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Employer-Purchasers Get In on the Analytics Act

October 22, 2016
by Mark Hagland
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A new survey looks at employer-purchasers’ interest in leveraging analytics to judge value in healthcare

With so many things changing all at once in healthcare, it’s no surprise that the corporations that are the private employer-purchasers of U.S. healthcare want to keep their collective finger on the pulse of what’s been going on with health insurers and healthcare providers. Indeed, as much as hospital, medical group, and health plan leaders are plunging ahead to leverage data analytics to understand health system clinical and resource utilization performance, so, too, the corporate purchasers of healthcare are intent on figuring out just what is going on these days with healthcare delivery and payment.

It is in that context that the Washington, D.C.-based non-profit National Alliance of Healthcare Purchaser Coalitions (the National Alliance) recently conducted a survey—commissioned by Geneia LLC, the for-profit subsidiary of the Harrisburg, Pa.-based Capital Blue Cross and Blue Shield—to find out what healthcare purchasers are doing in that area. That poll found that 97 percent of human resources executives at corporations agree that “now more than ever, it’s essential to have tools to effectively evaluate data and make informed decisions.” Most respondents (87 percent) say they are familiar with advanced analytics, but current users have a stronger understanding of how this kind of tool helps aggregate data, control spending, and manage health and wellness programs.

In releasing the results of that survey on Oct. 12, Michael Thompson, president and CEO of the National Alliance, said in a statement that “Many employers struggle with massive amounts of data and lack the ability to quickly and easily make informed decisions that shape their benefits programs. And it’s only getting worse,” Thompson said in the statement, “as it’s estimated by 2020 we will have 50 times the amount of data that was available in 2011. Gauging the knowledge and interest level of employers enables the National Alliance and its members to make available programs and tools to help purchasers overcome this challenge.”

Among other key findings in the survey:

>  Among survey respondents, 95 percent indicated that they’re interested in having access to the information that advanced analytics can provide.


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>  90 percent of respondents said that near-real-time data is imperative to realizing costs savings

>  94 percent agree that “healthcare analytics can help me evaluate which wellness programs would be most effective to offer to my employees.”

>  83 percent agree that using advanced analytics to understand how your employees use healthcare services, who your high-risk employees are and how to intervene effectively is the only way to lower costs and improve financial results.

>  When asked about what data and reports would be helpful, the top three responses were data on the number of employees regularly visiting the emergency department but who have not seen their primary care doctor in the last year; timely data on percentage of pre-diabetic employees who have not seen their primary care doctor in the last year; and an evaluation of their company’s healthcare spend against similarly sized companies in their industry or region

>  Of respondents who were not currently using advanced analytics tools, the perceived barriers to use were cost (38 percent), insufficient internal resources (31 percent) and needs already supported by health plan or broker (54 percent).

The release of the survey’s results also included a statement by Heather Lavoie, Geneia’s chief strategy officer. “Healthcare costs are still growing faster than inflation and are expected to increase 6.5 percent through next year, leaving employers, health plans and consumers struggling to find ways to contain costs without sacrificing quality and benefit design,” Lavoie said. “At Geneia, we know that the insight gained through advanced analytic tools offers employers the very real possibility of lowering costs while retaining competitive employee benefit programs.”

The online survey of human resource and benefits administrators was conducted in August and September 2016. Of the responses received, 89 percent of employers said they were self-funded, 69 percent work for companies that employ more than 1,000 and 60 percent said they are not current users of advanced analytic tools. Regionally, 50 percent of respondents were from the South, 26 percent were from the Northeast, 15 percent were from the West and 9 percent were from the Midwest.

Following the release of the survey’s results, Michael Thompson and Heather Lavoie spoke with Healthcare Informatics Editor-in-Chief Mark Hagland. Below are, first, excerpts from the interview with Thompson, and second, excerpts from the interview with Lavoie.


Tell me about the National Alliance of Healthcare Purchaser Coalitions.

Michael Thompson: The National Alliance is a group of 50 business coalitions across the country, representing 41 million people, and about 12,000 employers; and about 450 of them are over 5,000 employees. It’s public and private employers, as well as Taft-Hartley organizations—when there’s a union plan managed by a trust of half-management and half-union.

Where are your members right now?

As much as the discussion is all about cost, I think that purchasers’ mindset really is around value. There’s been a lot of terrific innovation in the industry that actually has value, health, and outcomes, and they recognize that. I think where they have a lot less tolerance is when things cost more but don’t add any value or add little value relative to the cost. That’s where purchasers are looking to change the system, and in how they guide their employees.

What were the biggest takeaways for you from the survey results?

We always recognize that employers value data, to be fact-based in their decision-making, but what was particularly interesting from this survey was the universality of the importance in terms of making data actionable--in other words, its value in informing them on how they should modify their benefits, modify their plan designs, modify their benefits.

Purchasers want to get more active in pushing the levers of control around healthcare delivery and costs, correct?

I think that’s a fair point, yes. Historically, employers have been focused on which health plan performs better compared to the next; but of course, the variations don’t really occur with health plans, but rather with providers themselves. So increasingly, employers are pushing health plans to create greater transparency around provider outcomes, so that employers can direct their employees to higher-performing systems. That’s frankly still evolving. Some employers are doing that on a direct basis; others are finding intermediaries to steer things towards bora-based solutions or towards more specialized solutions, like centers of excellence.

What are your and your members’ perceptions of the accountable care organization phenomenon?

