Artificial Intelligence: The Next Frontier in Health IT? (Part 2) | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Artificial Intelligence: The Next Frontier in Health IT? (Part 2)

September 12, 2017
by Rajiv Leventhal
| Reprints
Many will point to the massive potential of leveraging AI in healthcare, but there are complex challenges that need to be figured out first, experts say

Editor’s Note: Part 1 of this article, which covered how AI is being applied in healthcare right now, can be read here.

Although the use of artificial intelligence (AI) in healthcare is still very much at a premature level, prognosticators are quite bullish on how AI platforms could be incorporated in the future to improve patient care. Indeed, a 2016 study by market researcher Frost & Sullivan revealed that the market for AI in healthcare is projected to reach $6.6 billion by 2021, representing a 40 percent compound annual growth rate.

The study specifically noted that “Clinical support from AI will strengthen medical imaging diagnosis processes. In addition, the use of AI solutions for hospital workflows will enhance care delivery. Overall, AI has the potential to improve outcomes by 30 to 40 percent while cutting treatment costs by as much as 50 percent.” Researchers attested that AI is already being leveraged at a high level in other sectors, so it’s only a matter of time before “AI systems are poised to transform how we think about disease diagnosis and treatment.” They added, “By 2025, AI systems could be involved in everything from population health management to digital avatars capable of answering specific patient queries. On a global scale, in regions with high underserved patient populations, AI is expected to play a significant role in democratization of information and mitigating resource burdens.”

While the idea is to have AI systems learn and understand new medical functions, and in turn empower doctors to make better evidence-based decisions at the point of care, there has been significant discussion about whether or not the technology’s potential is so powerful that it could one day actually replace human doctors. Indeed, the issue has been written about in major media outlets, with one article in Fortune even quoting athenahealth CEO Jonathan Bush as saying, “The human is wrong so freaking often, it’s a massacre. Nobody ever goes after the radiologist—they’re wrong so often we don’t blame [th]em."

However, most healthcare observers will refrain from going as far down that road as Bush did. Many even will say that there is no chance AI will ever replace doctors. They attest that the job of artificial intelligence and machine learning is to mimic human cognitive functions, and to eliminate repetitive work for doctors—not eliminate the doctors themselves.

Jason Bhan, M.D., a family physician who is the co-founder of New York City-based AI company Prognos, cautions folks to not get too far ahead of themselves. “A lot of people are talking about replacing the doctor, but I am not at all convinced. It’s actually more like ‘beat the doctor,’ or ‘help the doctor in a friendlier way,’” he says. Bhan notes that as he’s going through his patient’s chart, what he doesn’t want is the computer to tell him what to do. “No doctor would be thrilled by that,” he admits. But, he adds, “We understand how to take care of our patients and we do want to be helped. That’s where there’s a huge opportunity for AI to help clinicians in their decision making.”

Bhan brings up an example of looking at a patient chart, where he can draw from his years of clinician experience and predict that the patient has a significant chance of getting diabetes in the next few years. “But machines can look at those patients, bounce it against millions of other patients like that, and say this patient has an 80 percent chance of developing diabetes in the next few years. That really changes my management,” he says. “With the clinical data and the lab data, you can hone that timeframe down into something that’s actionable. That’s where we see AI going.”

Meanwhile, senior executives from consulting firm Sapient Healthcare note that the CIOs they talk to within provider organizations, as well as the physicians in the trenches themselves, have expressed some concern that AI could replace physicians, but the consultants are working to quell those fears. “The real story is that AI will augment your [work] and let you do more interesting things. And there’s truth to that,” says Larry Lefkowitz, Ph.D., chief scientist at SapientRazorfish, a company under Sapient that launched this year. “Also, looking at the strengths and weaknesses of [AI], the technology can be very complementary. An example of that could be physicians and researchers using tools to get their hands on information more readily to help them make the decisions. In those cases, the system isn’t making the decision and the researcher doesn’t want to spend loads of time trying to find the right information, so you have a win-win,” says Lefkowitz.

Peter Borden, managing director at Sapient, notes that people are using the term “augmented intelligence”—meaning that AI is not replacing people, but rather trying to make things more effective. “But that fear of how it will affect people’s lives has to get figured out,” Borden says. “As strong as the business case might be for an organization, if the people internally don’t know how it will affect them, it won’t get adopted.”

