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At One North Carolina Health System, Transforming the IT Infrastructure to Meet Future Needs

June 7, 2017
by Heather Landi
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This Healthcare Informatics Special Report as part of the May/June issue details one health system's data management strategy
courtsey: Wake Forest Baptist Medical Center

At forward-thinking healthcare organizations seek to support new technologies, applications and services, such as advanced analytics to support precision medicine or population health initiatives, many are finding that their existing, older IT infrastructure may be an impediment to driving innovation forward. The volume of data that hospitals create and manage is growing exponentially, many health IT experts say, driven by the use of electronic health records (EHRs), diagnostic imaging systems, and mobile applications as well as federal regulations mandating the ongoing digitization of healthcare.

This unprecedented data growth, and the need to effectively leverage data to its potential, is proving to be a significant challenge for healthcare IT leaders. Effective data management and strategic data governance can be critical in order to move forward with operational improvements and to provide a high level of service and performance to clinician end users. To this end, many healthcare provider organizations have undertaken modernizing their IT infrastructure to meet future technology needs.

When Chad Eckes, executive vice president and chief financial officer, joined the Winston-Salem, N.C.-based Wake Forest Baptist Medical Center in March 2014 as CIO, he encountered significant legacy IT infrastructure challenges, and these challenges were impacting the organization’s ability to focus on its strategic priority of enhancing patient care versus maintenance and support. The aging IT infrastructure was difficult to support, there were sprawling data centers running out of space and critical projects were being delayed due to infrastructure constraints, he says.

“The prior CIO had chosen to direct investments in the IT organization toward two very large-scale IT software projects, an Epic EHR implementation and an Oracle PeopleSoft implementation, and had stopped putting proper investment into the data center, the networks and the core infrastructure there. There was no master architectural blueprint for the infrastructure, as a result, it grew haphazardly, and it was an aging and failing infrastructure,” he says.

Wake Forest Baptist Medical Center is an academic medical center and health system comprised of Wake Forest School of Medicine and an integrated clinical system with three hospitals and nearly 300 clinics serving 2.5 million residents in a 24-county area in northwestern North Carolina. The health system conducts 1.3 million patient clinic visits, 44,000 inpatient stays, 50,000 surgeries and 162,000 emergency department visits per year. The system also includes Wake Forest Innovations, a commercialization business. All told, the organization has 14,000 employees comprised of 1,200 physician faculty, 1,000 affiliated physicians and 1,900 students. In addition, the health system’s network also includes over 18 affiliated community hospitals, more than 100 clinics, physician practices and outpatient services serving one million patients annually.

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As then-CIO, Eckes’ first order of a business in 2014 was conducting an assessment of the IT environment. “There were many applications issues that had to be addressed. One of the things that we uncovered was a mounting infrastructure risk that was impacting the organization, and the second was a severe issue with analytics and reporting.”

Chad Eckes

The assessment demonstrated that 64 percent of the IT infrastructure was over seven years old, Eckes says, and 12 percent was more than 11 years old, and he adds, “How that was manifesting itself on the operations of the company was that there were significant downtimes on a regular basis. We were showing an uptime percentage of 84 percent out of that infrastructure.“

The IT infrastructure at the time required 1,500 servers and multiple storage area networks. “All the servers were your legacy racked and stacked,” Eckes says. Further, the organization had made limited progress on server virtualization.  “We were about 22 percent virtualized,” he says. And, Eckes adds, “We did not have a business continuity plan and disaster recovery plan for the systems, so that was core to our issues—when we were down, we were hard down, and that led to a lot of manually processing when taking care of patients.”

On the network side, the organization had many end-of-life products in the medical centers. “As an example, on our main campus we have 798 different networks, and 131 networks that had not received patch updates since 2010; not because we didn’t desire to, but because the products were so far end-of-life that we couldn’t patch them anymore,” he says.

For Wake Forest Baptist Medical Center’s executive leaders, modernizing the IT infrastructure was an imperative, and Eckes says organizational leaders considered two options. The first option for modernizing the IT infrastructure was what Eckes refers to as “the old-school way,” or traditional technology, and the second option was to implement a converged infrastructure.

“From a cost, risk and a speed-to-value perspective, all signs pointed to doing this with converged infrastructure,” he says.

