- Only a few short years ago, healthcare organizations were wondering what exactly “big data” was and why they had to care about it.
As the industry moves into 2017, they might have similar questions about the definitions of terms like “blockchain,” “the Internet of Things,” and “artificial intelligence” – but the use cases for these cutting-edge technologies are rapidly becoming crystal clear.
From precision medicine and business intelligence to data security and patient engagement, the IoT, AI, and blockchain all hold exciting promises for providers, patients, and researchers looking to move their big data hoards from repositories to real results.
The healthcare sector must join its peers in other industries to leverage these new applications for big data, according to a pair of reports from the White House and Gartner, Inc., in order to take advantage of the nearly-limitless opportunities for lowering costs, improving outcomes, and achieving quality goals.
Artificial intelligence will soon “improve the world”
While android physicians and self-driving gurneys are likely still several decades away, basic artificial intelligence programs are already making an impact on everyday society. Digital personal assistants are available on almost every smartphone, and chatbots, tailored advertisements, and voice-recognition systems are becoming increasingly common in the customer service industry.
In healthcare, breakthroughs in machine learning are starting to produce the first generation of intelligent clinical decision support tools that hold more knowledge than any human expert, and patients – particularly those with cancer – are starting to benefit from data-driven treatment plans and personalized care.
But artificial intelligence is only in its infancy, say the Executive Office of the President National Science and Technology Council Committee on Technology, and there is staggering potential for AI to revolutionize healthcare and other industries.
“Experts forecast that rapid progress in the field of specialized artificial intelligence will continue,” wrote US Chief Technology Officer Megan Smith and John P. Holdren, Assistant to the President for Science and Director, Office of Science and Technology Policy.
“One area of great optimism about AI and machine learning is their potential to improve people’s lives by helping to solve some of the world’s greatest challenges and inefficiencies. Public and private sector investments in basic and applied R&D on AI have already begun reaping major benefits to the public in fields as diverse as health care, transportation, the environment, criminal justice, and economic inclusion.”
The report suggests that self-driving cars may help to improve quality of life and access to care for elderly or immobile patients, and highlights the potential for precision medicine to help patients live longer, healthier lives. It also cites several examples of AI in action within the healthcare industry.
“At Walter Reed Medical Center, the Department of Veteran Affairs is using AI to better predict medical complications and improve treatment of severe combat wounds, leading to better patient outcomes, faster healing, and lower costs,” the report says. “The same general approach—predicting complications to enable preventive treatment—has also reduced hospital-acquired infections at Johns Hopkins University.”
“Given the current transition to electronic health records, predictive analysis of health data may play a key role across many health domains like precision medicine and cancer research,” Smith and Holdren envision.
Speed, efficiency, precision, and volume are the areas where machine learning and AI can make an impact on activities critical to patient care, added the Gartner report. Smart machines may be able to reduce error rates by up to 30 percent for tasks that require high precision, which could result in lower costs.
Additional benefits for the healthcare industry may include increased patient safety, earlier and more accurate diagnoses, and fewer missed opportunities to deliver care based on recommended protocols.
There are many challenges standing in the way of achieving these objectives, however, starting with safety, governance, and regulation. Rulemakers and legislators will need to create guidelines that ensure artificial intelligence is thoroughly tested and vetted before being released into the world, and that is it deployed in ways that do not pose risks to humankind.
The White House report acknowledges a long history of dystopian predictions about the rise of hyper-intelligent machines, but stresses that an artificial intelligence takeover is likely to remain in the realm of fiction.
Instead of fearing a revolution, developers should focus on creating AI tools that can enhance the human experience through automation, and policymakers should carefully consider rules and regulations that ensure public safety while maximizing the potential for AI to contribute to society.
Blockchain is still in “alpha testing,” but interest is growing
Blockchain is one of Gartner’s top ten technologies to watch in 2017 and beyond, but the company isn’t throwing all its weight behind this system of using distributing information to validate transactions, such as a financial transfer or an edit to the contents of a file.
"Distributed ledgers are potentially transformative but most initiatives are still in the early alpha or beta testing stage," said David Cearley, Vice President and Gartner Fellow.
The report points out that Bitcoin is one of the only successful blockchain applications at the moment, and points out a number of barriers very familiar to healthcare providers: insufficient data standards, a lack of interoperability, questions over how to achieve scale, and concerns about security.
“A critical aspect of blockchain technology today is the unregulated, ungoverned creation and transfer of funds, exemplified by bitcoin,” the report says. “It is this capability that funds much of blockchain development, but also concerns regulators and governments.”