Lefkowitz gives an example himself of how AI could supplement a radiologist’s work, as radiology is one area in healthcare where AI and machine learning are already being leveraged in critical situations. He says that numerous studies have shown that a human has a certain error rate and an automated system has a certain error rate, but when used together they have a much lower error rate. In particular, he explains, “Radiologists almost never get a false-positive [result on a mammogram], so if they say it’s a cancer or whatever it might be, they are almost always right, but they’re likely to miss many cases. But on the flip side, the machine learning approaches almost never get a false-negative and tend to be more conservative. So you can combine that and have the machine learning take the first pass at it, [meaning] virtually nothing will get through, and you will be able to present a much smaller number of cases for a human analyst to then look at. So you are again allowing the human to focus on what they do best,” says Lefkowitz.

While clinician pushback may or may not be a real barrier to AI being leveraged more in healthcare, other concrete challenges do exist. Experts who were interviewed for this article all say that access to “good and clean” data remains a real problem. In fact, Bhan calls it the “biggest issue we have right now in this space.” Pundits point to healthcare data sets not yet being big enough, and the correct answers that will be learned are often ambiguous or even unknown in their current state. Much of this stems from the human body being quite complex, with lifestyle and environmental functions playing a role but being hard to measure.

What’s more, the comfort level of humans using the technology could also pose challenges. Borden says that in his conversations with CIOs, it’s not necessarily that there is pushback towards AI, but rather they want to know that it’s supported by the business. And for that to be the case, there has to be well-defined strategies around leveraging AI that incorporate easing people into the program. “Certainly, the idea of having a holistic view of data in order to do analyses is core to the roadmaps for every CIO. So we don’t see much pushback on that,” Borden says. “But the businesses are weary; they know that there’s huge potential, but they intuitively feel the risk about what this change will mean. It’s a change management program, so easing the program into the organization is key,” he says.

Bhan appoints out that everyone is quick to say that healthcare is 10 years behind other industries in terms of adopting technology, so it will certainly take time to leverage AI at a high level. “I would never go to a doctor and say ‘here’s some awesome tool that will tell you the likelihood of a patient getting a disease;’ they are simply not ready for that. The entire system has to ease their way into it, and you do that by finding innovators,” he says.

These innovators could be in the payer, pharma, or provider industry, and the key is to find those innovators and get them to buy in, Bhan says. “You just need to proceed slowly, since doctors are a conservative lot in general, and for the right reason, since it is important not to make mistakes and validate why you make certain decisions. This is not like picking up an iPhone and starting to use it. You need to put the patient first. There’s a lot of complexity,” he says.


2018 Seattle Health IT Summit

Renowned leaders in U.S. and North American healthcare gather throughout the year to present important information and share insights at the Healthcare Informatics Health IT Summits.

October 22 - 23, 2018 | Seattle


ASCO Picks IBM Watson Exec to Lead CancerLinQ

August 10, 2018
by David Raths
| Reprints
Big data platform collects and analyzes data from cancer patients at practices nationwide

The American Society of Clinical Oncology (ASCO) has named a former IBM Watson executive as the new CEO of its CancerLinQ big data platform.

Cory Wiegert was most recently vice president of product management for IBM Watson Health. Prior to joining IBM, Wiegert held positions with Sterling Commerce, Siebel Systems Inc., Centura Software and Safety-Kleen.

Kevin Fitzpatrick stepped down as the nonprofit CancerLinQ’s CEO in April 2018. Richard Schilsky, M.D., who was serving as interim CEO of CancerLinQ, will continue his role as ASCO's chief medical officer.

CancerLinQ collects and analyzes data from cancer patients at practices nationwide, drawing from electronic health records, to inform and improve the quality of cancer care. Its database contains more than a million cancer patient records. The effort has two major components:

• The CancerLinQ quality improvement and data-sharing platform for oncology practices,

• CancerLinQ Discovery, which provides access to high-quality, de-identified datasets derived from the patient data to academic researchers, non-profit organizations, government agencies, industry, and others in the oncology community.