After reviewing technology solutions providers, executive leaders decided to adopt a converged infrastructure approach, which is a data center management approach to consolidate computer, networking and virtualization silos into a single solution to support all of the organization’s applications. The health system worked with Dell EMC to develop a strategic plan for a new infrastructure and application platform, which resulted in the deployment of Dell EMC’s Vblock Systems to provide the infrastructure for the organization’s new software-defined data center, Wake Cloud.

“One of the key top reasons we choose this route was speed. Once the planning was done, it was 45 days and the Vblock System was designed to our specifications. Once the Vblock System was delivered to our doorstop, we were able to plug them in, and within two days, we were up and running and able to start migrating over our applications onto them,” and he adds, “That same process would have taken us months doing it in a traditional way.”

Implementing a converged infrastructure also required less staffing. “We would have had to add nine people to our infrastructure team to execute the same projects, doing it the ‘old school’ way. So, this saved us on the staffing front, and we were also able to target our retraining of our current staff on to the converged platform,” Eckes says.

All told, the process took about 18 months, with the biggest task in the migration involving transitioning 1,131 applications onto the converged infrastructure environment from the legacy environment without disrupting patient care.

Improving Efficiencies and Supporting IT Innovation

As a result of the modernization project, Wake Forest Baptist Medical Center has enhanced the performance of its Epic EHR and achieved significant efficiencies by reducing maintenance cost and improving uptime. “We’ve gone from an 84 percent uptime to close to a 100 percent uptime. And, when you’re talking about lives being dependent on the systems that we’re running or the bedside monitors that are hooked into our environment, it starts becoming priceless because it literally can be life or death,” Eckes, who transitioned to the CFO role in April 2015, says.

As a result of the project, the organization will reach 96 percent virtualization, up from 22 percent, in just 18 months, with enables virtualized desktops. Other efficiencies that have resulted from the project include driving maintenance and support costs down from 44 percent of the IT budget to just 10 percent, better utilization of the data centers and reducing 70 percent of the IT team’s time devoted to routine support to allow more time for creating added value. Further, the disaster recovery plan has improved with automatic failovers.

Further, the organization rolled out an upgrade of its Epic platform on top of the converged infrastructure environment which has enhanced performance, such as improved latency speed for better application response times, and an overall 30 percent performance improvement for end users. Saving seconds on every click inside Epic can add up to a significant amount of time saved for clinicians and staff throughout the day, Eckes points out.

IT infrastructure is a core part of the business of healthcare, says Dee Emon, vice president and CIO, and formerly chief clinical information officer, at Wake Forest Baptist Medical Center, and these improvements have been highly beneficial to clinicians and physicians. “It’s very important that our physicians and other care providers have information at their fingertips at all points of care—whether that’s at the patient’s bedside or in the operating room,” Emon says, adding that clinicians and staff now have faster, more secure access to medical records, diagnostic information and medical imaging.

With a modernized network infrastructure, the health IT teams are able to create more innovative solutions on top of that, Eckes adds. “For example, we have next-generation RFID solutions, and we’re literally badging patients and providers and we’re able to badge equipment, and by doing all of that, you can create auto log-in scenarios and create more personalized scenarios with the patient using data where it resides,” he says.

As an academic medical center, Wake Forest Baptist Medical Center executive leaders also wanted to better utilize the large pools of data it captured to support data analytics work. To this end, the organization also worked with its vendor partners to launch Wake Lake, a data lake platform to integrate with Wake Cloud to enable the health system to begin aggregating both structured and unstructured data in a centralized repository. According to Eckes, this will allow users, from clinicians to researchers, to perform powerful analytics projects.

Martin Sizemore, Wake Forest Baptist Medical Center’s associate vice president and chief data officer, says the IT infrastructure improvements solve many of the most common data center challenges—flexibility and speed. “Our goal was to have the same experience as if you wanted to stand up hardware on Amazon; we wanted that flexibility, we wanted that nimbleness—to be able to say, I need four processors and I need as much storage, and be able to spin that out very quickly to get something configured and ready to go for a researcher in the medical school or a clinician doing informatics, or just a business user who is trying to analyze their budget,” he says, adding, “So what used to take days, now takes minutes. We can also recover those virtual machines and that storage and use it for someone else, so it’s much more economical because we can redeploy resources quickly for bigger projects, for temporary development or for testing.”

