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Healthcare Execs Accelerating Investment in AI, Citing Fear of Disruption

January 7, 2019
by Heather Landi, Associate Editor
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Three out of four healthcare executive leaders (77 percent) report that the pace of investment in big data and artificial intelligence (AI) is accelerating at their organizations, in large part due to concerns about disruptive forces and competitors.

A cross-industry survey conducted by NewVantage Partners, a strategic advisory firm, found that, across all enterprises, 92 percent of senior corporate executives report their organizations are increasing their pace of investment in big data and AI, and 62 percent have seen measurable results from their investments.

The aim of the survey is to gauge how big data and AI are accelerating business transformation and the 2019 version of the survey represented executives from nearly 65 companies, with financial services firms making up the majority of respondents. Healthcare respondents include United Health, Aetna, Cigna, CVS Health and Partners Healthcare. The majority of respondents identified as chief data officers, chief analytics officers or chief information officers.

While 92 percent of respondents across all industries confirm that the pace of investment in AI and big data is accelerating, 76 percent of healthcare executive leaders reported an acceleration investment. About the same percentage (78 percent) of healthcare senior C-suite executives reported greater urgency to invest in AI and data analytics, although this indicates a less urgent pace than their financial services counterparts (92 percent report processing at a more urgent pace).

Among respondents across all industries, when asked as to the motivation behind ramping up AI and big data investments, 75 percent cited fear disruption from new entrants, and 88 percent said they feel greater urgency to invest in big data and AI.

The fear of disruption was higher among healthcare executives—79 percent—relative to their financial services colleagues (72 percent cited concern about data-driven disruptors).

When asked to identify the principal driver of big data and AI investment, there was uniform consensus, across all industries. Companies are united in their view that business transformation and greater agility will enable them to operate more competitively–92 percent acknowledged these as the driving factors. Only 5 percent are driven by cost reduction.

In the survey report, NewVantage Partners CEO and founder Randy Bean and NewVantage Partners fellow Thomas H. Davenport, wrote, “Is the glass for data, analytics, and AI in large organizations half empty or half full? While there are still signs of emptiness, over all we see a glass that is half full and filling up slowly. Compared to, say, a decade ago, an impressive number of enterprises are data-driven today.”

However, Bean and Davenport also warn, “We should not fail to recognize that we live in a highly dynamic time when digital companies have with speed and force disrupted longstanding business models and traditional competitors. For this reason, these survey findings may be considered a call to action. In critical respects, one could argue that the glass remains half full—that progress has been slow, and that many companies still lack commitment to data-driven organizational processes and cultures.”

Across all industries, the number of firms investing greater than $500 million in AI and data analytics initiatives has increased significantly—from 12.7 percent in 2018 to 21 percent of firms in 2019. Likewise, the number of firms investing greater than $50 million has increased from 39 percent in 2018 to 55 percent in 2019.

Overall, 96 percent of executives report investing in AI/machine learning, reinforcing the view that investment in AI has become nearly universal. What’s more, 90 percent of executives report investing in cloud computing and 77 percent citing investment in digital technologies. Investment in blockchain technologies has yet to demonstrate momentum, with only 42 percent of executives reporting investing in that technology area.

Though there has been considerable discussion regarding the applicability of Blockchain with healthcare, the number of firms reporting investment in Blockchain was sharply lower among healthcare firms (29 percent) in comparison to financial services firms (45 percent).

Across all industries, executives were asked to identify their 2019 data priorities. With rising attention being paid to issues regarding data protection in the wake of GDPR legislation and well publicized data breeches, it should not come as a surprise that privacy and security were named as universal priorities.

Looking at the results of these investments, 62 percent of respondents across all industries report measurable results from their big data and AI investments, but less than half say they are competing on data and analytics (47 percent), have created a data-driven organization (31 percent), or have forged a data culture (28 percent).

Notably, healthcare firms reported greater success in competing on analytics than their financial services counterparts—57 percent of healthcare firms indicated that they were successful at competing on data and analytics, while only 45 percent of financial services firms reported success.

Cultural challenges remain the biggest obstacle to business adoption, according to the survey. Companies report (77 percent) that business adoption of big data and AI initiatives remains a major challenge. Executives cite multiple factors (organizational alignment, agility, resistance), with 95 percent stemming from cultural challenges (people and process), and only 5 percent relating to technology.

What’s more, the chief data officer role is evolving but ill-defined—48 percent of respondents see the CDO as having primary responsibility for data while 28 percent see no single point of accountability. Among healthcare executives, 43 percent reported there was no single point of accountability for data within their organization.

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AI in Imaging: Where’s the Bang for the Buck?

January 23, 2019
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Over the past year much has been written about the capability of Artificial Intelligence (AI), and what it will mean for imaging services.  At last year’s RSNA, AI was the featured topic and received the lion’s share of publicity. 

