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At Conference, Experts Address Implications of Intelligent Automation in Healthcare

September 13, 2017
by Heather Landi
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In order to address transformative issues in the healthcare industry, healthcare provider organizations, payers and life sciences companies need to be agile, need to drive disruption utilizing technology, and need to be more analytically driven, according to a panel of healthcare industry leaders. During a panel discussion at New York City-based consulting firm KPMG’s Annual NY Health and Life Sciences Summit, which took place at KPMG’s Manhattan office, healthcare industry thought leaders tackled the impact of disruptive technologies, such as intelligent automation and robotics, in healthcare.

Joe Parente, principal at KPMG, kicked off the summit by offering a general overview of the current moment in healthcare and the role that intelligent automation, and even artificial intelligence (AI) and machine learning, can play to address the most pressing challenges in healthcare. Parente noted that healthcare provider organizations are challenged with tremendous operating pressures with rising costs and shrinking reimbursements. “What will tomorrow’s successful healthcare organization look like? Agile,” he said, noting that adaptability will be critical moving forward.

“This is a time of uncertainty, with regard to legislation, regulations, increasing competition, driving the focus on cost reduction, along with an ongoing shift from volume to value, and improving quality of care and optimizing reimbursement,” he said. To face these challenges, healthcare organizations will need to see disruption as an opportunity, not a threat, and should drive the disruption, he said. “Organizations can use analytics to find variance in clinical process, re-engineer those processes and then use automation to be more efficient,” he said.

During the panel discussion, Lita Sands, an independent and industry consultant, Dusty Majumdar, chief marketing officer at IBM Watson Health and Paresh Shah, M.D., vice chair of quality and innovation in surgery at New York City-based NYU Langone Health gave their perspectives on the current adoption of intelligent automation, robotics and AI in the healthcare space.

Providing the vendor perspective during the panel discussion, Majumdar with IBM Watson noted that AI in healthcare is “red hot.” “In terms of where we see traction, we see a significant amount of traction in imaging. Radiologists, in our experience, they want something like Watson to help them detect that legion or to characterize a nodule that’s in the early stage of cancer. We do see it across imaging, see it across oncology, in terms of being able to stratify the patient with the right clinical trial, and we see it in genomics in terms of linking the mutation profile to the right clinical trial and the right treatment and also some advanced ways of looking at the genomic profile,” he said.

Majumdar’s comments come a week after Stat News published an investigative piece on IBM Watson’s shortcomings, contending that the artificial intelligence supercomputer as not lived up to its potential. As Healthcare Informatics Managing Editor Rajiv Leventhal noted in a news story about the Stat News report, the piece examined Watson for Oncology’s use, marketing, and performance in hospitals across the world, from South Korea to Slovakia to South Florida. The in-depth article included interviews with doctors that have deployed Watson at prominent healthcare institutions as well as other healthcare experts—many of whom seem far from thrilled about the results Watson has delivered so far.

Offering the healthcare provider perspective on where intelligent automation and AI are gaining traction, Shah said, “At the very granular, foot-solider level, that’s where it’s the hardest to get some traction because they are so consumed with the day-to-day of what they are doing. Interestingly enough, when a provider sees a tangible benefit, they are ready to adopt it. The hurdle is just getting it to them, to show them that it’s added value. Once they see it, they will take it on,” he said, adding, “Things like decision support, such as, if I’m a radiologist sitting in front of a screen, and I see something, if I could push a button and have it verify what I’m seeing, or push a button and have it give me three ideas that I haven’t even thought of, they love that.”

Shah continued, “Or, if I’m an internal medicine doctor, and I may or may not know what is the best option for treating diabetes for this particular patient. When I graduated medical school, there were only four drugs, outside of insulin, that were used to manage diabetes. Now, there’s a couple of dozen drugs. One of the challenges is that, at the provider level, the actual quantity of the information has expanded so exponentially giving providers a tool or vehicle in which they can access, categorize and curate that information, that is really valuable.”

The panelists also acknowledged that organizations need a structure around technology adoption in order to effectively prioritize projects. During an earlier keynote address, Shah discussed NYU Langone Health’s plans to leverage intelligent automation and robotics, particularly in its new Kimmel Pavilion, which will feature TUG robots to distribute food and medications, digital wayfinding tools for patients and families and Brainlab, an audiovisual medical communications system for the surgical and procedure rooms. He also detailed some of the health system’s deep learning IT initiatives to utilize data analytics and machine learning to reduce clinical variability and improve quality of care while reducing costs.

“For us, it started with our transformation to value, that was the primary driver and the mission that enabled us to prioritize different projects,” Shah said. “It was really around moving from volume-based to a value-based system. And, the first simple pass of that was around cost reduction, waste elimination, with the objective being wanting to improve care quality and reduce the cost at the same time. From an operational perspective, that’s how we looked at it. Some of that was easy and some of that turned out to be quite hard, and required some really in-depth analytics to understand it. And now we’re moving to the next generation of quality improvement, which is thinking beyond just what we currently do better, but thinking about how we can actually change how we do it.”

