Watson Works with AMA, Cerner to Create Health Data Model

December 1, 2017

We see IBM Watson is doing the partner thing again, this time with the American Medical Association (AMA). I guess they were not satisfied with blockchain applications and the i2 line of business after all. Forbes reports, “AMA Partners With IBM Watson, Cerner on Health Data Model.” Contributor Bruce Japsen cites James Madera of the AMA when he reports that though the organization has been collecting a lot of valuable clinical data, it has not yet been able to make the most of it. Of the new project, we learn:

The AMA’s ‘Integrated Health Model Initiative’ is designed to create a ‘shared framework for organizing health data , emphasizing patient-centric information and refining data elements to those most predictive of achieving better outcomes.’ Those already involved in the effort include IBM, Cerner, Intermountain Healthcare, the American Heart Association, the American Academy of Family Physicians and the American Medical Informatics Association. The initiative is open to all healthcare and information stakeholders and there are no licensing fees for participants or potential users of what is eventually created. Madara described the AMA’s role as being like that of Switzerland: working to tell companies like Cerner and IBM what data elements are important and encouraging best practices, particularly when patient care and clinical information is involved. The AMA, for example, would provide ‘clinical validation review to make sure there is an evidence base under it because we don’t want junk,’ Madara said.

IBM and Cerner each have their own healthcare platforms, of course, but each is happy to work with the AMA. Japsen notes that as the healthcare industry shifts from the fee-for-service approach to value-based pricing models, accurate and complete information become more crucial than ever.

Cynthia Murrell, December 1, 2017

Consumer Health Search: An Angle for an Amazon Black Friday Sale?

November 24, 2017

I read “How Consumers Search for Health Care.” What struck me as interesting about this article’s information was that the data reminded me of research conducted i 1986 by the one time commercial online giant Information Access, a unit of Ziff Communications. We developed the Health Reference Center, which was an innovative service at that time. A kiosk allowed a user to obtain curated information about a medical condition. I recall we placed these Health Reference Centers in libraries and a handful of forward thinking health care facilities. We did tons of research, and the product included a number of interesting features.

I matched the findings reported in the article with my recollection of some of the research we conducted as part of the IAC product development process. One finding which was decidedly different was the preference for millennials for convenience. If the data in the article are accurate, 40 percent of the millennials in the sample like convenience which translates to mobile usage and online scheduling.

Other data points were in line with the findings from three decades ago; for example, ease of use and finding solutions that would be covered by insurance companies.

What do these data suggest? Health care is unlikely to be able to deal with expectations for mobile scheduling and patient convenience. As for shopping around for a deal on a treatment or procedure, Amazon, not established health care providers, may be encouraged to enter the field.

Black Friday deals on nose jobs and hip replacements may sound interesting to the Bezos behemoth. Use an Amazon credit card? One might get some Amazon credits which might be applied to the next procedure. Prime cut?

Stephen E Arnold, November 24, 2017

Healthcare Analytics Projected to Explode

November 21, 2017

There are many factors influencing the growing demand for healthcare analytics: pressure to lower healthcare costs, demand for more personalized treatment, the emergence of advanced analytic technology, and impact of social media.  PR Newswire takes a look at how the market is expected to explode in the article, “Healthcare Analytics Market To Grow At 25.3% CAGR From 2013 To 2024: Million Insights.”  Other important factors that influence healthcare costs are errors in medical products, workflow shortcomings, and, possibly the biggest, having cost-effective measures without compromising care.

Analytics are supposed to be able to help and/or influence all of these issues:

Based on the component, the global healthcare analytics market is segmented into services, software, and hardware. Services segment held a lucrative share in 2016 and is anticipated to grow steady rate during the forecast period. The service segment was dominated by the outsourcing of data services. Outsourcing of big data services saves time and is cost effective. Moreover, Outsourcing also enables access to skilled staff thereby eliminating the requirement of training of staff.

The cloud-based delivery is anticipated to grow and be the most widespread analytics platform for healthcare.  It allows remote access, avoids complicated infrastructures, and has real-time data tracking.  Adopting analytics platforms help curb the rising problems from cost to workforce to treatment the healthcare industry faces and will deal with in the future.  While these systems are being implemented, the harder part is determining how readily workers will be correctly trained on using them.

Whitney Grace, November 21, 2017

Is This the End of the Middleman?

September 20, 2017

The introduction of the internet began to reduce the need for professional intermediaries back in the 1990s, but that trend has accelerated with today’s AI capabilities. The Korea Times examines the matter in, “AI Invigorates ‘Scissors Economy’.”  The term “scissors economy” harkens back to 1999’s Market Shock by Todd Buchholz, in which that author coined the phrase to describe the shrinking reliance on go-betweens prompted by online technologies.