In general, we applaud any movement to shift the mindset of providers to align their systems and delivery of care with value. Frankly, the fact that they call themselves an accountable care organization may not mean that they’re high-performing at this point in time; and what we see is very much a maturity model as it relates to organizations and how they perform. Different employers will have different appetites to get involved with less mature entities. But if it’s a long journey, it’s good that providers have started down that path. And while Medicare has started to move in the direction of accountable care, it’s still early in the game, but as Medicare brings accountable care into the broader Medicare program, that’s going to be a major influence. So, the writing’s on the wall that this ship is turning, and employers are going to push as hard as possible to compel value in healthcare.

When you look at the new MACRA (Medicare Access and CHIP Reauthorization Act) law and the new Quality Payment system, do you see opportunity there for employer-purchasers?

Yes. My own view is that providers continue to struggle—the old model is fee-for-service, and it’s hard to transform towards being rewarded for value rather than volume. As the mainstream part of the market moves towards more value-driven programs, it will be incumbent on providers to change the way they practice medicine, to align. And it’s this transition that’s messy. I think organizations can succeed in either FFS or value-based, but it’s hard to succeed in both at once, still.

And the MIPS (Merit-based Incentive Payment System) program will require all physicians except pediatricians to do outcomes reporting. That will be an opportunity for purchasers, yes?

Yes, and it’s going to be incumbent to move towards more universal systems of outcomes reporting. And there are some differences among populations—Medicare, Medicaid, and commercial—but honestly, the more alignment we can achieve, the more likely we can make changes in the HC system.

What do you think will happen in the next few years?

The past decade has been the decade of the consumer, really, trying to get more information into the hands of consumers. I think the next decade will be more focused on the supply side—on how we get health plans, providers, and pharmaceutical companies to deliver more value. And data will be central to that discussion, and frankly, there will be much more focus on collectivism, rather than on everybody do their own thing. That’s why collaboratives are so helpful—they help purchasers to collectively support changes.

On a scale of 1 to 10, how optimistic are you about the transformation of the U.S. healthcare system?

Oh, I think I’m a 7. There are a lot of good things happening now; still, we can’t release our foot on pedal.


Is it your sense that employers are still early in their journey around advanced health plan design?

Heather Lavoie: I think that they have an understanding of health plan design—but as it gets more granular than that—the extent to which wellness programs are demonstrating a return on investment, for example, or elements like site of service or centers of excellence—what elements they can move to improve quality and cost—their HR departments have bene very small traditionally, and they’ve heavily relied on the brokers per the plans. They’ve had reports, but usually they’re retrospective, and they’ve felt powerless to have an impact. And we’ve been seeing some latency in the adoption of tools, so some have certainly gone out and used tools, but the uptake has been rather slow, because they don’t have the internal manpower to handle the administration of this. There’s been some concern about the numbers being small, and about access. But we’ve seen overwhelming interest in having access, but wanting to do this on an aggregated basis—employers see the benefit of pooling resources to have access to tools, and to inform strong practic3 in implementation—what programs will be most effective, and looking at benchmarks—on their own, they just don’t have the access to get the results.

Where are purchasers on population health right now, per plans and providers?

We asked them to rate how useful different types of access would help, on a scale of 1-7. Some of the most useful were data on the number of employees regularly using EDs but hadn’t seen their physicians in 12 months; timely data on employees who are pre-diabetic, but haven’t seen their PCP in 12 months; and the percentage of employees engaged in population health programs. And 5.5 was the rating for the same population health data, for seeing the same data that physicians and health plans are seeing on patients, that they see that that data is important for them to see as well. So they feel they need to see that data, too, to help effect change on our end.

Where will the emerging policy, payment, and demographic trends take us in terms of population health and analytics?

There’s going to be a demand for the sharing of data across all entities, so everyone’s aligned in their goals. Employers are seeing that they’re going to have to take a very firm position on costs and quality; the most aggressive are doing direct contracting with providers; others are pushing very hard on the plans for quality and cost results. They were pushing on the benefit design string for so long, and now employees can’t afford any more cost-sharing, and so the only place to go is the engagement of patients in care management and in the delivery of services, changing the site of care, such as urgent care versus ER, and so on. Every year, Willis Towers Watson (which brought together the firms of Willis Carroon and Towers Watson, into one firm), takes a look at the best-performing companies in terms of health care costs, and at the drivers of those kinds of performance. Last year, they were able to take claims data and quantify the net impact of the different best practices. And the best performers used clinical-level medical claims data to inform their program design; they had a 60-percent lead over the national average. And the best performers in 2015 paid $2,000 less per employee than other companies and were able to maintain a cost trend that was 2.6 percent lower across a two-year cost trend.

How do you see employers looking at the ACO phenomenon in this context?

It depends on the sophistication of the particular employer. But the most pioneering employers are a very educated group, and are advocating more for risk-based contracting and for the shift from volume to value. Being on the receiving end, they’re baking it into their requests for proposal, asking for documentation of effectiveness, and looking at a range of possibilities, from shared savings to full risk. So they’re very aware, and are certainly advocating it.

What should the CIOs and CMIOs of provider organizations take from this discussion?

I think they need to recognize employers as a critical, direct constituency now, and that employers really want transparency for the cost and quality of healthcare, and they really have a strong in understanding how healthcare is delivered. And that dialogue hadn’t traditionally occurred; they mostly worked through the plans, but employers are really wanting to get much more involved, not just through direct contracting, but through solutioning. They have day-to-day contact with the employees who are the patients. And that alignment can provide a lot of potential, if leveraged properly. 

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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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