CancerLinQ LLC also has established a number of collaborations with government and nonprofit entities -- including American Society of Radiation Oncology, Food and Drug Administration, and the National Cancer Institute -- as well as industry through its collaborators AstraZeneca, Tempus, and Concerto HealthAI.

In a statement, ASCO CEO and CancerLinQ LLC Board of Governors Chair Clifford A. Hudis, M.D., said Wiegert’s arrival “comes at a pivotal time, as we are quickly building on and improving CancerLinQ's core quality improvement platform for oncologists and data analytics services for the broader cancer community."

As CEO, Wiegert will be tasked with developing new solutions to help oncology practices improve the day-to-day care they provide their patients and continuing to serve CancerLinQ collaborators.




More From Healthcare Informatics


A ‘Google’ for Clinical Notes Draws Interest

August 8, 2018
| Reprints
Developed at the University of Michigan, EMERSE allows users to search the EHR’s unstructured clinical notes
Click To View Gallery

Those of us who cover healthcare informatics often hear clinicians and researchers talk about the problems involved in doing analytics or research on unstructured data in clinical notes. That was why I was intrigued when I saw that informatics teams at the University of North Carolina School of Medicine are implementing a tool called EMERSE (Electronic Medical Record Search Engine), which allows users to search free-text clinical notes from the electronic health record (EHR). They describe it as being like "Google" for clinical notes. 

But then I noticed that the tool was actually created quite a while ago, in 2005, at the University of Michigan, and has been in use there ever since. So I reached out to its developer, David Hanauer, M.D., a clinical associate professor of pediatrics and communicable diseases at the University of Michigan Medical School. He also serves as assistant director for clinical informatics in UM’s Comprehensive Cancer Center’s Informatics Core as well as associate chief medical information officer at the UM Medical Center.

Hanauer told me that the developers of EMERSE at Michigan have a grant from the National Cancer Institute to further develop the tool and help disseminate it, with a focus on cancer centers around the country. “We are about one year into the grant,” he said. “We have spent the last year cleaning up the infrastructure to make it even easier for people to adopt. We have been working hard on technical documentation. When we started it, we had almost no documentation; now we have substantial and detailed documentation about how to implement and run it.”  

The five sites implementing EMERSE as part of the grant are the University of North Carolina, University of Kentucky, University of Cincinnati, Case Western Reserve University and Columbia University.

I asked Hanauer if health systems continue to struggle with unstructured data in clinical notes. “They all absolutely struggle with it,” he said. “They have mostly been ignoring it, to tell you the truth. That is why we believe and hope EMERSE will fit well into this environment of people needing different tools.”

I also asked him to describe some of the use cases. Most generically, anybody who needs to look through the chart and doesn’t know exactly where to look can get benefit from it, he said. He described three categories of users: research, clinical care and operations. “For example, in research you could use it for cohort identification. You want to find patients who meet your needs when it comes to a research study. This is important in part because ICD codes, the go-to way people often try to identify a cohort, are often inaccurate and non-specific.”

According to the EMERSE web site, for studies in which eligibility determination is complex and may rely on data only captured within the free text portion of documents, EMERSE can be a rapid way to check for mentions of inclusion/exclusion criteria.

In another example, EMERSE also can be used to help find details about a patient rapidly, even during a clinical visit. “For example, if a patient mentions that a certain medication helped their migraine three years ago but can’t remember the name, just search the chart for 'migraine' and find that note within seconds,” the web site notes. Cancer registrars can use EMERSE for data abstraction tasks, including difficult-to-find information such as genetic and biomarker testing.

Hanauer said at Michigan, clinicians have a way to access EMERSE from their Epic EHR. “If you have a patient’s record open, you can click a button, it will log you into EMERSE and bring that patient’s context over, and you can start searching in just of a few seconds.”

In 2005, the platform was written to work with a homegrown EHR. When UM transitioned to Epic in 2012, Hanauer and team used that as an opportunity to make it more powerful. “When we went live with Epic, it became clear there were some architectural limitations that were probably going to limit the future power of the software,” he recalled. “We leveraged the design and concepts and rewrote it from scratch. But even though we were going to work with Epic, we designed it specifically so it would not be tied to any particular EHR.”