Some of the businesses that have been affected by these changing circumstances included brick-and-mortar stores, travel agents, stockbrokers, and insurance agents. It should come as no surprise– technologies that give consumers more direct control necessarily abridge nearly any transaction, cutting out professional intercessors. Writer Yoon Sung-won observes:

Expectations are that the phenomenon of the scissors economy will gain more strength as industries expedite introducing AI technologies in actual businesses. For instance, financial institutions such as banks, brokerage houses and insurance companies have started to use AI-based technologies not just to recommend optimal financial products to their clients but also to make decisions such as whom to grant loans to and where to invest. In the process, less and less human intervention is needed. Online shopping malls are also rushing to adopt new type of services, also based on AI technologies. Upon the customers’ agreement, online shopping platform operators collect information on their preferences to recommend products for customers to purchase. Internet and gaming service providers also use AI technologies to analyze their users to understand consumption patterns. Advanced medical institutions such as cancer centers are also tapping into AI technologies. In Korea, multiple hospitals including Gachon University Gil Medical Center have introduced IBM’s Watson AI system to give medical advice.

Yoon cites an “industry source” when noting that not many workers have been directly replaced by AI systems yet, but that it is only a matter of time. We’re also cautioned—maybe those humans-in-the-middle are actually beneficial. What world will we create when we hand as much decision-making to algorithms as possible?

Cynthia Murrell, September 20, 2017

Alexa Gets a Physical Body

September 20, 2017

Alexa did not really get physical robot body, instead, Bionik Laboratories developed an Alexa skill to control their AKRE lower-body exoskeleton.  The news comes from iReviews’s article, “Amazon’s Alexa Can Control An Exoskeleton With Verbal Instructions.”

This is the first time Alexa has ever been connected to an exoskeleton and it could potentially lead to amazing breakthroughs in prosthetics.  Bionik Laboratories developed the exoskeleton to help older people and those with lower body impairments.  Users can activate the exoskeleton through Alexa with simple commands like, “I’m ready to stand” or “I’m ready to walk.”

As the population ages, there will be a higher demand for technology that can help senior citizens move around with more ease.

The ARKE exoskeleton has the potential to help in 100% of all stroke survivors who suffer from lower limb impairment. A portion of wheelchair-bound stroke survivors will be eligible for the exoskeleton. For spinal cord injury patients, Bionik Labs expects to treat 80% of all cases with the ARKE exoskeleton. There is also potential for patients with quadriplegia or incomplete spinal cord injury.

Bionik Laboratories plans to help people regain their mobility and improve their quality of life.  The company is focusing on stroke survivors and other mobile-impaired patients.  Pairing the exoskeleton with Alexa demonstrates the potential home healthcare will have in the future.  It will also feed imaginations as they wonder if the exoskeletons can be programmed not only walk and run but search and kill?  Just a joke, but the potential for aiding impaired people is amazing.

Whitney Grace, September 20, 2015

Drugmaker Merk Partners with Palantir on Data Analysis

July 21, 2017

Pharmaceutical company Merk is working with data-analysis firm Palantir on a project to inform future research, we learn from the piece, “Merk Forges Cancer-Focused Big Data Alliance with Palantir” at pharmaceutical news site PMLive. The project is an effort to remove the bottleneck that currently exists between growing silos of medical data and practical applications of that information. Writer Phil Taylor specifies:

Merck will work with Palantir on cancer therapies in the first instance, with the aim of developing a collaborative data and analytics platform for the drug development processes that will give researchers new understanding of how new medicines work. Palantir contends that many scientists in pharma companies struggle with unstructured data and information silos that ‘reduce creativity and limit researchers’ corrective analyses’. The data analytics and sharing platform will help Merck researchers analyse real-world and bioinformatics data so they can ‘understand the patients who may benefit most’ from a treatment.

The alliance also has a patient-centric component, and according to Merck will improve the experience of patients using its products, improve adherence as well as provide feedback on real-world efficacy.

Finally, the two companies will collaborate on a platform that will allow improved global supply chain forecasting and help to get medicines to patients who need them around the world as quickly as possible. Neither company has disclosed any financial details on the deal.

This is no surprise move for the 125-year-old Merk, which has been embracing digital technology in part by funding projects around the world. Known as MSD everywhere but the U.S. and Canada, the company started with a small pharmacy in Germany but now has its headquarters in New Jersey.

Palantir has recently stirred up some controversy. The company’s massive-scale data platforms allow even the largest organizations to integrate, manage, and secure all sorts of data. Its founding members include PayPal alumni and Stanford computer-science grads. The company is based in Palo Alto, California, and has offices around the world.

Cynthia Murrell, July 21, 2017

Big Data in Biomedical

July 19, 2017

The biomedical field which is replete with unstructured data is all set to take a giant leap towards standardization with Biological Text Mining Unit.

According to PHYS.ORG, in a peer review article titled Researchers Review the State-Of-The-Art Text Mining Technologies for Chemistry, the author states:

Being able to transform unstructured biomedical research data into structured databases that can be more efficiently processed by machines or queried by humans is critical for a range of heterogeneous applications.

