Data-driven haircare, blockchain-enabled long island ice tea or artificially intelligent toilet paper: the buzzwords of our time seem to be everywhere, and digital health is no exception. Sometimes it even seems to be the breeding ground of overhyped technologies and overmarketing. Here, we collected the most often used digital health buzzwords and placed them on our buzzword radar.

Digital health is ripe for hype

As digital health is gaining momentum, more and more companies come forward with their disruptive ideas; or at least with their claims about having built disruptive digital health solutions. For the reason that online presence or at least some digital dimension are intrinsic to these products, that imposes specific features to their marketing behavior. As information flows faster and reaches more people than ever, while everybody else has that very same condition, the number one challenge is to stand out from the crowd.

As the online space seems to value sensationalist titles, brands, and messages, digital health companies are also inclined to participate in the big game for attention. Even if that means overselling their technology or using trendy buzzwords. For example, in the case of the blockchain, Reuters explained in its analysis, the average share price of companies who have jumped on the bandwagon and put the word “blockchain” into their name, has risen more than threefold since their re-branding. These conditions serve entrepreneurs who do not necessarily wish to create better healthcare through their inventions but go for big money in a relatively short time. We are against those, entirely.

digital health buzzwords

The guardians of the digital health galaxy

Although it takes time to recognize when something cannot go beyond the hype, sooner or later overhypers get caught, and if they cannot live up to their customers’ expectations, they will fail terribly. Just look at what happened with Elizabeth Holmes and Theranos. She promised to revolutionize blood testing, and investors flocked to the company. However, after the Wall Street Journal raised its serious concerns about the viability of the project, in July 2016, regulators decided to revoke Theranos’ license to operate a lab in California because of unsafe practices and to ban Holmes from the blood-testing business for at least two years. That’s a significant backlash to the once $9-billion worth company. Since then, it turned out there is not even proof or evidence that Theranos did what they claim they did.

Theranos-like stories are especially damaging as they undermine scientific achievements as well as the power of digital health technologies. Thus, The Medical Futurist undertakes the role of the “voluntary policeman” or the guardian of the digital health galaxy to filter out companies with overhyped and oversold technologies and propagates the ones whose claims correlate with their actual achievements. Here, we collected all the digital health buzzwords that make health technology companies look suspicious up to the point when they prove us wrong.

As The Medical Futurist is an entirely independent organization – we do not use advertisements on our pages, we do not accept any financial contributions or support when reviewing products -, we have no interest in clickbait headlines or in supporting sensationalist companies. On the contrary! We love to seek out companies who say more than they can provide and we take pride in questioning them publicly. Now, let’s see which buzzwords are we going after.

digital health buzzwords
Source: PATRICK HERTZOG/AFP/Getty Images

Artificial intelligence equals an Excel spreadsheet?

Every company is developing artificial intelligence-solutions these days. Christina Farr, a CNBC health journalist, said in her interview to Medgadget that the term is used very liberally, and in some cases, these data analysis-type projects are just a little bit more than an Excel spreadsheet.

It goes without saying that the tendency to represent a wide variety of companies and their activities under the umbrella of artificial intelligence solution building undermines the credibility and potential of A.I. in the health industry and damages the reputation of enterprises building genuinely innovative solutions. We believe the best antidote is to clear up the fog of misconceptions and confusions.

Health market players who claim to use A.I., apply in fact artificial narrow intelligence (ANI), mostly natural language processing and computer image. In healthcare, medical imaging enterprises build on these technologies extensively. These narrowly intelligent programs defeat humans in specific tasks, such as IBM’s supercomputer Deep Blue winning at chess but solving other duties requires much more complex narrow programs to be built, and it is an immense challenge. Thus, at present, we are nowhere close to artificial general intelligence (AGI), that level of intelligence when a machine is capable of abstracting concepts from limited experience and transferring knowledge between domains.

digital health buzzwords

Machine learning, deep learning, and big data

If A.I. weren’t enough, big data, deep learning, machine learning, smart algorithms, augmented intelligence, cognitive computing or big data analysis all line up next to artificial intelligence as the most popular expressions for innovation nowadays. No worries, we guide you through it, and if you want to read more on the subject, here’s some food for thought.

