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Andy Dé on how data-driven technologies are enabling a ‘Hive Mind’ in healthcare.

Since early 2020, the world has witnessed radical changes to government policy, economic welfare, industry development and life itself. With the number of coronavirus infections recently surpassing 31 million cases worldwide—and 42,000 deaths occurring in the UK—we’re stuck sailing unchartered waters.

Naturally, healthcare has been heavily relied on to mitigate the pandemic’s burden on a macro level, with data-driven technologies adopted to make smart yet critical decisions more efficient. But, what exactly has the data rich Artificial Intelligence (AI) been doing behind the scenes to keep services afloat?

Well, there’s a lot to unpick. COVID-19 has rapidly accelerated healthcare’s already growing dependence on data-driven technologies. Data and analytics have been invaluable in instructing and tracking the supply chain distribution of N-95 masks, gloves and PPE which have been in massive shortage throughout the pandemic.

Equally, the financial crisis occurring as a consequence of the loss of elective procedures has impacted revenues and margins, whilst additionally creating unprecedented risks for the health and safety of caregivers.

Perhaps the most significant area of transformation is the underlying clinical processes for patient engagement, diagnosis and post-discharge care and these are, likewise, driven by AI and analytics. All these factors have invigorated the industry to pursue swift digital transformation and innovate new kinds of digital patient engagement.

How healthcare providers already utilise and depend on data and analytics

Many healthcare organisations are looking to harness the vast potential of artificial intelligence (AI) and its four components – machine learning (ML), natural language processing (NLP), deep learning and robotics – to transform their clinical and business processes.

They seek to apply these advanced technologies to make sense of an ever-expanding “tsunami” of structured and unstructured data, and to automate iterative operations that previously required manual processing.

In light of all these new challenges, healthcare leaders see tremendous potential for analytics to deliver on the promise of better-quality care at lower cost by empowering their executives, clinicians and nurses to harness the power of predictive and prescriptive analytics.

For instance, UK charity Anthony Nolan eliminates data barriers through their use of the Alteryx Platform to achieve life-saving outcomes for people with blood cancer.

Analysts are empowered beyond traditional narrow silos and repetitive data munging with agile, shared warehousing of our critical business data.

Through an array of efficiency and effectiveness business changes, Anthony Nolan have spearheaded data-driven technologies to derive rapid hypothesis from data flows.

Importantly, the democratisation of data is pivotal in enabling this process, which allows health workers to harness all the same capabilities as data scientists, through easily accessible systems. Through utilising data and analytics tools, ethical and innovative data driven enhancements are being delivered to assist the transplant centres, stem cell donors and patients.

Data science and engineering tools are applicable from across the healthcare industry, from Jersey Hospital’s data-driven online waiting lists that is able to automate the analysis of recent data across the hospital to visualise the number of referrals and median waiting lists for new appointments to the Saudi Arabia Ministry of Health, APA systems have optimised the healthcare service.

For instance, the Saudi Arabia Ministry of Health manages local government hospital and medical activities with the assistance of automation platforms, allowing various administrative tasks such as collecting COVID test results to determining quarantine durations automatically.

This network analysis has allowed the government to understand the virus reproductions rate and track its spread. Crucially, this information has informed decisions which have assisted in reducing the spread of the virus and ultimately, saving lives.

Through insight analysis, the Saudi Arabia Health Ministry could target where, who and when they were required to response to COVID-19 cases and inform quarantining regulation.

How can healthcare innovation leaders further embrace robotics? 

We believe there are four primary areas in which robotics will become the normative practise within the post-pandemic healthcare provisions, many of which are already in use across the world. These areas are namely: improving the efficiency of repetitive manual processes; protecting care teams by reducing contact with patients; enabling and supporting clinical procedures to accelerate patient recuperation; assisting with post-discharge patient care and recovery.

To improve the efficiency of repetitive manual process is allows doctors, surgeons and staff to streamline their efforts on more important tasks, such as providing care which AI is incapable of. For example, hospital sanitation is crucial, but unfortunately, is prone to human error.

Considering the gravity of risk that insufficient sanitation induces, these tasks are a no-brainer for automation to protect both staff and patients. Through sophisticated “pick and place” systems, robots are able to disinfect thousands of medical instruments with consistency and without fatigue.

