Harnessing the potential of technology to transform health and care is a key focus for the NHS. Minister of Health and Care, Matt Hancock, has made it a central theme of his time in office, and the recently published NHS Long Term Plan has listed ‘making better use of digital technology’ as one of the key action points for achieving its goals.
Exploring the transformational potential of technology and its pivotal role in delivering improvements within health and care formed the basis for the recent inaugural Digital Health Rewired 2019 conference. The event brought together many specialists, researchers and digital leaders from across the world of health and care.
For the team at SCW, applying digital technology and Artificial Intelligence (AI) to the modelling of healthcare for the future is the focus of an important project. This subject was presented and explored by SCW’s Catherine Dampney, Director of Transformation, in her presentation at the conference, which outlined the important work of the team so far and a powerful new tool they have developed; the Dynamic Pathways Tool.
The need for the effective use of digital technology in the planning and evolution of healthcare has never been so crucial, due to the host of challenges faced by the NHS. AI modelling can provide a solution to the task of analysing huge amounts of data from patients, doctors, hospitals and commissioners from across the healthcare system.
“Health needs are changing fast, but systems are not keeping up,” said SCW’s John O’Connell, Director of Business Intelligence, in an interview leading up to the event.
“This is one of the many current commissioning challenges, together with an ageing population, access to data, increase of chronic and complex conditions and the significant NHS funding gap.
“To plan and deliver the health and care systems of the future, what is required is a shift from transactional, activity-based analytics to transformational and insightful analytics,” adds John. “With the Dynamic Pathways Tool, we have created an insightful, data-rich piece of research and development which helps to tackle these challenges.”
What is the Dynamic Pathways Tool?
Built upon research and analysis spanning more than five years, the Dynamic Pathways Tool is an innovative, scalable AI data system which delivers rich data insights that enable SCW to model and predict potential future needs for health and care systems.
The insightful tool was co-developed with Cecile Coignet, Head of Business Intelligence at Oxfordshire Clinical Commissioning Group (CCG). Cecile also presented the tool and findings alongside John and Catherine at the recent conference.
“In our position as Business Information custodians to health and care providers, commissioners and systems across our region, we have access to data on over 12 million anonymised people,” said Catherine.
“This encompasses an array of different yet rich data sets, which have given us the scale and opportunity to apply machine learning in the analysis of this data. Our journey with the data over the past five years has built a large, scalable data system from which we have developed our AI model; the Dynamic Pathway Tool. The scale and power of the insight it delivers is unquestionable.”
The ability to process national and local data sets, together with data from numerous care settings, including primary care, community and hospitals, means that the tool boasts the system data insight and the scalability to “take analytics to the next level.”
A wider view
“What we now have is not just data on 12 million people, but a platform, the data and the basis for an intelligence system for 12 million people. The insight this tool has undertaken can now be applied to additional data when included and we can extract the intelligence and communicate the insight to the data owners,” Catherine stated.
Through the compilation of data, this powerful tool has the capability to cast a wider view of the health and care system. “We can integrate and link data in a sophisticated way to not just unlock a traditional performance commissioning view of the world, but also unlock what the whole system looks like,” says Catherine.
The data insight will also lead to the “development of appropriate leading system indicators to identify what is happening,” added John.
This wider system perspective will help deliver an improved provision of services and marks a noticeable shift in approach; a clear move away from isolated information silos to combining data sets in one pool.
The richness of the data, when processed by the tool’s sophisticated AI algorithms, will help to increase efficiencies, reduce pressure on analysts and facilitate the NHS Long Term Plan’s “big focus on taking healthcare out into the community and out of hospital.”
“When we start bringing in other rich data sets from multiple health systems, like community systems and local hospital systems; it is just too much work for an individual analysist to undertake.”
The tool’s features, such as integrated dashboards and intelligence tools, reveal activity pressure points within the health system and opportunities for improvement. This insight will lead to the identification of alternative pathways of care. “AI allows us to look for pathways and patterns of optimal care,” explains John.
The Dynamic Pathways Tool’s algorithms can reduce weeks of analysis to just 20 minutes. The analysis of an entire pathway also helps to facilitate the debunking of key system-wide myths, which are presumed to be driving pressures onto various NHS services. Key instances of where this can be seen include the patient urgent care pathway and the diabetes integrated care programme.
With the foundations firmly in place, the potential of the Dynamic Pathways Tools is truly limitless.
“Having developed an enterprise-wide system, we’ve now got
data at scale that allows us to apply AI and machine learning which can take
our analytics to the next level,” said Catherine. “The tool’s algorithms will
test data, learn it and establish data patterns; this will then heavily
influence the design of specific pathways of patient care.”
The next stage of tool development is to build the sophisticated insight into predictive modelling; this will be used to collect, identify and predict patterns in patient needs and instigate changes in care pathways to address this.
Instigating positive change in health and care and empowering patients through informed data is a key driver when it comes to AI, machine learning and commissioning.
“When we go from A to B, we first used paper-based maps, then they became GPS navigators and now we’re currently using smart phones in our cars that use maths and real-time data to predict your journey time and change your route around roadworks or traffic jams. If we can do that for navigating from London to Manchester, why can’t we do that in healthcare?”
The use of sophisticated data sets, machine learning and AI is set to transform healthcare provision, improve patient care pathways and lead to empowered individuals across the healthcare system.