One of the biggest lessons learned from this initiative, Eckes says, was devoting a significant amount of time on organizational change management with the infrastructure team. “This is a radically new way of thinking and there’s folks that have been making a career out of racking and stacking and implementing operating systems, and doing the normal care and feeding of servers. The new jobs that you have after going to converged infrastructure are much more interesting. The need for people doesn’t go away, but the roles change,” he says.

Eckes, who has worn both CIO and CFO hats, asserts as healthcare executive leaders move to cloud and converged infrastructure technologies, they should be prepared that these technologies essentially change the financials of IT.

“The way we used to do IT, especially in healthcare, is more project-based. You would decide to be put in a new system and that piece of software required X number of servers and X number of storage, and you would fund it off a CapEx (capital expenditure) project, and then you would worry about replacing the hardware down the road on another CapEx project. And you were always chasing the tail of capital dollars being available, and then you’d find that the replacements would be pushed out, because CapEx was squeezed,” he says. Deploying a converged infrastructure environment changes the discussion, he asserts, as “now it’s all about actually putting in capacity and planning for that capacity upfront so that it’s ready and waiting and you would call it more of a service-based approach to IT versus a project-based approach.”

Further he adds, “Our vision of the future is that software stays the same for our infrastructure and our internal consumers might say, ‘I want to spin up a new environment for this research study,’ and instead of using internal cloud computed storage, we can use a less expensive Amazon Web Services-based infrastructure. They still go through and utilize the same procurement process internally that manages that spin-off. Now all the sudden, from a finance perspective, you’re paying for the compute and storage, versus physical equipment.”

The Critical Role of Data Governance, as Healthcare Complexity Grows

Beyond issues related to modernizing aging infrastructure, healthcare provider organizations are grappling with changing market dynamics and trends, such as increasing digitalization, consumerism, regulatory impacts and healthcare delivery transformation. These market dynamics are creating demand for health IT and for more effective management of all the healthcare data.

Daniel Herman, informatics and technology practice area senior advisor at the Chicago-based The Chartis Group, a healthcare consulting firm, says as healthcare organizations continue to form different kinds of affiliations, whether through mergers and acquisitions or forming clinically integrated networks (CIN), this increases the need to focus on moving information from one place to another to access value and cost, and also provide patients access to their data as they go across these virtual networks. “We are seeing consistently this issue of governance and decision-making on how to balance supply and demand related to technology requests and capital investments. It’s an insatiable demand going on right now and there’s just limited amount of funds to go around, so looking at how we work with operational leaders to own those decisions just like they would own decisions related to investments, expansion or building programs or building new facilities and things like that,” Herman says.

Harold (Hal) Wolf, director with The Chartis Group and national leader for its information and digital health strategy practice, agrees, adding that this demand for technology “is such a critical and fundamental part of the building blocks that are happening inside the industry. There is this other significant demand going on in conjunction with personalized care in the digital space, so what’s beginning to happen, you’re seeing a tremendous amount of attention to governance inside organizations that are more complex that they even were just two years ago.”

Wolf continues, “The necessity to match IT investment and integrate it into the enterprise strategy is at an all-time high, because to gain the capabilities that are necessary for mobility, for population care management, for investment and analytics, you really have critical IT dependencies that have to be funded and they have to support the enterprise strategy, so the integration between the IT strategy and the enterprise strategy never before has been greater and it’s sitting inside that governance sphere.”

He also notes that healthcare leaders should approach technology projects as not strictly IT projects, but business projects supported by IT and critical to the success of the enterprise.

As an example, Herman points out that the consulting firm works with multi-entity, multi-region healthcare provider organizations. “With one organization, the first project was, ‘why are we spending so much on IT?’ And this is from the CFO and management team. After education was provided, the organization saw they were getting a lot of value from their spending.”

He continues, “And the next question was really the IT governance piece. The CEO of that health system really took ownership of that because he saw that the decisions related to it were very similar to the other decisions related to the prioritization of capital operating across the health system. As an example, for building programs that were already approved, the technology capital associated with that needed to be incorporated into the overall budget, and that wasn’t up for question, that was already approved.”

Ultimately, developing strategies for managing data, and addressing the technical as well as the cultural challenges, will be imperative as the transformation of healthcare continues and complexity only grows.

