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Orlando Agrippa, CEO, Draper and Dash: Embracing Artificial Intelligence and Machine Learning for Healthcare

Emerging trends like artificial intelligence (AI) and machine learning (ML) look set to provide early adopters and forward-thinking firms deep insights and advanced analytics that could radically transform and revolutionise healthcare into a new digital age. Integrating such technologies with existing systems may seem challenging to those responsible, but the benefits could be unbounded. Potential benefits could include predictive and prescriptive analytics, driven by rules-based and structured algorithms that are designed to deliver better business outcomes, streamlined processes, reallocation of resources and improved patient care. It could also include reaction, diagnosis or prescription to serious health issues based on numerical reasoning.

This new wave of transformation is being driven by technology and digital data that some might describe as the industrial revolution 4.0. That is, in short, the entire combination of digital, technological, and repeatable methods of producing work through machines or robotics. The question on everybody’s lips is, can these futuristic looking trends provide the real value promised, and do the technology partners have the expertise and computational power to scale and deliver whilst protecting valuable and sensitive data? Orlando Agrippa, CEO, Draper & Dash, outlines the incredible rise of AI and ML and discusses how these mega-trends are set to impact healthcare.

What are AI and ML?

In its simplest form, AI is the development of computer systems that can perform tasks normally requiring human intelligence, such as decision-making based on non-emotional factors. ML allows data derived from AI to learn by focusing on prediction-making and prescriptive outcomes and continues to learn. Both are intrinsically linked, and the significant rise of ML is due to speed and scalability of computational power – in other words – the cloud and the growing power of on-premise machines.

This means, automation of mundane tasks or streamlined workflows can be quickly and easily configured by data scientists as long as digital data aligns and frameworks are in place. One striking and prominent feature of AI and ML is that a machine has the potential to tell a person something they didn’t know. This means, rather than humans teaching computers everything they need to know, computers will indeed be able to impart wisdom to humans.

One consideration, or word of caution, might arise around expertise vs computer-driven recommendations, like an experienced doctor or nurse who base their decisions on expertise compared to computer-generated outcomes. It is probable however that these can work together and can be integrated to get the best of both worlds. In fact, I recall a very well-known article titled “Data Scientist: The Sexiest Job of the 21st Century” by D.J. Patil and Thomas Davenport written in 2012. Even then, these experts were able to recognise the impact data was set to have on industry and profession and that a data scientist would soon become a must-have for organisations that wanted to harness this for their benefit. Data scientists and the harnessing of data will continue to impact on social care and healthcare today and in the future.

AI and ML in Healthcare

The term “revolution” mustn’t be used lightly, or for the sake of causing a reaction. In the context of the digital revolution, this term is perfectly applicable, and indeed necessitated due to the growing difficulties of national healthcare services and firms that need to do more with less. With challenges faced with social care and healthcare alike, influential leaders are looking for ideas. With ailing services, falling patient care and heavy financial constraints, the time has come for change. The National Health Service (NHS) for example requires attention in the wake of changing times and the need to deliver better services, at a lower cost. This seems a simple equation, and in essence it is.

The upside to this revolution is the potential to deliver huge value to society and further improve the day-to-day running of social care and healthcare systems. The downside is the uncertainty this provides around jobs and the reskilling needed to manage a new working environment. Furthermore, issues around security and noncompliance also need to be addressed. The debate around derived information for doctors to enact upon looks set to dominate not only moral implications but also safety. The output and success of these are untested. With the influx of data being generated, the NHS is particularly susceptible to change, especially if the upside is an overall better outcome for the health service. The long-term vision does appear to be positive however.

The Digital Transformation: Dark Data

The global market analyst firm McKinsey reports that AI is just one of the many mega-trends to emerge from a global digital revolution that looks set to dramatically improve infrastructure, society and economy. These types of technologies have been frustrating early adopters for many years. According to McKinsey, “(AI) is finally starting to deliver real-life benefits to early-adopting companies”. The driving forces behind this new development are down to new computing power, sophisticated analytics and the tremendous amount of data that makes AI possible. More importantly, in order to achieve AI, McKinsey prescribe the path to harnessing such potential as “accelerating the digital-transformation journey”. Without the basic digital assets and knowledge base, AI and ML will not be possible.

In an age of digital transformation and the continued production and reproduction of data, one issue remains incredibly pertinent today – that is – “dark data”. One of the key aspects of embracing this transformation in the digital age is how an organisation can harness their data in a meaningful way for deeper insight and the provisioning of new methods to streamline doctors or reduce A&E waiting times for example. The problem with dark data is it doesn’t align with machine processes. In order to make intelligible decisions, data must conform and align otherwise it’s rendered useless.

In fact, PwC suggested that: an “unprecedented increase in the volume of patient healthcare data has left the industry struggling to put that data into practical use. Artificial Intelligence (AI) with its capability to draw ‘intelligent’ inferences based on vast amounts of raw data, may hold the solution. Follow the money and you’ll see big bets on healthcare AI across the globe: 63% of healthcare executives worldwide already actively invest in AI technologies, and 74% say they are planning to do so”. It would appear the time is ripe for change.

Draper and Dash’s Approach

Draper & Dash (D&D) is a healthcare data, insight, analytics and improvement company. Its solutions drive actionable insights, powered by superior information assets, which are tuned to each client’s precise requirements. One of the latest focus areas to come from the R&D department at D&D has been to devise AI and ML solutions to deliver improvement to healthcare firms. This is partly due to demand but also as a recognition of the significant opportunities available. For example, Accenture believes AI is a “self-running engine” that can have a dramatic impact on healthcare. According to its research, early adopters and those that embrace such technologies can potentially create 150 billion USD in annual savings for the US healthcare economy alone by 2026, which is a staggering sum. D&D has recognised this opportunity and is dedicated its services to delivering outcomes through data insights with AI and ML at its core.

Furthermore, D&D is partnering with major brands to ensure services meet stringent data standards and performance. This provides not only cutting-edge solutions, but the required computational power and flexibility of the cloud. Having delivered solutions across the globe, and with over 60+ satisfied clients, D&D continues to grow and deliver against its targets. With expertise in-house, domain knowledge and a thirst for solving challenges with the use of digital analytics, I believe this is the perfect storm for delivering a new industrial revolution 4.0.