Scientific data has fixed set of vocabulary which makes standardization and indexation easy. However, most big names in Big Data and enterprise search are concentrating their efforts on e-commerce.

Hundreds of new compounds are discovered every year. If the data pertaining to these compounds is made available to other researchers, advancements in this field will be very rapid. The major hurdle is the data is in an unstructured format, which Biological Text Mining Unit standards intend to overcome.

Vishal Ingole, July 19, 2017

Study: Social Media and Young People

July 19, 2017

Some of us elders have been saying it for years, but now research seems to confirm it—social media can be bad for mental health.  The Next Web reports, “Study: Snapchat and Instagram Are the Worst for Young People.” The study is from the UK’s Royal Society for Public Health (RSPH), and the “young people” sampled are 1,479 Brits aged 14-24. An explanatory three-minute video from the RSPH accompanies the article. Writer Rachel Kaser reports:

The researchers surveyed 1,479 British youths ages 14-24, asking them how they felt the different social media networks effected their mental health. They took in several factors such as body image, sleep deprivation, bullying, and self-identity. The results suggest the two worst social media networks for kids are Instagram and Snapchat, as they had terrible scores for body image, bullying, and anxiety. Twitter and Facebook weren’t much better, though. YouTube was the only one that apparently inspired more positive feelings than negative ones. It could be because Snapchat and Instagram are image-based apps, meaning it’s not easy for users to avoid visual comparisons. Both apps ranked high on ‘Fear of Missing Out,’ and the researchers suggested this was likely to foster anxiety in fellow users.

I recommend the video for interested readers. It shows some respondents’ answers to certain questions, and clearly summarizes the pros and cons of each platform examined. It helpfully concludes with a list of concrete suggestions: Implement pop-up notifications that tell users when they’ve been online for a certain amount of time; require watermarks on photos that have been digitally altered; educate folks on the healthy use of social media; and incorporate analysis tools to identify users at risk for poor mental health and “discreetly” steer them toward help. It does seem such measures could help; will social-media companies cooperate?

Cynthia Murrell, July 19, 2017

Hope for Improvement in Predictive Modeling

July 18, 2017

A fresh approach to predictive modeling may just improve the process exponentially. Phys.org reports, “Molecular Dynamics, Machine Learning Create ‘Hyper-Predictive Computer Models.” The insight arose, and is being tested, at North Carolina State University.

The article begins by describing the incredibly complex and costly process of drug development, including computer models that predict the effects of certain chemical compounds. Such models traditionally rely on QSAR modeling and molecular docking. We learn:

Denis Fourches, assistant professor of computational chemistry, wanted to improve upon the accuracy of these QSAR models. … Fourches and Jeremy Ash, a graduate student in bioinformatics, decided to incorporate the results of molecular dynamics calculations – all-atom simulations of how a particular compound moves in the binding pocket of a protein – into prediction models based on machine learning. ‘Most models only use the two-dimensional structures of molecules,’ Fourches says. ‘But in reality, chemicals are complex three-dimensional objects that move, vibrate and have dynamic intermolecular interactions with the protein once docked in its binding site. You cannot see that if you just look at the 2-D or 3-D structure of a given molecule.’

See the article for some details about the team’s proof-of-concept study. Fourches asserts the breakthrough delivers a simulation that would previously have been built over six months in a mere three hours. That is quite an improvement! If this technique pans out, we could soon see more rapid prediction not only in pharmaceuticals but many other areas as well. Stay tuned.

Cynthia Murrell, July 18, 2017

Can an Algorithm Tame Misinformation Online?

June 23, 2017

UCLA researchers are working on an algorithmic solution to the “fake news” problem, we learn from the article, “Algorithm Reads Millions of Posts on Parenting Sites in Bid to Understand Online Misinformation” at TechRadar. Okay, it’s actually indexing and text analysis, not “reading,” but we get the idea. Reporter Duncan Geere tells us:

There’s a special logic to the flow of posts on a forum or message board, one that’s easy to parse by someone who’s spent a lot of time on them but kinda hard to understand for those who haven’t. Researchers at UCLA are working on teaching computers to understand these structured narratives within chronological posts on the web, in an attempt to get a better grasp of how humans think and communicate online.

Researchers used the hot topic of vaccinations, as discussed on two parenting forums, as their test case. Through an examination of nearly 2 million posts, the algorithm was able to come to accurate conclusions, or “narrative framework.” Geere writes:

While this study was targeted at conversations around vaccination, the researchers say the same principles could be applied to any topic. Down the line, they hope it could allow for false narratives to be identified as they develop and countered by targeted messaging.

The phrase “down the line” is incredibly vague, but the sooner the better, we say (though we wonder exactly what form this “targeted messaging” will take). The original study can be found here at eHealth publisher JMIR Publications.

Cynthia Murrell, June 23, 2017

 

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