3 emerging technologies that will impact healthcare

Artificial intelligence, blockchain technology and digital transformation are maturing rapidly and are likely to affect care delivery in the next three years.

If you read my previous article concerning the progress we have made in health information technology adoption and the development of digital health tools, yo. I believe we have made significant progress in many areas, but there are also some places where we have a long way to go.

I am optimistic that if we unleash the creativity of entrepreneurs and innovators, we can solve some big problems society is facing and certainly build a better healthcare system. Things are changing quickly and the policy landscape is shifting under our feet (often feeling like quicksand). There is confusion and sometimes chaos in the uncertain future of federal policy, yet this also creates opportunity for those bold enough to charge ahead.

There are going to be some big changes coming to healthcare, driven by these new policies and a different kind of leadership in Washington, but technology will still play a key role in transforming the healthcare system, creating change on a monumental scale. This massive change will occur because of the exponential growth of information technology, and this will impact all emerging technologies—robotics, automation, 3D printing, quantum computing, virtual and augmented reality, nanotube electronics, sensors, mobile technology, artificial intelligence, machine learning, natural language processing, cloud storage, big data analytics, the Internet of Things, and much more.

I see three important trends in looking towards 2020:
  • Machine learning and artificial intelligence
  • Blockchain technology
  • Digital transformation

The investments being made in these areas, by established industry players, disruptors and startups, are beginning to bear fruit.

Machine learning and artificial intelligence
There are many use cases identified where artificial intelligence (AI) will help improve outcomes, which is a critical need to thrive in a value-based care delivery and payment environment, and ultimately lower costs across the spectrum. I believe this is one of the reasons why venture capitalists and corporate interests are taking such strong positions in the AI market within the healthcare space.

There are numerous startups involved in this space from a wide range of specific areas—research, drug discovery, diagnostics and imaging, wearables, insights and risk management, ER and hospital management, among others. Global equity funding in AI for healthcare since 2012 exceeds $1.5 billion and not likely to let up.

So with all this energy and funding going into AI for healthcare how mature is the market really? I think we are close to what Malcolm Gladwell termed the "tipping point" and we are going to see rapid advance and some remarkable successes from many of these startups, perhaps within the next three to five years, perhaps sooner.

Gartner is the gold standard for technology analysis and their analysts are usually ahead of the curve in identifying technology trends. However, I think they may have had a near miss on this one. Their own much-hyped Hype Cycle for Emerging Technologies, now in its 22nd year, did not even have machine learning listed until last year, and it was already sliding down the peak of inflated expectations. In 2016, they pushed it back up to the peak, and yet deep learning is still nowhere on the list. Perhaps the analysts don't understand the significance of these technologies or maybe they just don't see a need for a separate listing. Or it may be that they are not giving adequate attention to the exponential advance of information technology.

It appears as though Gartner believes that the benefits of these technologies are still years off in the future. They have machine learning, distributed ledger and virtual personal assistants in the five- to 10-year category, and quantum computing at more than 10 years plus. Because of the exponential growth of information technology, these timelines will be shortened. Machine learning is here now and solving some important problems in healthcare. Smart robots and virtual personal assistants are in use today, although not yet widely used or commercially available.

I think it is important to take a holistic look at all of these technologies and the corresponding policy levers and market forces in play. 2017 will see significant advance in the use of machine learning and AI in healthcare, and along with a cloud infrastructure with data management and storage capabilities to handle these big data (and very small data elements as well). This will cause a paradigm shift in how we view, manage and use health data and, more importantly, how these data can create information and ultimately knowledge.

AI is not some far off science fiction horizon—it is here now, and few understand the exponential evolutionary nature of what is occurring. AI and machine learning are going to have a massive impact on society, on the economies of the world, on culture, education, and most definitely on healthcare.

There are valid concerns around ethics of machines being in control of key processes. There is a need for educated technologists who will prioritize ethical considerations in the design and development of autonomous and intelligent systems. This is why the IEEE Standards Association created the Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems and produced their first version of the document Ethically Aligned Design: A Vision for Prioritizing Human Wellbeing with Artificial Intelligence and Autonomous Systems.

There are also legitimate concerns on the effect of automation on jobs. Certainly some will lose their jobs to machines; however there will also be new opportunities for those willing to learn the necessary skills for humans to work in the future. Artificial intelligence will have a substantial impact on healthcare in the delivery of care, payment processes and all through the value chain.

Blockchain technology
Another emerging technology that had been underestimated initially among most healthcare leaders is blockchain technology. The blockchain is a type of distributed ledger, a database really, that maintains a constantly growing list of ordered records called blocks. Each block contains a timestamp and a link to a previous block, forming a sort of chain.

By design, blockchains are inherently resistant to modification of the data, some would say immutably so, which makes it a prime candidate for some interesting healthcare use cases. The blockchain technologies can be seen as a portent for the rise of the programmable economy and offers radical transformative power.

