learn from the developments of other institutions, can ensure the NHS continues to provide world-class healthcare long into the future.