The glamorous aspect of AI and Machine Learning has been how AI can assist the radiologist with diagnosis of imaging studies.  A key area of focus has been in chest imaging ( where there has been some success in triaging abnormal chest images.  The upside of such applications is improved diagnostic efficiency, particularly as healthcare moves toward value-based care.  The downside is that such algorithms require substantial amounts of data to validate, and they will need to go through the FDA approval process, which will take time before they can be fully implemented.

Ultimately, AI imaging applications will pay off.  But, what about the other potentially less-glamorous aspect of applying AI/Machine Learning to the diagnostic process?  By that, I am referring to its use in terms of workflow orchestration.  Aside from interpreting imaging content, AI/Machine Learning applied to workflow orchestration can provide valuable information and assistance in preparing a case for interpretation. 

Take for example Siemens Healthineer’s AI-Rad Companion application (  The application provides automated identification, localization, labeling and measurements for anatomies and abnormalities.  Such a capability can improve the radiologist’s efficiency without necessarily employing an algorithm to assess the image.

Other workflow applications can assess the study and mine relevant information from the EHR to present to the radiologist, again with the goal of improving their efficiency and efficacy.  Still other applications match radiologist reading assignments with available studies to improve reading efficiency.  In another twist, one company has demonstrated a capability to further analyze cases, using AI to assign the next appropriate case to a radiologist without the need for a worklist. 

As healthcare providers consolidate, there is a growing need for improvement in resource utilization across facilities.  Smart worklists that can present cases to individual radiologists across facilities can improve the overall efficiency and efficacy of interpretation.  Rule sets that address radiologist availability, reading sub-specialties, location, etc. can help “level-load” reading resources. 

My point is that while AI applications that manipulate images may hold great promise for the future of diagnosis, areas such as workflow orchestration might offer more immediate results in an environment of changing healthcare.  Providers should take a close look at these applications to assess whether they can achieve a more immediate impact on imaging operations.

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National Library of Medicine Creating Scientific Director Position

January 23, 2019
by David Raths, Contributing Editor
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New position will oversee Lister Hill National Center for Biomedical Communications and National Center for Biotechnology Information

As part of a reorganization of its intramural research activities, the U.S. National Library of Medicine (NLM) has launched a search for a scientific director. The scientific director will oversee a group of 150 scientific personnel, developing new approaches to data science, biomedical informatics, and computational biology.

In a blog post on the library’s website, director Patti Brennan, R.N., Ph.D., called the move a big step in revving up its intramural research operation.

One of the 27 Institutes and Centers of the National Institutes of Health (NIH), NLM creates and hosts major digital resources, tools, and services for biomedical and health literature, data, and standards, sending 115 terabytes of data to five million users and receiving 15 terabytes of data from 3,000 users every weekday.

NLM’s strategic plan for 2017-2027 positions it to become a platform for biomedical discovery and data-powered health. NLM anticipates continued expansion of its intramural research program to keep pace with growing demand for innovative data science and informatics approaches that can be applied to biomedical research and health and growing interest in data science across the NIH.

A Blue Ribbon Panel recently reviewed NLM’s intramural research programs and recommended, among other things, unifying the programs under a single scientific director. That shift also aligns the library with NIH’s other institutes and centers, most of which are guided by one scientific director.

NLM’s  intramural research program includes activities housed in both the Lister Hill National Center for Biomedical Communications (LHC) and the National Center for Biotechnology Information (NCBI). The researchers in these two centers develop and apply computational approaches to a broad range of problems in biomedicine, molecular biology, and health, but LHC focuses on medical and clinical data, while NCBI focuses on biological and genomic data.

But the Blue Ribbon Panel noted that the boundaries between clinical and biological data are dissolving, and the analytical and computational strategies for each are increasingly shared. “As a result, the current research environment calls for a more holistic view of biomedical data, one best served by shared approaches and ongoing collaborations while preserving the two centers’ unique identities, wrote Brennan, who came to NIH in 2016 from the University of Wisconsin-Madison, where she was the Lillian L. Moehlman Bascom Professor at the School of Nursing and College of Engineering.

She added that having a single scientific director should lead to a sharper focus on research priorities, fewer barriers to collaboration, the cross-fertilization of ideas and the optimization of scarce resources.

The new scientific director will be asked to craft a long-range plan that identifies research areas where the NLM can best leverage its unique position and resources. We’ll also look for ways to allocate more resources to fundamental research while streamlining operational support. “Down the road, we’ll expand our research agenda to include high-risk, high-reward endeavors, the kinds of things that raise profound questions and have the potential to yield tremendous impact,” she wrote.

Besides the scientific director, the NLM is also recruiting three investigators to complement its strengths in machine learning and natural language processing.





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Survey: Digital, AI Top Priorities in 2019, but EHRs Will Dominate IT Spend

January 22, 2019
by Heather Landi, Associate Editor
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Digital, advanced analytics, and artificial intelligence (AI) are top spending priorities for healthcare executives in 2019, but electronic health record (EHR) systems will dominate technology spending budgets, according to a recent technology-focused healthcare survey.

