Surviving the transformation of healthcare: What kind of leaders are needed?
Tan LeFounder & CEO of EMOTIV
Surviving the transformation of healthcare: What kind of leaders are needed?26 May 2019
The advancement of AI, automation, big data, and neurotechnology is forcing leaders in the healthcare industry to either embrace the changes they will bring, or get left behind by the competition
Data is the fuel that will power future advances and create value, so organizations need to develop new frameworks to manage it efficiently
Implementing a multi-faceted approach to create a workforce that will have the skills needed to realize the full potential of these changes is imperative for success
We are moving into a period of unprecedented change, a 4th Industrial Revolution characterized by the integration of the physical, digital, and biological realms. In the 18th and 19th centuries, coal and steam power swept aside certainties and ways of life that had endured for millennia. In the early 20th century, electricity and mass production transformed our transport systems, our homes and our jobs. More recently, the advent of mass computing and the internet has ushered in a digital world of instantaneous global communication and almost frictionless access to information.
“It is not a future to be reluctantly survived, but one to be embraced with enthusiasm.”
At each of these stages, there were choices to be made. Those who embraced the new paradigm were propelled forward, gaining huge advantages over their competitors and earning the opportunity to shape the coming world. Those who chose to cling to the past were left by the wayside and consigned to history.
We now face similar choices once again. AI, automation, big data, and neurotechnology have all moved beyond their infancy, forcing leaders across all industries to grapple with the changes they will bring. Big data analytics will open up new products and processes and will challenge businesses to find new efficiencies. Machines and algorithms are expected to displace 75 million jobs by 2022, while 133 million additional positions will be created by the new technologies.¹ The tasks carried out by humans will change radically and quickly, requiring reskilling on an unprecedented level.
In the healthcare sector, the World Economic Forum (WEF) estimates that the share of task hours carried out by machines in complex and technical areas will grow by 50%.² Providers will have to grapple with ever greater demands for transparency from patients and insurers. Costs and outcomes will become more closely correlated than ever before and richer data sets will drive business to the providers who add most value. The quest for efficiencies will play an even more central role than it does now and those who can’t keep up will be swallowed by the tech-savvy competition.
The scale of these challenges, and the speed at which they are approaching, can seem overwhelming. However, if we take a deep breath and change the way we think about this future, the picture begins to look rather different. The 4th Industrial Revolution offers unparalleled opportunities for improving the way healthcare is delivered. It is not a future to be reluctantly survived, but one to be embraced with enthusiasm. For those who accept the challenge, the question becomes not ‘How can we get through this?’ but ‘How can we best lead the healthcare transformation?’.
The first problem that leaders in healthcare need to tackle is that of knowledge. 80% of healthcare companies identify not understanding the potential of these new technologies as the greatest barrier to adoption.³ This isn’t just a problem for healthcare. Tiger Tyagarajan, CEO of Genpact, has recently estimated that while 80% of business leaders approach artificial intelligence (AI) as a cost-cutting tool, only 20% see it primarily as a way of creating new value.4 Coming to understand how these new technologies can actively create value is a vital first step for leaders who want to be at the forefront of this revolution.
AI is a great example. We tend to think of AI in terms of the automation of machines and the replacement of simple, repetitive tasks. It’s not surprising that this picture doesn’t yell ‘potential’ to those working in a complex industry centered around individual human outcomes. But AI has a lot more to offer than just robotics.
Machine learning (ML) algorithms can be taught to seek out patterns in data at a speed that would be impossible for humans ever to approach. They can trawl through collections of millions or billions of data points to find correlations and connections that would otherwise never be apparent. This means that they can be used to find new ways to deliver value or to disrupt processes and frameworks.
For example, an insurance company like Blue Cross Blue Shield can use ML to investigate the social networks that drive recommendations from primary care physicians to healthcare providers.5 By understanding these social connections, they can then take action to disrupt the traditional recommendation flow and offer patients better-value alternatives that might not be considered by their physicians.5
This kind of value-driven approach is increasingly expected of healthcare providers themselves. With the vast data sets that providers gather, they are in a prime position to develop data analytics programs of their own or in collaboration with partners. For instance, ML algorithms have been used to explore the vast data sets generated by genomic studies, allowing researchers to identify correlations between the genomic profiles of tumors and sensitivity to specific cancer treatments.6
With this information in hand, the profiles of individual patient tumors can be used to predict the treatments that are most likely to be successful, improving outcomes and reducing costs. Similar approaches have been used to model cancer progression7 or to predict the outbreak and spread of diseases.8 Large-scale electroencephalography (EEG) data can be explored in a similar way to identify biomarkers for abnormal brain conditions or pre-clinical indicators for anything from Parkinson’s disease to mood disorders.
The potential applications of big data analytics are vast. However, to take full advantage of these possibilities, leaders in healthcare need to treat data not as a byproduct of the work they do, but as a valuable resource in its own right. Data is the fuel that will power future advances, so organizations need to develop new frameworks for managing it efficiently. A number of key steps need to be taken to ensure that healthcare businesses can maximize the value of their data.
