Huawei and Phillips will collaborate on a new cloud-based healthcare solution
Rapid disruption is happening in the healthcare space. At the end of 2016, Huawei and Philips signed an MOU to build a new, cloud-based healthcare solution for deployment in China. The country is becoming home to an increased ageing population and limited resources, which has seen the need for the healthcare industry to become increasingly digital and patient centric. The use of digital technologies will therefore deliver increased accuracy within diagnostics and analytics and enable the ability for medical professionals to provide exceptional medical treatment surrounding chronic, long-term conditions.
Testing surrounding Huawei and Phillips’ healthcare solution has now been completed, at which the project is now looking towards a future where cloud and machine-learning will digitalise and disrupt the healthcare vertical with unprecedented speed and reach.
Targeting China’s smaller urban centers, the two companies will expand high-quality, cloud-driven healthcare to communities which lack advanced healthcare solutions or physicians with specialist skills.
The use of cloud AI will enable the processing of large volumes of data in a shorter timescale, and deliver greater accuracy than traditional medical professionals. Ludwig Liang, Head of Population Health Management for Philips in China, has explained the significance of this within China’s tier-2 cities, as many physicians “don’t necessarily have the skills to read image diagnostics like MRI scans and CT scans.”
“If you ask a doctor to process thousands of images a day, he may miss something. In contrast, AI is adept at spotting patterns in big datasets. For terminal illnesses, machine learning solutions hosted in the cloud can make a real difference in a patient’s prognosis.
Cloud AI in the healthcare domain can therefore benefit individuals, physicians, and populations.”
Mobile technology and apps put personal healthcare management and control back in the hands of the patient, enabling a move away from a reactive and sporadic model to one that’s proactive and always-on. “Using an app, people get objective data from a cognitive device, rather than just the word of someone they might not trust,” adds Liang.
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Through this transformation, patients will be able to approach consultation with healthcare professionals on a more informed level, with personal healthcare expanding into predictive monitoring, pre-emptive action, and even remote diagnostics and treatment. For example, data from a life-logging app that records your habits can work in tandem with wearables that monitor your physiology. Data can be sent to your physician in real time if, for example, your heart rate indicates a possible problem, “We can set a threshold that will alert your doctor so they become aware of something you may not notice,” says Liang.
However, will the older population be left behind in the face of such technological advancements? “We have to admit that we’re heading into new areas, how healthcare can be extended from hospitals to homes and leveraging apps and connected devices,” comments Liang. And, for Liang, the concept of extended healthcare is very important – treatment will no longer start and stop in a hospital or doctor’s office after someone becomes sick. Apps, sensors, smart devices, and the cloud will in effect mean “you have your own health team on call 24/7."
Increase of wearables
Wearable technologies are becoming increasingly commonplace within the health and wellness sector. In the future, we can expect bio sensing functionalities to offer a broader overall picture of one’s health, with advances in machine learning promising much greater predictive power. “For example, a smartphone might employ voice analysis technology to identify stress, heart disease, or Alzheimer’s based on vocal patterns,” observes Laing. “Your steering wheel may be able to pick up on the onset of Parkinson’s disease from small tremors in your hands; or your shower or bath might be scanning you for tumours on a daily basis.”
Cloud AI can eliminate a lot of the repetitive work for physicians. Doctors will be able to offload part of their work tasks, such as diagnostics to computers which are far superior at observing patterns. For example, strokes are caused by blockages or bleeds, but there’s just a 45-minute window to make a diagnosis and begin treatment to dissolve a clot when the first signs appear. However, it can take hours – or even days – for a shadow to appear on a scan that’s recognisable to a doctor.
Doctors will also be able to increasingly share information and conduct research using massive data sets that can be instantly mined. “[Doctors] collectively can record a huge amount of data from different cases over a long-time period,” says Liang. “So, they have a better chance of understanding different diseases and identifying how they can provide more effective treatment for patients.”
Cloud AI and the analysis of huge data sets will mean healthier overall populations, where trends can identify potential epidemics, implement constant monitoring, and facilitate AI-enabled research into rare diseases and sub-populations or geographies that are too fine-grained for humans to analyse.
The Philips-Huawei solution will go some way to levelling the playing field by cutting costs and increasing the efficiency, speed, and accuracy of diagnostics and treatments. “Our collaboration basically covers a cloud platform, but it also includes IoT connectivity and solutions,” says Liang. “We’ve tested our solutions on Huawei’s cloud and we’re very satisfied with the results. Now it’s about both companies working together to go to market.”
How UiPath robots are helping with the NHS backlog
The COVID-19 pandemic has caused many hospitals to have logistical nightmares, as backlogs of surgeries built up as a result of cancellations. The BMJ has estimated it will take the UK's National Health Service (NHS) a year and a half to recover.
However software robots can help, by automating computer-based processes such as replenishing inventory, managing patient bookings, and digitising patient files. Mark O’Connor, Public Sector Director for Ireland at UiPath, tells us how they deployed robots at Mater Hospital in Dublin, saving clinicians valuable time.