 

 


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Have CIOs’ Top Priorities for 2018 Become a Reality?

December 12, 2018
by Rajiv Leventhal, Managing Editor
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In comparing healthcare CIOs’ priorities at the end of 2017 to this current moment, new analysis has found that core clinical IT goals have shifted from focusing on EHR (electronic health record) integration to data analytics.

In December 2017, hospitals CIOs said they planned to mostly focus on EHR integration and mobile adoption and physician buy-in, according to a survey then-conducted by Springfield, Va.-based Spok, a clinical communications solutions company, of College of Healthcare Information Management Executives (CHIME) member CIOs.

The survey from one year ago found that across hospitals, 40 percent of CIO respondents said deploying an enterprise analytics platform is a top priority in 2018. Seventy-one percent of respondents cited integrating with the EHR is a top priority, and 62 percent said physician adoption and buy-in for securing messaging was a top priority in the next 18 months. What’s more, 38 percent said optimizing EHR integration with other hospital systems with a key focus for 2018.

Spok researchers were curious whether their predictions became reality, so they analyzed several industry reports and asked a handful of CIOs to recap their experiences from 2018. The most up-to-date responses revealed that compared to last year when just 40 percent of CIOs said they were deploying an enterprise analytics platform in 2018, harnessing data analytics looks to be a huge priority in 2019: 100 percent of the CIOs reported this as top of mind.

Further comparisons on 2018 predictions to realities included:

  • 62 percent of CIOs predicted 2018 as the year of EHR integration; 75 percent reported they are now integrating patient monitoring data
  • 79 percent said they were selecting and deploying technology primarily for secure messaging; now, 90 percent of hospitals have adopted mobile technology and report that it’s helping improve patient safety and outcomes
  • 54 percent said the top secure messaging challenge was adoption/buy in; now, 51 percent said they now involve clinicians in mobile policy and adoption

What’s more, regarding future predictions, 87 percent of CIOs said they expect to increase spending on cybersecurity in 2019, and in three years from now, 60 percent of respondents expect data to be stored in a hybrid/private cloud.

CIOs also expressed concern regarding big tech companies such as Apple, Amazon and Google disrupting the healthcare market; 70 percent said they were somewhat concerned.

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How One Community Hospital is Leveraging AI to Bolster Its Care Pathways Process

December 6, 2018
by Heather Landi, Associate Editor
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Managing clinical variation continues to be a significant challenge facing most hospitals and health systems today as unwarranted clinical variation often results in higher costs without improvements to patient experience or outcomes.

Like many other hospitals and health systems, Flagler Hospital, a 335-bed community hospital in St. Augustine, Florida, had a board-level mandate to address its unwarranted clinical variation with the goal of improving outcomes and lowering costs, says Michael Sanders, M.D., Flagler Hospital’s chief medical information officer (CMIO).

“Every hospital has been struggling with this for decades, managing clinical variation,” he says, noting that traditional methods of addressing clinical variation management have been inefficient, as developing care pathways, which involves identifying best practices for high-cost procedures, often takes up to six months or even years to develop and implement. “By the time you finish, it’s out of date,” Sanders says. “There wasn’t a good way of doing this, other than picking your spots periodically, doing analysis and trying to make sense of the data.”

What’s more, available analytics software is incapable of correlating all the variables within the clinical, billing, analytics and electronic health record (EHR) databases, he notes.

Another limitation is that care pathways are vulnerable to the biases of the clinicians involved, Sanders says. “In medicine, what we typically do is we’ll have an idea of what we want to study, design a protocol, and then run the trial and collect the data that we think is important and then we try to disprove or prove our hypothesis,” he says.

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Sanders says he was intrigued by advances in machine learning tools and artificial intelligence (AI) platforms capable of applying advanced analytics to identify hidden patterns in data.

Working with Palo Alto, Calif.-based machine intelligence software company Ayasdi, Flagler Hospital initiated a pilot project to use Ayasdi’s clinical variation management application to develop care pathways for both acute and non-acute conditions and then measure adherence to those pathways.

Michael Sanders, M.D.

Flagler targeted their treatment protocols for pneumonia as an initial care process model. “We kicked around the idea of doing sepsis first, because it’s a huge problem throughout the country. We decided to use pneumonia first to get our feet wet and figure out how to use the tool correctly,” he says.

