May 17, 2020

The five key principles for building a patient-centric data-sharing platform

Digital health
healthcare services
Health IT
Saduf Ali-Drakesmith, EMEA Hea...
4 min
Enter any modern hospital and you’ll find that most specialist departments still operate a mixture of paper records and proprietary data storage syste...

Enter any modern hospital and you’ll find that most specialist departments still operate a mixture of paper records and proprietary data storage systems. Data may be shared, but it’s the clinician that’s doing the sharing, not a system, and this inevitably means that practitioners only have a partial view of a patient’s records.

At the very least, having part of a patient’s data trapped in ‘information silos’ where it is unavailable in the EMR is inefficient, hampering clinical decision-making and introducing variations in the standard of care across the organisation. In the worst-case scenario, crucial patient information could be unavailable to clinical staff in an emergency, despite the hospital being in possession of those facts somewhere in an outmoded filing system.

With the advent of the Internet of Things (IoT), these problems are being compounded by automated systems that only function effectively if they have access to the most up-to-date details. Indeed, there is a risk that without an appropriate unifying platform, the core data derived from connected devices will simply create further data silos, unavailable to the wider healthcare ecosystem.

One solution to such fragmentation is a standards-based clinical visualisation system built around the clinician, to unite disparate data sources in one place. It is more efficient, more productive and, most importantly, improves decision making and reduces unnecessary variations in care.

Unfortunately, there is frequently resistance to further technology by staff who are wary of disruptive IT projects that often don’t serve their needs. That shouldn’t be the case. With these five steps, every healthcare organisation can ensure the smooth delivery of an effective patient-centric data sharing platform.

1. Change the Culture

Professionals are naturally wary of the introduction of complex new processes, and sceptical of the promised benefits of new technology. But they do want a system that works and facilitates the care they provide. This means a system designed around their needs, working patterns and devices —rather than built to a management concept to which they are then forced to adapt.

That’s why introducing a new system within a clinical setting should be viewed as more than a technical challenge: the whole programme should be about developing new ways of working that are designed around the clinician, and all stakeholders should be closely involved in the development process. This doesn’t just ensure a better end product, but also encourages a cultural change throughout the organisation so that technology is viewed as an enabler of excellence, rather than a nuisance.

2. Focus on outcomes

A clear understanding of how and why clinicians use information sharing systems is essential in order to pinpoint the desired effect on the clinical outcome of a project. That outcome should then be the key force driving implementation.

 For example, when Hyland Healthcare developed a zero-footprint viewer and streaming technology to improve the diagnosis of stroke patients, it worked with clinicians to understand their working practices and needs. What emerged was a remotely accessible system to view CT scans, whereby clinicians could use their mobile phones to securely access data, and make an immediate decision to thrombolyse or not — potentially saving lives.  By focusing on the clinical outcomes, and understanding the way clinicians work, a system was devised that ultimately benefited patients.

3. Invest in standards-based systems

Radiology departments across the world have embraced PACS as the primary means for storing and viewing DICOM medical images. While based on the DICOM standard, many of these systems wrap the DICOM asset in a proprietary code set that makes the image and study difficult to share with a PACS from a competing vendor. Therefore, costly image migrations and CD/DVD image exchanges have become the norm.

 Furthermore, the world of medical imaging consists of much more than DICOM images in today’s healthcare environment. Images captured in specialty departments ranging from dermatology to gastroenterology to pathology come in many formats, including JPEG, TIFF and MP4. Hospitals need to invest in truly vendor neutral platforms that can centrally manage a wide variety of images in their native formats to simplify image exchange and collaboration.

4. Think big, but start small

While it is tempting to embark on a huge project where potential savings or improvements can be expected, it’s wiser to exercise caution and start small. There are untold numbers of failed projects that promise much, but fail to deliver the outcomes.

 New systems should be thoroughly trialled, starting with teams where there is the highest chance of success, rather than the highest potential rate of return. As lessons are learned, improved versions can be rolled out to the wider enterprise.

5. Appoint a clinical champion

Every project needs a clinical champion who can bring the medical perspective to the table, providing representation for stakeholders and advising on patient interests too. You will need to choose someone who can remain enthusiastic and committed to the project, is data driven, and can help define what constitutes high-quality care, as well as what is required to deliver it.

Credit: Hyland Health

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Jun 11, 2021

How UiPath robots are helping with the NHS backlog

6 min
UiPath software robots are helping clinicians at Dublin's Mater Hospital save valuable time

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. 

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