Jonathan Rapley, business consultant at Netcall, reveals the future role intelligent automation tools and processes will play in helping the NHS to address the treatment backlog
Automation tools such as machine learning and artificial intelligence offer the NHS a cost-efficient solution to address some of the key challenges
Over the years, healthcare organisations have struggled to get to grips with the digital transformation of their systems.
Now, with patient consultations and treatment backlogs at an all-time high and Did Not Attends (DNAs) costing the NHS £1.4m each day, there is an urgent demand to solve this growing problem.
Happily, the rise of intelligent automation tools and processes presents healthcare organisations with the ability to tackle this head on.
Investing in automation allows organisations to significantly improve response time, efficiency, and ultimately the patient experience.
Automation can also enable healthcare organisations to transform processes with end-to-end digital health platforms and services.
If implemented correctly, innovative tech solutions, such as low-code tools and robotic process automation (RPA), can help to reduce costs, increase staff capacity, and generate accurate data-driven insights to help improve patient outcomes.
Getting started with an automation project, however, can be daunting and many organisations are unsure of exactly where to start.
Here are eight top tips for driving successful automation projects within healthcare organisations:
Automation provides healthcare organisations with a great opportunity to solve all manner of challenges. In other words, if you can see a problem, automation can solve it – the possibilities are endless.
By implementing procedures driven by intelligent automation, organisations can improve patient care and experience and increase staff capacity.
The key here for healthcare organisations is not to be restrictive with their investment in automation and, if possible, be imaginative and invest in all areas of the organisation to unlock the full benefits available.
Automation provides healthcare organisations with a great opportunity to solve all manner of challenges. In other words, if you can see a problem, automation can solve it
There is so much potential in intelligent automation, whether it is RPA, low-code, or artificial intelligence (AI) – all of these can help improve different aspects of the healthcare structure.
It is important, however, to remember to scope out the process and set out building blocks first so there is an understanding of where automation is needed most to improve processes.
NHS trusts and other bodies within the Integrated Care System (ICS) that can implement an automation process across the whole organisation and, indeed, across the ICS, reap greater benefits than those that just implement a new system in the back office of one department or silo.
To reap the full benefits of automation projects across the organisation, it is vital to utilise the staff within your organisation, speak to the experts, and work together to draw out the processes and find solutions to problems.
It is also necessary to involve staff when scaling up automation across the organisation, rather than leaving it to IT teams to manage alone and do in small pockets.
Low-code technology can be particularly useful for staff as part of an automation architecture as it allows them to become citizen developers and be not only involved, but engaged in the development process.
One of the biggest benefits of low-code is that it takes the pressure off IT departments, i.e. anybody within the business can use this technology as it does not require tech skills or knowledge to utilise.
Most NHS trusts use hundreds of different, and often siloed, processes to conduct various tasks. This generates large amounts of isolated data rife with untapped intelligence.
This is where AI and, in particular machine learning (ML), can be used to provide insights into that data and learnings that can then be used to improve processes and decision-making even further.
Its ability to find patterns and correlations amid vast data sets enables ML data models to automate decision making and make value-adding predictions based on its analysis, for example, of the likelihood of a patient missing an appointment.
In the past, this has been the domain of expensive data science teams using specialist tools and considerable resources. However, now the use of AI and ML is becoming available to all people within an organisation.
The key for healthcare organisations is not to be restrictive with their investment in automation and, if possible, be imaginative and invest in all areas of the organisation to unlock the full benefits available
People can build and train their own machine learning models, allowing them to better understand their data, use it to predict future outcomes and, as a result, address their unique organisational needs and process issues, delivering an overall better experience for patients and staff alike.
While it is important to identify problems within healthcare (for example, the use of outdated software), this could just be the tip of the iceberg to many other issues, so it is important to first get a holistic view.
The key is to create an automation process that identifies bottlenecks as you go through the planning process, starting simply, but broadly.
Once a process has been created that identifies the hidden problems, this provides an opportunity to get empirical feedback (reporting) on the bottlenecks and identify whether these problems relate to patient flow or staff procedure flow.
Although empirical feedback is important, so is anecdotal feedback – especially from staff and patients who will be involved with the new process.
Identifying challenges early will help to work out what issues this could cause or what impact this could have and resolve them before the problems become a bigger issue.
It is important to remember that one type of automation does not work for every problem or system; different automation tools and approaches are needed to solve different process challenges.
It’s essential to look at automation challenges from a strategic and tactical perspective, whether that is making improvements to an existing structure or reinventing a new process
It’s essential to look at automation challenges from a strategic and tactical perspective, whether that is making improvements to an existing structure or reinventing a new process. Be pragmatic with the decision-making process.
Low-code, RPA and AI/ML all have a significant role in this, especially when it comes to integration methods and using data. But this can also create challenges and, therefore, it is important to be pragmatic with the use of different automation tools for each problem.
Developing a completely-new structure is not always needed. In fact, for some processes, only an update is needed for it to work more efficiently.
Within many NHS trusts, the main issue is the continued use of outdated legacy processes and the need to transform parts of these.
The objective is to implement an automation project that is quick and simple to get off the ground, and cost-effective, otherwise it will not succeed in achieving better patient care or improving staff capacity.
It’s important to remember that it isn’t always possible to make all the necessary changes at once. New methods work better when changes are made incrementally, over time, and can rely on real-time and historical data feedback to inform amendments/improvements.
Planning from the outside to understand that automation itself will need to adapt and evolve as the organisation’s processes do, is an important reason to consider a reusable platform that can help address these changing requirements.
Start simple, so something operational is up and running, and make iterate improvements based on data and patient/ staff feedback.
The objective is to implement an automation project that is quick and simple to get off the ground, and cost-effective, otherwise it will not succeed in achieving better patient care or improving staff capacity
A key strategy to follow here is the four-step digital factory approach. Following these four steps will create a cadence of new automation deliverables that will help to make improvements to the automation process.
The final step to making an automation project a success for healthcare is creating an ethos and culture of innovation.
Encouraging creation, learning, and sharing of ideas and inspiration between staff and organisations.
Promoting automation projects within the healthcare setting will be essential to solving the issues of waiting list backlogs and outdated legacy systems.
Most importantly, sharing the success of these automation projects will enable others to see what has been created, and how it has been effective and hopefully encourage others to follow suit.
Promoting automation projects within the healthcare setting will be essential to solving the issues of waiting list backlogs and outdated legacy systems
The future of health and technology is expanding in many different directions and investing in automation, whether that is RPA, low-code technology, or AI, can help to provide long-term solutions to many problems through technology-led transformation.
The creation, development, and rollout of successful automation projects will lead to improved business efficiency and response time and improve the patient journey; all while significantly reducing costs and employee hours spent on mundane repetitive tasks.
Automation projects, aided by technology, will help to propel healthcare organisations forward to become more stable in today’s digital world.