The AI tools from Ayasdi revealed new, improved care pathways for pneumonia after analyzing thousands of patient records from the hospital and identifying the commonalities between those with the best outcomes. The application uses unsupervised machine learning and supervised prediction to optimally align the sequence and timing of care with the goal of optimizing for patient outcomes, cost, readmissions, mortality rate, provider adherence, and other variables.

The hospital quickly implemented the new pneumonia pathway by changing the order set in its Allscripts EHR system. As a result, for the pneumonia care path, Flagler Hospital saved $1,350 per patient and reduced the length of stay (LOS) for these patients by two days, on average. What’s more, the hospital reduced readmission by 7 times—the readmission rate dropped from 2.9 percent to 0.4 percent, hospital officials report. The initial work saved nearly $850,000 in unnecessary costs—the costs were trimmed by eliminating labs, X-rays and other processes that did not add value or resulted in a reduction in the lengths of stay or readmissions.

“Those results are pretty amazing,” Sanders says. “It’s taking our data and showing us what we need to pursue. That’s powerful.”

With the success of the pneumonia care pathway, Flagler Hospital leaders also deployed a new sepsis pathway. The hospital has expanded its plans for using Ayasdi to develop new care pathways, from the original plan of tackling 12 conditions over three years, to now tackling one condition per month. Future plans are to tackle heart failure, total hip replacement, chronic obstructive pulmonary disease (COPD), coronary artery bypass grafting (CABG), hysterectomy and diabetes, among other conditions. Flagler Hospital expects to save at least $20 million from this program in the next three years, according to officials.

Finding the “Goldilocks” group

Strong collaboration between IT and physician teams has been a critical factor in deploying the AI tool and to continue to successfully implement new care pathways, Sanders notes.

The effort to create the first pathway began with the IT staff writing structured query language (SQL) code to extract the necessary data from the hospital’s Allscripts EHR, enterprise data warehouse, surgical, financial and corporate performance systems. This data was brought into the clinical variation management application using the FHIR (Fast Healthcare Interoperability Resources) standard.

“That was a major effort, but some of us had been data scientists before we were physicians, and so we parameterized all these calls. The first pneumonia care path was completed in about nine weeks. We’ve turned around and did a second care path, for sepsis, which is much harder, and we’ve done that in two weeks. We’ve finished sepsis and have moved on to total hip and total knee replacements. We have about 18 or 19 care paths that we’re going to be doing over the next 18 months,” he says.

After being fed data of past pneumonia treatments, the software automatically created cohorts of patients who had similar outcomes accompanied by the treatments they received at particular times and in what sequence. The program also calculated the direct variable costs, average lengths of stay, readmission and mortality rates for each of those cohorts, along with the statistical significance of its conclusions. Each group had different comorbidities, such as diabetes, COPD and heart failure, which was factored into the application's calculations. At the push of a button, the application created a care path based on the treatment given to the patients in each cohort.

The findings were then reviewed with the physician IT group, or what Sanders calls the PIT crew, to select what they refer to as the “Goldilocks” cohort. “This is a group of patients that had the combination of low cost, short length of stay, low readmissions and almost zero mortality rate. We then can publish the care path and then monitor adherence to that care path across our physicians,” Sanders says.

The AI application uncovered relationships and patterns that physicians either would not have identified or would have taken much longer to identify, Sanders says. For instance, the analysis revealed that for patients with pneumonia and COPD, beginning nebulizer treatments early in their hospital stays improved outcomes tremendously, hospital leaders report.

The optimal events, sequence, and timing of care were presented to the physician team using an intuitive interface that allowed them to understand exactly why each step, and the timing of the action, was recommended. Upon approval, the team operationalized the new care path by revising the emergency-department and inpatient order sets in the hospital EHR.

Sanders says having the data generated by the AI software is critical to getting physicians on board with the project. “When we deployed the tool for the pneumonia care pathway, our physicians were saying, ‘Oh no, not another tool’,” Sanders says. “I brought in a PIT Crew (physician IT crew) and we went through our data with them. I had physicians in the group going through the analysis and they saw that the data was real. We went into the EMR to make sure the data was in fact valid, and after they realized that, then they began to look at the outcomes, the length of stay, the drop in readmissions and how the costs dropped, and they were on board right away.”