Because it deals with patient records, security and audit logs have to be taken very seriously. Every time you log into EMERSE, you come to an attestation page. “You have to declare why you are using it for this session,” Hanauer explained. “We have tried to make it as simple as possible. Almost every institution that does research now has an electronic IRB system, so we have a way you can pull a user’s IRB-approved study into the EMERSE database, and a list appears of that user’s studies only. The user can click on it, record that use, and move forward.” There also are quick buttons for common administrative use cases.

I asked Hanauer if other academic medical centers had developed similar search tools. He said some have created local tools. “The main difference with EMERSE is that it is proven it can work elsewhere. (It was used at the VA in Ann Arbor, Mich., on the VistA system.) “We have a long track record of use and have been working on the infrastructure to disseminate it,” he said. “We are giving it away at no cost, but it is almost like running a software company, where you have to have a web site, user documentation, and system administrator documentation. To me, it doesn’t make a lot of sense for others to reinvent the wheel when this is something we have invested millions of dollars in at this point.”

He stressed that although the grant project is focused on five cancer centers, they are giving the software away at no cost, and are glad to help anybody interested in getting it up and running. “One of the key challenges is that the users can’t control whether it gets deployed or not,” he said. “Our biggest challenges is not the users, who are contacting us and asking us for it, but getting this through local IT leadership, and that is a big hurdle.”

Why would CIOs be opposed to deploying this tool? “I think their plates are full and a lot of times people are looking for vendor solutions,” he surmised.  “I also think that often people don’t understand what the issues are. Some people think they will just get some off-the-shelf NLP software. But I can assure you that that software will not be able to do the kinds of things that EMERSE can do. That is partly because a lot of medical documents are not in natural language. Medical documents are anything but. They are a mess.”



Related Insights For: Analytics


Anthem Expands $500M Deal with IBM with Focus on IT Automation, AI

July 26, 2018
by Heather Landi
| Reprints

Health insurer Anthem has expanded its services agreement with technology leader IBM with a focus on using artificial intelligence (AI) and automation to improve operational efficiency and modernize technology platforms.

With this collaboration, Armonk, New York-based IBM and Indianapolis-based Anthem, one of the largest U.S. health insurance coampnies, will work together to help drive Anthem’s digital transformation and deliver an enhanced digital experience for its nearly 40 million consumers, Anthem said in a press release.

In 2015, Anthem entered into a five-year, $500-million-dollar strategic technology services partnership with IBM in which the technology giant provided operational services for Anthem’s mainframe and data center server and storage infrastructure. As part of that agreement, Anthem has been able to leverage IBM Cloud solutions to increase the ease, availability and speed of adding infrastructure to support new business requirements, the company said.

Under the expanded agreement, IBM will provide Anthem with enterprise services for its mainframe and data center server and storage infrastructure management. In addition, IBM will work with Anthem towards creating an AI environment which will allow for an automated infrastructure providing 24/7 digital capabilities. This will bring greater value and access to Anthem's consumers, care providers, and employees, Anthem said.

IBM and Anthem will also continue to work together on IT automation. Since 2015, the two companies’ have implemented over 130 bots, automating over 70 percent of the monthly high volume repetitive tasks. This includes bots that can identify when a server is reaching capacity to shift workloads to other less utilized servers ensuring that work is not impacted. This capability has improved systems availability as well as freed up resources to work on higher-value projects, Anthem said in a press release.
“We are seeing a dynamic change in the healthcare industry, requiring us to be more agile and responsive, utilizing advanced technology like AI to drive better quality and outcomes for consumers,” Tim Skeen, senior vice president and chief information officer, Anthem, Inc., said in a statement. “Our continued strategic partnership with IBM will help establish a stronger foundation for Anthem to respond to the changing demands in the market, deliver greater quality of services for consumers and help accelerate Anthem’s focus on leading the transformation of healthcare to create a more accessible, more affordable, more accountable healthcare system for all Americans.”

“The collaboration between IBM Services and Anthem has already laid the groundwork to improve healthcare processes and quality,” said Martin Jetter, senior vice president, IBM Global Technology Services. “Our latest agreement will accelerate Anthem’s growth strategy and continued leadership as one of the largest healthcare insurance companies and provide a solid path to bringing new efficiencies in driving digital transformation.”


See more on Analytics