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Dr. AI Will See You Now: Machines and the Future of Medicine

December 18, 2018
by Dr. Gautam Sivakumar, Industry Voice, CEO, Medisas
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Artificial intelligence (AI) has been a hot topic lately. Much has been said about its promise to improve our lives, as well as its threat to replace jobs ranging from receptionists to radiologists. These wider discussions have naturally led to some interesting questions about the future of medicine. What role will human beings have in an ever-changing technology landscape? When AI becomes a better "doctor," what will become of doctors? How will patients and medical professionals adjust to these changes?

While it is, of course, hard to make accurate predictions about the distant future, my experience both as a doctor and now CEO of a software company that uses AI to help doctors deliver safer care, gives me some insight into what the intermediate future will hold for the medical profession.

Medicine is one of the great professions in every culture in the world—an altruistic, challenging, aspirational vocation that often draws the best and the brightest. Doctors spend years in training to make decisions, perform procedures, and guide people through some of their most vulnerable points in life. But medicine is, for the most part, still stuck in a pre-internet era. Entering a hospital is like walking into a time capsule to a world where people still prefer paper, communication happens through pagers, and software looks like it’s from the 1980s or 1990s.

But this won’t last; three giant forces of technology have been building over the last few years, and they are about to fundamentally transform healthcare: the cloud, mobile, and AI. The force least understood by doctors is AI; after all, even technophobic doctors now spend a lot of time using the internet on their smartphones. Even so, AI is the one that will likely have the biggest impact on the profession.

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A lot of people believe that AI will become the primary decision maker, replacing human doctors. In that eventuality, Dr. AI will still need a human “interface,” because it is likely patients will need the familiarity of a human to translate the AI’s clinical decision making and recommendations. I find it an intriguing thought—going to the doctor’s office and seeing a human whose job it is to read the recommendations of a computer just to offer the human touch.

But to understand what the future could hold, we must first understand the different types of problems that need to be solved. Broadly, problems can be split into simple, complicated, and complex ones. Simple and complicated problems can be solved using paradigmatic thought (following standardized sets of rules), something computers excel at. What makes complex problems unique is that they require judgment based on more than just numbers and logic. For the time being, the modern machine learning techniques that we classify as “AI” are not well suited to solving complex problems that require this deeper understanding of context, systems, and situation.

Given the abundance of complex problems in medicine, I believe that the human “interfaces” in an AI-powered future won't simply be compassionate people whose only job is to sit and hold the hand of a patient while reading from a script. These people will be real doctors, trained in medicine in much the same way as today—in anatomy, physiology, embryology, and more. They will understand the science of medicine and the decision making behind Dr. AI. They will be able to explain things to the patient and field their questions in a way that only people can. And most importantly, they will be able to focus on solving complex medical problems that require a deeper understanding, aided by Dr. AI.

I believe that the intermediate future of medicine will feel very similar to aviation today. Nobody questions whether commercial airline pilots should still exist, even though computers and autopilot now handle the vast majority of a typical flight. Like these pilots, doctors will let "auto-doc" automate the routine busy work that has regrettably taken over a lot of a clinician’s day—automatically tackling simple problems that only require human monitoring, such as tracking normal lab results or following an evidence-based protocol for treatment. This will let doctors concentrate on the far more complex situations, like pilots do for takeoffs and landings.

Dr. AI will become a trusted assistant who can help a human doctor make the best possible decision, with the human doctor still acting as the ultimate decision maker. Dr. AI can pull together all of the relevant pieces of data, potentially highlighting things a human doctor may not normally spot in an ocean of information, while the human doctor can take into consideration the patient and their situation as a whole.

Medicine is both an art and a science, requiring doctors to consider context when applying evidence-based practices. AI will certainly take over the science of medicine in the coming years but most likely won't take over the art for a while. However, in the near future, doctors will need to evolve from being scientists who understand the art of medicine to artists who understand the science.

Dr. Gautam Sivakumar is the CEO of Medisas


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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 (https://www.auntminnieeurope.com/index.aspx?sec=sup&sub=aic&pag=dis&ItemID=616828) 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 (https://www.healthcare.siemens.com/infrastructure-it/artificial-intelligence/ai-rad-companion).  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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