The majority of Flagler physicians are adhering to the new care path, according to reports generated by the AI software's adherence application. The care paths effectively sourced the best practices from the hospital’s best doctors using the hospital’s own patient groups, and that is key, Sanders notes.

“When we had conversations with physicians about the data, some would say, ‘My patient is sicker than yours,’ or ‘I have a different patient population.’ However, we can drill down to the physician’s patients and show the physician where things are. It’s not based on an ivory tower analysis, it’s based on our own data. And, yes, our patients, and our community, are unique—a little older than most, and we have a lot of Europeans here visiting. We have some challenges, but this tool is taking our data and showing us what we need to pursue. That’s pretty powerful.”

He adds, “It’s been amazing to see physicians rally around this. We just never had the tool before that could do this.”

While Flagler Hospital is a small community hospital with fewer resources than academic medical centers or larger health systems—for example, the hospital doesn’t have a dedicated data scientist but rather uses its in-house informatics staff for this project—the hospital is progressive in its use of advanced analytics, according to Sanders.

“We’ve been able to do a lot of querying ourselves, and we have some sepsis predictive models that we’ve created and put into place. We do a lot of real-time monitoring for sepsis and central line-associated bloodstream infections,” he says. “Central line-associated bloodstream infections are a bane for all hospitals. In the past year and a half, since we’ve put in our predictive model, we’ve had zero bloodstream infections, and that’s just unheard of.”

Sanders and his team plan to continue to use the AI tool to analyze new data and adjust the care paths according to new discoveries. As the algorithms find more effective and efficient ways to deliver care that result in better outcomes, Flagler will continue to improve its care paths and measure the adherence of its providers.

There continues to be growing interest, and also some hype, around AI tools, but Sanders notes that AI and machine learning are simply another tool. “Historically, what we’ve done is that we had an idea of what we wanted to do, conducted a clinical trial and then proved or disproved the hypothesis, based on the data that we collected. We have a tool with AI which can basically show us relationships that we didn’t know even existed and answer questions that we didn’t know to ask. I think it’s going to open up a tremendous pathway in medicine for us to both reduce cost, improve care and really take better care of our patients,” he says, adding, “When you can say that to physicians, they are on board. They respond to the data.”

 


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At RSNA 2018, An Intense Focus on Artificial Intelligence

November 29, 2018
by Mark Hagland, Editor-in-Chief
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Artificial intelligence solutions—and discussions—were everywhere at RSNA 2018 this week

Artificial intelligence solutions—and certainly, the promotion of such solutions—were everywhere this year at the RSNA Conference, held this week at Chicago’s vast McCormick Place, where nearly 49,000 attendees attended clinical education sessions, viewed nearly 700 vendor exhibits. And AI and machine learning promotions, and discussions were everywhere.

Scanning the exhibit floor on Monday, Glenn Galloway, CIO of the Center for Diagnostic Imaging, an ambulatory imaging center in the Minneapolis suburb of St. Louis Park, Minn., noted that “There’s a lot of focus on AI this year. We’re still trying to figure out exactly what it is; I think a lot of people are doing the same, with AI.” In terms of whether what’s being pitched is authentic solutions, vaporware, or something in between, Galloway said, “I think it’s all that. I think there will be some solutions that live and survive. There are some interesting concepts of how to deliver it. We’ve been talking to a few folks. But the successful solutions are going to be very focused; not just AI for a lung, but for a lung and some very specific diagnoses, for example.” And what will be most useful? According to Galloway, “Two things: AI for the workflow and the quality. And there’ll be some interesting things for what it will do for the quality and the workflow.”

“Certainly, this is another year where machine learning is absolutely dominating the conversation,” said James Whitfill, M.D., CMO at Innovation Care Partners in Scottsdale, Ariz., on Monday. “In radiology, we continue to be aware of how the hype of machine learning is giving way to the reality; that it’s not a wholesale replacement of physicians. There have already been tremendous advances in, for example, interpreting chest x-rays; some of the work that Stanford’s done. They’ve got algorithms that can diagnose 15 different pathological findings. So there is true material advancement taking place.”