Damo Consulting, a Chicago-based healthcare growth and digital transformation advisory firm, surveyed technology and service provider executives and healthcare enterprise executives about how the demand environment for healthcare IT is changing and will impact the industry in the coming year. Damo Consulting’s third annual Healthcare IT Demand Survey also analyzes the challenges for healthcare organizations and the perceived impact of macro-level changes.

The report indicates technology vendors will continue to struggle with long sales cycles as they aggressively market digital and AI. For the second year in a row, the rise of non-traditional players such as Amazon and Google will have a strong impact on the competitive environment among technology vendors while EHR vendors grow in dominance.

Among the key findings from the survey, IT budgets are expected to grow by 20 percent or more, with healthcare executives indicating they are more upbeat about IT spend growth than vendors. All the healthcare executives who participated in the survey said digital transformation initiatives are gaining momentum in their enterprises.

However, the majority (75 percent) agree that rapid change in the healthcare IT landscape makes technology decisions harder and only 58 percent believe there are plenty of viable and ready-to-deploy solutions available today in emerging technologies such as AI and digital health solutions. Seventy-one percent agree that federal government policies have provided a boost to healthcare IT spend this past year.

Top IT priorities for healthcare enterprise executives in 2019 are digital, advanced analytics and AI. Of the survey respondents, 79 percent said accelerating digital health initiatives was a top priority and 58 percent cited investing in advanced analytics and AI capabilities as top priorities. However, modernizing IT infrastructure (25 percent) and optimizing EHRs (21 percent) are also significant priorities.

Technology vendors also see AI, advanced analytics and digital transformation as top areas of focus for next year, as those areas were cited by 75 percent and 70 percent of technology and service provider executives, respectively. Thirty-three percent of those respondents cited EHR optimization and 25 percent cited cybersecurity and ransomware. Thirteen percent cited M&A integration as a top area of focus in 2019.

However, EHR systems will dominate technology spending budgets, even as the focus turns to digital analytics, the survey found. Technology and service provider executives who participated in the survey identified EHR system optimization and cybersecurity as significant drivers of technology spend in 2019. Sixty percent of respondents said enterprise digital transformation and advanced analytics and AI would drive technology spend this year, but 38 percent also cited EHR optimization and cybersecurity/ransomware. One executive survey respondent said, “For best of breed solutions, (the challenge is) attracting enough mindshare and budget vs. EHR spends.”

When asked what digital transformation means, close to half of healthcare executives cited reimaging patient and caregiver experiences, while one quarter cited analytics and AI and 17 percent cited automation. As one executive said, “The biggest challenge for healthcare in 2019 will be navigating tightening margins and limited incentives to invest in care design.”

Healthcare executives are divided on whether digital is primarily an IT-led initiative, and are also divided on whether technology-led innovation is dependent on the startup ecosystem.

The CIO remains the most important buyer for technology vendors, however IT budgets are now sitting with multiple stakeholders, the survey found, as respondents also cited the CFO, the CTO, the CMIO and the chief digital officer.

“Digital and AI are emerging as critical areas for technology spend among healthcare enterprises in 2019. However, healthcare executives are realistic around their technology needs vs. their need to improve care delivery. They find the currently available digital health solutions in the market are not very mature,” Paddy Padmanabhan, CEO of Damo Consulting, said in a statement. “However, they are also more upbeat about the overall IT spend growth than their technology vendors.”

Looking at the technology market, healthcare executives perceive a lack of maturity in technology solution choices for digital initiatives, as well as a lack of internal capabilities for managing digital transformation. In the survey report, one executive said, “HIT architecture needs to substantially change from large monolithic code sets to an API-driven environment with multiple competing apps.”

A majority of healthcare enterprise executives view data silos and lack of interoperability as the biggest challenges to digital transformation. And, 63 percent believe the fee-for-service reimbursement model will remain the dominant payment model for the foreseeable future.

In addition, cybersecurity issues will continue to be a challenge for the healthcare sector in 2019, but not the biggest driver of technology spending or the top area of focus for health systems in the coming year, according to the survey.

Healthcare executives continue to be confused by the buzz around AI and digital and struggle to make sense of the changing landscape of who is playing what role and the blurred lines of capabilities and competition, according to the survey report. When asked who their primary choice is when looking for potential partners to help with digital transformation, 46 percent of healthcare executives cited their own internal IT and innovation teams, 17 percent cited their EHR vendor and 8 percent cited boutique consulting firms. A quarter of respondents cited “other.”

For technology vendors, the biggest challenge is long cycles, along with product/service differentiation and brand visibility.

The rise of non-traditional players, such as Amazon, Apple, and Google, will have a strong impact on the competitive healthcare technology environment, the survey responses indicated. At the same time, deeply entrenched EHR vendors such as Epic and Cerner will grow in dominance.


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