Four cloud trends to shape healthcare in 2019
At the start of 2018, the healthcare industry found itself in the midst of a significant change including the adoption of the public cloud, multi-cloud access, the widespread use of emerging technologies like machine learning and artificial intelligence and planning around increasingly complex regulatory frameworks including the enactment of the General Data Protection Regulation (GDPR) in May 2018. This called for the three major public clouds - Amazon, Google and Microsoft - to consistently bring new solutions to the market (often behind a Business Associate Agreement and meeting HIPAA compliance frameworks) that evolved how healthcare does business.
Properly implemented and maintained, cloud-based solutions offer payers, providers, life sciences and Software as a Service (SaaS) healthcare organisations unprecedented opportunities to innovate and glean insights from massive data sets while still maintaining privacy, security, and compliance.
With advancements in technology and security over the last year, many healthcare organisations can harness the benefits of the cloud now more than ever before. The global healthcare cloud computing market was estimated at $20.2bn in 2017 and is predicted to grow to $35bn by 2022 according to a recent BCC Research report. As we see more development in technologies like telehealth, remote monitoring, and natural language processing APIs, cloud technology will continue to evolve to fit our new digital health landscape in four important ways in the coming year.
- Multi-cloud use will increase in 2019, especially for larger enterprises.
Larger enterprises are seeing distinct advantages of particular clouds, especially for Platform as a Service (PaaS) solutions. Healthcare organisations are gaining confidence that they can effectively partner with more than one cloud provider. Rather than thinking about multi-cloud as separate cloud providers for different applications, disaster recovery, or cloud provider diversity, 2019 will see a focus on a cohesive healthcare multi-cloud strategy around different public cloud services for the same application.
As cloud computing platforms increase their ability to store, secure, process and analyse, we will continue to see healthcare transformed by data. For example, Google has a strong history in big data, analytics, and machine learning, culminating in the launch of their Google Health API. As multi-cloud access increases, we can expect healthcare organisations to use Google Cloud’s expertise while also consuming services such as Amazon Simple Storage Service and Amazon Elastic Compute Cloud for computing and data storage to meet the unique needs of their business.
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- Pharmaceutical and life sciences companies will have another big year in cloud adoption.
If you look at the services that are being deployed by Amazon Web Services (AWS), Google Cloud Platform, and Microsoft Azure, a large percentage revolves around making data easier to consume, whether it be new database architectures, de-identification, classification, anonymisation or compliance-led initiatives. All of these services help break down critical barriers for pharmaceutical and life sciences organisations to put their data to work as they progress in analysing large and diverse sources of data, and work to speed their time to market. In 2019, as applications become more mobile and web-based, we will continue to see a strong cloud adoption across pharmaceutical and life science organisations on a global scale.
- The adoption of container and serverless technologies in healthcare will become mainstream.
While they are not new technologies, organisations will reprioritise containers and serverless services (think Kubernetes) as we see significant growth in artificial intelligence and machine learning in healthcare. Adoption of serverless technologies offers organisations a cost-effective way to launch applications without provisioning or managing any servers, further limiting vulnerabilities within the healthcare environment. As cloud computing platforms increase their ability to store, secure, process and analyse, we will continue to see healthcare transformed by data, and the ability to find meaning in it, and share it across silos with increasing interoperability.
- Complexity will increase in 2019, and with multi-cloud, there will be a need for greater attention to security, compliance, and privacy.
The ‘seams’ or boundaries between environments are often the most vulnerable points and multi-cloud, while offering many advantages, can create new security complexities. The complexity itself will continue, shifting from simply understanding Infrastructure as a Service (IaaS) on one cloud provider to strategizing how SaaS and PaaS can work together.
In addition to the technology aspect, the challenges many organisations faced with GDPR compliance in 2018 will continue to bleed into the new year. A GDPR certification framework is still a long way from fruition and the principles of “state of the art” measures to protect data are open to interpretation, much like HIPAA was until HITRUST provided prescriptive guidance. Very few companies fully understand how to architect cloud solutions in a manner that complies with GDPR principles. Now that more healthcare organisations are becoming GDPR aware, we will see these organisations utilise Microsoft in some locations and AWS in others as they seek to leverage the cloud while keeping governance and privacy their highest priority.
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.