Meanwhile, Dr. Whitfill said, “At the same time, people are realizing that coming up with the algorithm is one piece, but that there are surprising complications. So you develop an algorithm on Siemens equipment, but when you to Fuji, the algorithm fails—it no longer reliably identifies pathology, because it turns out you have to train the algorithm not just on examples form just one manufacturer, but form lots of manufacturers. We continue to find that these algorithms are not as consistent as identifying yourself on Facebook, for example. It’s turning out that radiology is way more complex. We take images on lots of different machines. So huge strides are being made,” he said. “But it’s very clear that human and machine learning together will create the breakthroughs. We talk about physician burnout, and even physicians leaving. I think that machine learning offers a good chance of removing a lot of the drudgery in healthcare. If we can automate some processes, then it will free up our time for quality judgment, and also to spend time talking to patients, not just staring at the screen.”

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Looking at the hype cycle around AI

Of course, inevitably, there was talk around the talk of the hype cycle involving artificial intelligence. One of those engaging in that discussion was Paul Chang, M.D.., a practicing radiologist and medical director of enterprise imaging at the University of Chicago. Dr. Chang gave a presentation on Tuesday about AI. According a report by Michael Walter in Radiology Business, Dr. Chang said, “AI is not new or spooky. It’s been around for decades. So why the hype?” He described computer-aided detection (CAD) as a form of artificial intelligence, one that radiologists have been making use of for years.

Meanwhile, with regard to the new form of AI, and the inevitable hype cycle around emerging technologies, Dr. Chang said during his presentation that “When you’re going up the ride, you get excited. But then right at the top, before you are about to go down, you have that moment of clarity—‘What am I getting myself into?’—and that’s where we are now. We are upon that crest of magical hype and we are about to get the trench of disillusionment.” Still, he told his audience, “It is worth the rollercoaster of hype. But I’m here to tell you that it’s going to take longer than you think.”

So, which artificial intelligence-based solutions will end up going the distance? On a certain level, the answer to that question is simple, said Joe Marion, a principal in the Waukesha, Wis.-based Healthcare Integration Strategies LLC, and one of the imaging informatics industry’s most respected observers. “I think it’s going to be the value of the product,” said Marion, who has participated in 42 RSNA conferences; “and also the extent to which the vendors will make their products flexible in terms of being interfaced with others, so there’s this integration aspect, folding into vendor A, vendor B, vendor C, etc. So for a third party, the more they reach out and create relationships, the more successful they’ll be. A lot of it will come down to clinical value, though. Watson has had problems in that people have said, it’s great, but where’s the clinical value? So the ones that succeed will be the ones that find the most clinical value.”

Still, Marion noted, even the concept of AI, as applied to imaging informatics, remains an area with some areas lacking in clarity. “The reality, he said, “is that I think it means different things to different people. The difference between last year and this year is that some things are coming to fruition; it’s more real. And so some vendors are offering viable solutions. The message I’m hearing from vendors this year is, I have this platform, and if a third party wants to develop an application or I develop an application, or even an academic institution develops a solution, I can run it on my platform. They’re trying to become as vendor-agnostic as possible.”

Marion expressed surprise at the seemingly all-encompassing focus on artificial intelligence this year, given the steady march towards value-based healthcare-driven mandates. “Outside of one vendor, I’m not really seeing a whole lot of emphasis this year on value-based care; that’s disappointing,” Marion said. “I don’t know whether people don’t get it or not about value-based care, but the vendors are clearly more focused on AI right now.”

Might next year prove to be different? Yes, absolutely, especially given the coming mandates coming out of the Protecting Access to Medicare Act (PAMA), which will require referring providers to consult appropriate use criteria (AUC) prior to ordering advanced diagnostic imaging services—CT, MR, nuclear medicine and PET—for Medicare patients. The federal Centers for Medicare and Medicaid Services (CMS) will progress with a phased rollout of the CDS mandate, as the American College of Radiology (ACR) explains on its website, with voluntary reporting of the use of AUC taking place until December 2019, and mandatory reporting beginning in January 2020.

But for now, this certainly was the year of the artificial intelligence focus at the RSNA Conference. Only time will tell how that focus plays out in the imaging and imaging informatics vendor space within the coming 12 months, before RSNA 2019 kicks off one year from now, at the conference’s perennial location, McCormick Place.

 

 


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