KEY STEPS TO MAXIMIZE THE VALUE OF HEALTHCARE DATA
|1.||Build the infrastructure needed to collect, maintain, and store data efficiently|
|2.||Put in place strategies to improve the volume and quality of data collected|
|3.||Structure the data collected so it can be used effectively|
|4.||Create frameworks to ensure that data is handled in an ethical manner|
|5.||Build collaborative partnerships to share data|
|6.||Develop and deploy ML algorithms to explore the data in an intelligent manner|
Augment the workforce
Research is not the only area where these new technologies can create or add value. Public debates about the incoming technological revolution have focused on automation and the replacement of humans in the workforce. However, this framing of the issue risks casting the coming changes in terms of the negative processes of replacement, removal, and dehumanization.
But another approach is possible. The 4th Industrial Revolution will bring together not just the digital and physical worlds, but also the biological realm. When we add humans back into the picture, we can see that even the replacement of human tasks with technology involves augmenting what human individuals and human society can achieve.
Recent developments in wearable electronics can help us see what kinds of advances will be possible. Wearable EEGs connected to apps on smart devices can already monitor stress levels and provide real-time feedback on steps to take to help maintain optimal cognitive health. Wearable heart rate monitors can build up rich individual datasets to help with diagnosis or to support preventive healthcare programs. In the longer term, the integration of wearable tech with smart environments and machine learning will enable the creation of physical spaces – offices, homes, hospitals – that will respond intelligently to the needs of the humans inhabiting them to help them live healthy lifestyles or optimize recovery from illnesses.
Smart electronic assistants have the potential to augment the delivery of better value healthcare in more direct ways as well. A 2018 survey carried out by Deloitte found that the key obstacle identified by physicians in responding to value-based reimbursement models was a lack of useful data and the tools needed for understanding it.9 At the moment, only 28% of physicians receive any sort of cost information for the treatments they recommend and only 14% receive performance data for facilities and doctors to which they might refer patients.9
In the future, ML-powered assistants will be able to push the right data into the right hands at the right times, providing personalized analysis to guide treatment decisions. This sort of human augmentation will both improve outcomes and ensure that the treatments delivered offer the best possible value.
Bridge the skills gap
Between 2018 and 2022, it is estimated that the share of complex and technical tasks carried out by machines in the healthcare industry will increase dramatically, from 26% to 39%.10 One of the biggest challenges facing the sector is creating a workforce that will have the skills needed to realize the full potential of these changes. The US education system is now beginning to offer students the tools they will need for the future workplace, but it will not be enough to rely on entry-level hires to do all the heavy lifting. To meet this challenge, industry leaders will need to develop multi-faceted strategies to bridge the skills gap.
- Hire senior managers with strategic vision as well as technical skills.
The leaders who take responsibility for managing the transition need to understand the new technologies that will power the 4th Industrial revolution. But just as important is the ability to create the new team structures, data infrastructures, and training programs that will integrate these capabilities and sustain them as part of the broader organization.
- Retraining is key.
Employees will need to work with the new technologies at all levels of the organization, so the skills gap cannot be bridged simply by hiring in new technical experts. The WEF estimates that 59% of the healthcare workforce will require some level of reskilling before 2022, with 33% of the workforce needing 3 to 12 months of retraining.11 To manage this scale of continuing education will require swift action and careful planning. Those companies who successfully create the internal employment resources they need will enjoy a substantial advantage over their competitors.
- Collaborate with the education sector.
Leaders in the healthcare industry can get ahead of the trend by taking proactive steps to collaborate with local educational providers. This approach will help ensure that pools of skilled workers are available when and where they are needed. Costly retraining in the future can be avoided by making sure that programs meet the changing needs of individual employers and the sector as a whole ahead of time.
- Collaborate with technology providers.
Solutions to the skills gap can be found in the development and implementation of the new technologies responsible for the gap. Industry leaders need to communicate and work with technology partners to ensure they create solutions and platforms that can be used with minimal technical expertise. For example, working with tech companies to build simple drag-and-drop interfaces can allow employees to create sophisticated and specialized programs without requiring technical programming skills. By ensuring that technology products can be used by the informed many rather than just the specialized few, hiring costs and training times can be reduced dramatically.
The challenge is the solution
The 4th Industrial Revolution will be defined by the unprecedented connections it makes possible: connections between humans and their environments; between man and machine; between data sets and practical applications. In order to move forward and keep pace with the coming changes, we will all have to seek out and create new connections of our own.
Those who retreat behind the walls of their organizations will miss vital opportunities to create value, while those who can collaborate – sharing data for mutual benefit and working with suppliers and the community to meet mutual needs – will survive and thrive. We need to look forward to this coming world with optimism. If we build the technological and social systems we need, and invest in our people, we can set aside our fears and move forward with our eyes firmly fixed on the new opportunities within our grasp.
Tan Le is the Founder and CEO of EMOTIV, a neuroinformatics company advancing understanding of the human brain through electroencephalography (EEG). She is a pioneer in the field of neurotechnology and serves on the World Economic Forum’s Global Future Council on Neurotechnologies. Tan is an award-winning entrepreneur. Her many awards include the prestigious 2018 IRI Achievement Award, given to honor outstanding achievement in innovation and individual creativity that contribute broadly to the development of industry and benefit to society. Her portrait was inducted into Australia’s National Portrait Gallery in 2018. Her TED Talks have received over 3 million views
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