There has been a great deal of investment into various aspects of blockchain technology from such industry heavy hitters as IBM, Accenture, VISA, Microsoft, J.P. Morgan and many others. Primarily the energy thus far has been in financial services and cryptocurrencies like Bitcoin, but exploration for use in healthcare is gathering steam.

One of the top experts on blockchain, and in particular for use in healthcare, is Melanie Swan, who is a philosopher and economic theorist at the New School for Social Research. She also founded the Institute for Blockchain Studies, an independent non-profit research institute examining the theoretical, philosophical and societal implications of blockchain technology. She has outlined several areas in which blockchain technology can play a role in healthcare.

ONC, in partnership with NIST, has investigated blockchain as possibly providing solutions for health IT, launching an ideation challenge that solicited white papers on the topic of “Blockchain Technology and the Potential for Its Use in Health IT and/or Healthcare Related Research Data,” and exploring how the technology can advance interoperability and privacy needs. The agency announced the 15 winning white papers out of more than 80 submitted. One of the papers by Deloitte, "Blockchain: Opportunities for Healthcare," states that blockchain can offer a promising new distributed framework to amplify and support integration of healthcare information across a range of uses and stakeholders. They even offer a use case for blockchain as a new model for health information exchanges, potentially solving such thorny problems as distributed trust, cost and varying data standards.

My favorite paper among those submitted was from a team led by Ariel Ekblaw of MIT Media Lab who along with John Halamka, MD, CIO at Beth Israel Deaconess Hospital, which proposed a workable solution for medication reconciliation. The concepts were drawn from a peer-reviewed paper published by IEEE, "MedRec: Using Blockchain for Medical Data Access and Permission Management." A working prototype was designed with an interesting mechanism for how records are validated and added to the blockchain.

The miners (mining is the distributed computational review process performed on each block of data) for MedRec are medical researchers who are rewarded with access to census-level data of the medical records. Similar to the census, the individual privacy of the person is protected, and the aggregate data is used for critical research. Therefore, this is both a medical research blockchain and a clinical one. The MedRec proposal applies blockchain smart contracts to create a decentralized content management system for healthcare data across providers—the MedRec authentication log governs medical record access, while providing means for auditability and data sharing.

Another effort that has exciting possibilities is the Hyperledger Project's new Healthcare Working Group. The Hyperledger Project was started by the Linux Foundation to support blockchain-based distributed ledgers. Brian Behlendorf, the open source visionary, heads up the effort as executive director. With all of this momentum and incredible thought leadership working towards blockchain technology solutions in healthcare, I am very optimistic that the next three years will see rapid adoption of these solutions.

Digital transformation
The rapid pace of digital innovation continues to accelerate, and more than 90 percent of global businesses have initiated a digital business transformation strategy, according to a survey of 573 business leaders by Forbes Insights.

Technology is at the heart of digital transformation; however, digital transformation is not purely about technology. Rather, it uses technology as a means to an end and even goes beyond business. It is also about organizational culture, staff workflow and really a fundamental change in structure and how leaders think.

Every business needs to be on the path towards digital transformation, and this is especially true in healthcare. Technology for tech's sake is not the answer. Solutions need to be geared towards outcomes. New business models and the drive towards value-based care make digital transformation an imperative.

In healthcare, we have mountains of data and are beginning to share it across platforms, yet still we are not realizing the full potential of these data. There are actually three sets of customers to consider within the healthcare business as we look at transformation: administrative, clinical and the patients themselves. Few have mastered the consumer experience, whether as care providers and organizations or health plans. This shows the underutilized potential as well as the opportunity to those who are prepared for these changes.

A successful strategy will need to marry technology with people and process. Technology is often viewed as the biggest challenge, while simultaneously providing the necessary solutions for successful digital transformation. Oftentimes people, whether it is talent or capacity and capability, are overlooked when thinking through a digital transformation strategy. The top drivers identified by Altimeter in its report, "The 2016 State of Digital Transformation," shows that customer experience remains the top driver of digital transformation, but IT and marketing still influence technology investments.

Remember that defining the customer depends on the job needing to be done. Looking at the situation from a jobs-to-be-done framework means discovering needs on a situational basis—what is it the customer (whether patient or clinician) sees as a problem to be solved? Evolving customer behaviors and preferences can be a primary catalyst for change, and there is enormous pressure throughout the healthcare industry driving changes in behavior. Still, this is just as much about changing the culture of the healthcare business as it is about finding the right technology solutions. A good strategy is going to be balanced between these priorities.

Healthcare is going to be quite different in 2020 and beyond. Digital business transformation, enabled in part by emerging technologies such as blockchain, along with the advent of machine learning tools and artificial intelligence, are going to radically transform how care is both delivered and paid for. This will create substantial opportunity while also providing some significant challenges.

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