Automated guided vehicles (AGV’s) have already been deployed in hospitals in Germany and other European countries, allowing the automatic pick-up and delivery of a multitude of critical items – equivalently, this is an indication of how robotics can support the efficiency of otherwise manual and repetitive processes.

Protecting care teams by reducing direct contact with patients is equally essential.

This is perhaps the largest area in which we’ll see widescale adoption of robotics.

Temperature, blood pressure, sugar levels and pulse oximetry could all soon be captured without contact – indeed, this is already happening in countries like China, Taiwan and Japan. It is likely we will also see significant adoption in the UK in the near future.

This could even extend to robots scanning members of the public for COVID-19 at hospital receptions, retail stores, airline security checkpoints and even company offices.

Crucially, using this automated equipment to clean with precision could minimize sometimes deadly hospital acquired infections (HAIs).

While it might be hard to envision, robot nurses will help reduce the risks associated with drawing blood for both patients and nurses simply by eliminating the need for the close person-to-person proximity.

The third area is using technology to support clinical procedures.

Though many interventions involving complex procedures or invasive surgeries will continue to be carried out in person, there is significant innovation underway to enable minimally invasive robotic surgeries.

Ultimately, these AI-driven surgeries would offer benefits like smaller incisions and scars, reduced infection risk, less need for blood transfusions, faster recovery times and shorter hospital stays.

Similarly, Exoskeletons are structures that are designed to help people who have been paralysed or suffered serious injuries. Notable use cases have been with soldiers and military personnel who have sustained injuries on the battlefield effecting their ability to walk.

These robotic exoskeletons can be controlled via a joystick or voice commands, helping these patients become more independent.

Finally, technology will be incredibly useful in assisting with post-discharge patient care and recovery.

Given the new reliance on remote patient monitoring (RPM) systems in the wake of the pandemic, the natural next step may be to have fully-connected robots equipped with a speaker, camera and video-screen to engage with patients.

Those currently being adopted throughout the Eastern world have become enormously popular of late, and it’s likely we’ll see the same trend appear in the UK.

Democratising data and analytics for healthcare

Data-driven technologies are beginning to empower every human decision, thus liberating workers from the monotony of basic tasks, such as temperature checks when entering a hospital. Next-generation surgical robots have recently been hailed by UK doctors as ‘a leap in surgical precision’, having performed successful operations at two NHS hospitals – Edinburgh being the first to use the new robotic arm technology in Europe.

This is a perfect example of the ultimate synergy of human intuition and technological capabilities. As more organisations evolve towards a technology and data-led culture, the rate at which smart systems can be scaled across all parts of a business has emerged as the true measurement of business success.

However, there remains a data-literacy gap across UK healthcare, with many organisations remaining hesitant to fully harness the power of data and analytics. As the amount of data collected surges exponentially, the sheer quantity can overwhelm businesses. Consequently, many organisations have little choice but to focus on narrow portions of data – an incomplete fraction when solutions demand greater percentage of the whole.

The emergent category of Analytic Process Automation, or APA, could be the key to capturing the best of man and machine at scale.

APA automates business processes and grants even novice-level knowledge workers direct self-service access to business-critical data insights at speed. In practice, this means more employees can adopt — and benefit from — data with minimal training.

This in turn dissipates the familiar tension between data specialists and business managers, where the latter have been reliant upon the former’s access to much-needed information. APA democratises data analytics in a way the business world hasn’t seen before.

The horizon

There is little doubt, that 2020 has proved to be the most pivotal landmark within the 21st century and equally, pivotal for the healthcare world.

As the industry painfully realised the importance of data and analytics in harsh circumstances, this allows the opportunity for technology to spearhead a new frontier for healthcare.

As the complexity of data increases, it is imperative to adopt both descriptive and predictive analysis, while embracing Machine Learning and natural language processing to obtain the necessary information.

Nonetheless, the NHS must remain inquisitive and progressive, through asking the right questions and applying the right technologies, there is nothing which data and analytics can’t solve.

Andy Dé is senior director, healthcare solutions strategy and go-to-market strategy, at Alteryx, a data analytics firm.

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