When Did Mater Hospital implement the software robots - was it specifically to address the challenges of the pandemic?
The need for automation at Mater Hospital pre-existed the pandemic but it was the onset of COVID-19 that got the team to turn to the technology and start introducing software robots into the workflow of doctors and nurses.
The pandemic placed an increased administrative strain on the Infection Prevention and Control (IPC) department at Mater Hospital in Dublin. To combat the problem and ensure that nurses could spend more time with their patients and less time on admin, the IPC deployed its first software robots in March 2020.
The IPC at Mater plans to continue using robots to manage data around drug resistant microbes such as MRSA once the COVID-19 crisis subsides.
What tasks do they perform?
In the IPC at Mater Hospital, software robots have taken the task of reporting COVID-19 test results. Pre-automation, the process created during the 2003 SARS outbreak required a clinician to log into the laboratory system, extract a disease code and then manually enter the results into a data platform. This was hugely time consuming, taking up to three hours of a nurse’s day.
UiPath software robots are now responsible for this task. They process the data in a fraction of the time, distributing patient results in minutes and consequently freeing up to 18 hours of each IPC nurse’s time each week, and up to 936 hours over the course of a year. As a result, the healthcare professionals can spend more time caring for their patients and less time on repetitive tasks and admin work.
Is there any possibility of error with software robots, compared to humans?
By nature, humans are prone to make mistakes, especially when working under pressure, under strict deadlines and while handling a large volume of data while performing repetitive tasks.
Once taught the process, software robots, on the other hand, will follow the same steps every time without the risk of the inevitable human error. Simply speaking, robots can perform data-intensive tasks more quickly and accurately than humans can.
Which members of staff benefit the most, and what can they do with the time saved?
In the case of Mater Hospital, the IPC unit has adopted a robot for every nurse approach. This means that every nurse in the department has access to a robot to help reduce the burden of their admin work. Rather than spending time entering test results, they can focus on the work that requires their human ingenuity, empathy and skill – taking care of their patients.
In other sectors, the story is no different. Every job will have some repetitive nature to it. Whether that be a finance department processing thousands of invoices a day or simply having to send one daily email. If a task is repetitive and data-intensive, the chances are that a software robot can help. Just like with the nurses in the IPC, these employees can then focus on handling exceptions and on work that requires decision making or creativity - the work that people enjoy doing.
How can software robots most benefit healthcare providers both during a pandemic and beyond?
When the COVID-19 outbreak hit, software robots were deployed to lessen the administrative strain healthcare professionals were facing and give them more time to care for an increased number of patients. With hospitals around the world at capacity, every moment with a patient counted.
Now, the NHS and other healthcare providers face a huge backlog of routine surgeries and procedures following cancellations during the pandemic. In the UK alone, 5 million people are waiting for treatment and it’s estimated that this could cause 6,400 excess deaths by the end of next year if the problem isn’t rectified.
Many healthcare organisations have now acquired the skills needed to deploy automation, therefore it will be easier for them to build more robots to respond to the backlog going forwards. Software robots that had been processing registrations at COVID test sites, for example, could now be taught how to schedule procedures, process patient details or even manage procurement and recruitment to help streamline the processes associated with the backlog. The possibilities are vast.
The technology, however, should not be considered a short-term, tactical and reactive solution that can be deployed in times of crisis. Automation has the power to solve systematic problems that healthcare providers face year-round. Hospital managers should consider the wider challenge of dealing with endless repetitive work that saps the energy of professionals and turns attention away from patient care and discuss how investing in a long-term automation project could help alleviate these issues.
How widely adopted is this technology in healthcare at the moment?
Automation was being used in healthcare around the world before the pandemic, but the COVID-19 outbreak has certainly accelerated the trend.
Automation’s reach is wide. From the NHS Shared Business Service in the UK to the Cleveland Clinic in the US and healthcare organisations in the likes of Norway, India and Canada, we see a huge range of healthcare providers deploying automation technology.
Many healthcare providers, however, are still in the early stages of their journeys or are just discovering automation’s potential because of the pandemic. I expect to see the deployment of software robots in healthcare grow over the coming years as its benefits continue to be realised globally.
How do you see this technology evolving in the future?
If one thing is certain, it’s that the technology will continue to evolve and grow over time – and I believe there will come a point in time when all processes that can be automated, will be automated. This is known as the fully automated enterprise.
By joining all automation projects into one enterprise-wide effort, the healthcare industry can tap into the full benefits of the technology. This will involve software robots becoming increasingly intelligent in order to reach and improve more processes. Integrating the capabilities of Artificial Intelligence and Machine Learning into automation, for example, will allow providers to reach non-rule-based processes too.
We are already seeing steps towards this being taken by NHS Shared Business Service, for example. The organisation, which provides non-clinical services to around two-thirds of all NHS provider trusts and every clinical commissioning organisation in the UK, is working to create an entire eco-system of robots. It believes that no automation should be looked at in isolation, but rather the technology should stretch across departments and functions. As such, inefficiencies in the care pathway can be significantly reduced, saving healthcare providers a substantial amount of time and money.