“The debates about permissioned, permissionless, hybrid and private ecosystems and governance will force a more-robust analysis of distributed ledgers. As these analyses are completed, workable solutions will evolve.”
The Office of the National Coordinator has expressed keen interest in how those solutions may evolve to help the healthcare industry, where privacy is paramount and accurate, up-to-date data is essential for decision-making.
Earlier this year, several dozen blockchain experts shared their visions for the use of blockchain in healthcare, highlighting opportunities for data reconciliation, collaborative patient engagement, health information exchange, and quality data reporting.
The winning papers hinted at a big data environment where patients could create and control a community of providers, family members, and caregivers who could view, edit, and share a centralized personal health record – with full confidence in the security and privacy of their data.
At Beth Israel Deaconess Medical Center, blockchain is already starting to make this future a reality, said CIO John Halamka in his organization’s entry. A system called MedRec is helping users assign permissions for sharing and access according to their preferences.
“Providers can add a new record associated with a particular patient, and patients can authorize sharing of records between providers,” Halamka and his team explained. “In both cases, the party receiving new information receives an automated notification and can verify the proposed record before accepting or rejecting the data. This keeps participants informed and engaged in the evolution of their records.”
“MedRec prioritizes usability by also offering a designated contract which aggregates references to all of a user's patient-provider relationships, thus providing a single point of reference to check for any updates to medical history.”
This type of technology may help patients keep sensitive mental health or substance abuse data from certain parties, ensure that medications and allergies are up-to-date across disparate organizations, and engage in more shared decision-making with caregivers of their choosing.
But much work still needs to be done in order for organizations to adopt this approach on a larger scale, Gartner says, starting with the fact that many potential customers – and vendors, for that matter – don’t really understand what blockchain is, what its limitations may be, and how to integrate the technology into existing infrastructure.
“Use extreme caution when interacting with vendors that have ill-defined/nonexistent blockchain offerings,” the report urges. “Ensure you are clearly identifying how the term 'blockchain' is being used and applied, both internally and by providers.”
“Resources permitting, consider distributed ledger as proof-of-concept development. But, before embarking on a distributed-ledger project, ensure your team has the cryptographic skills to understand what is and isn't possible. Identify the integration points with existing infrastructures to determine the necessary future investments, and monitor the platform evolution and maturation.”
The Internet of Things can turn big data into better decisions
Healthcare is a prime market for the Internet of Things, a web of Internet-enabled devices, apps, interfaces, and sensors that are already collecting patient-generated health data (PGHD) including blood sugar readings, body weight, heart rates, fitness metrics, sleep patterns, and medication adherence habits.
The data created by this growing category of devices is problematic for providers: not only is it poorly standardized, but it’s so voluminous that it’s often impossible to glean any actionable insights from the torrent of data within a reasonable time frame.
Providers are reluctant to accept PGHD into their workflows because they fear drowning in data that may or may not prove its value.
According to a July survey from Strategy Analytics, forty-two percent of participants from across multiple industries believe that there is simply too much IoT data to deal with efficiently, 28 percent can’t capture the data reliably, and 26 percent lack the analytics capabilities to extract the insights they want.
But some organizations are starting to learn how to deal with the deluge, and are creating better analytics and smarter EHR workflows to highlight the most important pieces of data.
If developers can convince providers to harness the IoT for patient care, it may produce a number of benefits, including nearly real-time access to data for chronic disease management, improved methods of patient engagement, and more personalized treatment plans based on consumer preferences and needs.
Gartner also notes that there is a large market for “embedded intelligence,” which includes items like home appliances, thermostat and security systems, or hospital equipment that transmit and receive data through an internet connection and may leverage AI and machine learning to make adjustments or complete routine tasks.
“For example, today's digital stethoscope can record and store heartbeat and respiratory sounds,” the report says. “Collecting a massive database of such data, relating the data to diagnostic and treatment information, and building an AI-powered doctor assistance app would enable doctors to receive diagnostic support in real time.”
Generally, the healthcare industry does not yet have big data analytics capabilities to make the Internet of Things a commonplace tool for patient care, but excitement about the IoT’s potential is growing. Funding for IoT and big data analytics projects is on the rise, according to Mercom Capital Group, and these new technologies are even grabbing the attention of the US Senate.
The IoT is a $410 billion opportunity just waiting for the healthcare sector and other industries to leverage their big data. It is likely that the Internet of Things, along with blockchain technology and artificial intelligence, will start to come into their own as the decade draws to a close, opening up the potential for drastic improvements in care quality, the patient experience, and providers’ ability to make informed, actionable decisions.