Shah provided an example of how the health system’s Value-Based Management (VBM) program, which serves as the oversight for many of these projects, leverages technology to address problems. Health system leaders found that many hospital patients are readmitted because they get dehydrated. “The current mechanism to handle that in our system is those patients come through the ER, because in the physician office, due to regulatory issues, you can’t start an IV, even though the physician’s office is in building with the hospital,” Shah said. “So, in order to understand how big the problem was, we used our data warehouse and we applied intelligent analytics to look at what the scope of the problem was, not just episodes of reoccurrence, but looking at what the true cost was, what that translates into, and how do we act on it?” The insights derived from that analytics work motived the health system to set up a process to provide patients with hydration in the outpatient setting to avoid patients being readmitted due to dehydration.

As Healthcare Informatics’ Leventhal addressed in a recent article on the opportunities for artificial intelligence in healthcare, one of the key concerns among clinicians is that AI and machine learning will eventually replace doctors. IBM Watson Health’s Majumdar addressed this issue, referring to it as a “myth” around AI. “Our belief is that it will augment humans. If we can augment the oncologist, with the right data at the right time, based on 7,000 cancer-related publications per day, based on the explosion of genomic data, based on all the different publications around treatment that are out there and around drugs, we think we can augment the oncologist, the pathologist, the surgeon to take the right steps.”

He added, “There are some more subtle challenges in radiology. It’s not just about recognizing a tumor, but the characteristics of it. We’re just beginning to get there with machines; it’s going to be a long time before a machine can actually replace the critical judgment of the radiologist who has seen 10,000 similar tumors. You need a lot of data, a few million tumors, for the machine to learn from. We believe that we are, at this point, augmenting radiologists, oncologists, in a big way with cognitive intelligence, what we call cognitive capabilities, and this is a journey. In my opinion, it’s at least a couple of decades’ long journey before we can think of machines completely replacing physicians.”

Shah also noted that adopting technology with cognitive capabilities is as much as process issue as a technology issue. “It’s a process, and an evolution. As you build trust in this technology and as the technology demonstrates enough reliability to engender that trust, you will allow it more freedom. We’re not at the point of cognitive independence; and nor are we trying to get there. We’re trying to maximize the existing potential. With radiologists, for example, if you get yourself lulled into this sense of confidence, or even complacency, around what it’s spitting out at you, you run the risk of propagating error, rather than reducing error. That’s true to everything we’ve done to now. That isn’t new to AI. That’s a process issue more than a technology issue. I think you build processes to protect against that, and you train and educate around that.”

On the subject of disruptive technologies in healthcare, the panelists also discussed the impact of new entrants into the market, such as Verily, Amazon and Apple. Sands, a consultant in the life sciences space, says there is an opportunity for these technology companies, as well as payers, to leverage technology to change consumers’ behavior and, subsequently, have a profound impact on population health. “You have some payers trying to reinvent itself themselves. For example, the CEO of Aetna has gone out there and said, ‘We’re going to take the perspective that we need to move from the exam table to the kitchen table.’ You probably read they made a big investment with Apple watch, using this data to help people change behavior. That’s a great example of a player that’s being innovative.”

She continued, “And then of course, we’ve been reading a lot about Amazon, and I think they call their division 1492, and they are going into the pharma space. With Amazon moving into the space, I’m enthusiastic about it; it’s an opportunity to remove barriers. You could extend it into all sorts of avenues in terms of being able to do clinical studies in the home.” What’s more, Sands said she sees opportunities for technology companies in the life sciences and pharma space to put together claims data with behavioral data, “which is where the nirvana is. “Once you have that, and then use AI, you can now start to create tailored, clinical pathways and we can quickly monitor and adjust a medication. It’s been proven that with access to data, insights and action-driven behavior, you can dramatically change your health,” she said.

Moving forward, Sands says life sciences companies need to change their strategy and become more analytically-driven to succeed in this new, disruptive world. “We’re moving into the world where data is the new currency; data and insights, we have to come to the table with that, it’s not just our drugs, it’s about the whole patient. If that’s what the model looks like and we’re discovering that personalized data from technology impacts human behavior, let’s go to the beginning; let’s start with zero and change how we do our clinical trials, augmented with technology, let’s not be afraid of this,” she said.

The panelists also offered their perspectives on lessons learned from early adopters of these technologies.

IBM Watson’s Majumdar said partnership is a key to success. “IBM doesn’t do anything on their own in healthcare,” he said. And, he also noted, “As we are applying AI to imaging, we have to remember that the imaging technology is not sitting still, it’s also evolving. The MRI machines, and each of these advancements in CT or MRI, are improving the specificity, the accuracy of diagnosis. The key is to tie advancements in AI with the changes and advancements in imaging.”

Shah reiterated the need for provider organizations to have a strategic plan to help prioritize technology-driven projects. “The second lesson is, fail fast,” he said. “One of the biggest challenges is that there is so much out there. Provider organizations are inundated with vendors, of all sizes and shapes, giving you these sexy, appealing ideas, but you’re going to engage with something, make sure that your pilot is able to demonstrate its true value quickly, and if not, then cut and run and move on.” Shah also added, “You have to a have a clinical champion. It can’t be something that’s dictated from on high from the C suite. There needs to be a ground level clinician who wants this to happen; because that’s the person who is going to help you with change management and help you with the clinical case as well as the business case.”



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ASCO Picks IBM Watson Exec to Lead CancerLinQ

August 10, 2018
by David Raths
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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.




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A ‘Google’ for Clinical Notes Draws Interest

August 8, 2018
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Developed at the University of Michigan, EMERSE allows users to search the EHR’s unstructured clinical notes
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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.”



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

July 26, 2018
by Heather Landi
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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.”


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