For reaching ANI, massive data sets and specific algorithms, which are making sense of that enormous amount of information through machine learning, are necessary. So, the first step: big data, which actually only refers to extensive data sets, inside and outside of a company, that can be analyzed to reveal trends, patterns, and associations, mainly related to human interactions and behaviors.

Using sophisticated data analyzing methods on big data sets in themselves is not artificial intelligence, however. And sometimes you can even have better results without it. For example, in a small Hungarian hospital, the pre-treatment waiting time for oncology patients dropped drastically from 54 to 21 days only by optimizing patient management processes with the help of simple methods such as recording and following-up cases closely.

On the other hand, machine learning is the field of computer science that enables computers to learn without being explicitly programmed and builds on top of computational statistics and data mining. Deep learning is the subfield of machine learning where computers learn with the help of layered neural networks. So when companies start using any of these buzzwords, be careful and ask around what they are actually up to.

digital health buzzwords

The goldmine behind cryptocurrencies: blockchain

No wonder that there are hundreds of companies, start-ups, enterprises, ventures experimenting with blockchain technology. The hype is extreme. Similarly, as in the case of artificial intelligence, there are crazy places where the mechanism behind cryptocurrencies pops up. Just look at how Kodak and Long Island Ice Tea tried to leverage on the blockchain.

But what the hell is it and who is using it in healthcare? When The Medical Futurist asked Ivo Lohmus from Guardtime, an Estonian company developing K.S.I. blockchain technology, he said to imagine it as a shared book of records, or in more technical terms, a distributed database that’s designed in such a smart way that whatever is added to this database, is immutable. As if it is carved into stone. Any change becomes immediately evident. Moreover, there is no central authority to decide what’s right or wrong. No bank, no regulator, no oversight. The participants need to signify they accept a shared consensus.

So, why is it a win for healthcare? As the blocks are impossible to change you cannot delete or change anything without leaving a trace. That is critical in the case of health data. It could secure health records, clinical trial records or ensure regulatory compliance. In pharma, the most apparent use of blockchain is securing the supply chain and fighting against counterfeit drugs. And here, we collected the best examples of companies using blockchain in healthcare so you can navigate in the blockchain jungle successfully.

digital health buzzwords

What’s coded in your genes?

Due to the collapse of the price of genetic testing and the FDA’s gradual ease of the regulatory environment, direct-to-consumer (DTC) genetic testing companies are booming – and they offer the wildest services imaginable. Do you want to know whether your kid is talented in football? Whether your grumpy moods are coded in your genes? Who is your perfect match based on your DNA? Order a DNA test! No wonder that even Stephen Colbert joked about how Orig3n wanted to organize a giveaway of free DNA tests to fans before a Baltimore Ravens game. There are hundreds of ventures trying to find their niche on the DTC genetic testing market with all available marketing means, and it is more and more difficult for customers to separate the wheat from the chaff.

The Medical Futurist can only tell you one advice and offer our article on the topic: no matter what DTC companies try to sell you, beyond ancestry, specific health risks, and limited application of nutrigenomics, you cannot get to know much more – and you should most certainly not order your drink based on genetically influenced wine recommendations.

digital health buzzwords

The ultimate digital health buzzword product

So what do you get if you combine all the buzzwords around digital health? Imagine that you and your significant other just had a baby, and you are concerned about the little one’s health. You purchase a baby monitor. At first, you’re tasked to send back the cheek swab of your child, and within 2-3 weeks, the enterprise provides you with the genetic test results. The company says that it’s necessary to know the possible health risks as well as genetically determined development curves of the baby to be able to sensitively monitor how the little one progresses. But consumers do not have to worry because all the genetic data is stored on a platform secured by blockchain next to all the other types of data that the baby monitor generates while listening how the baby sleeps or moves, what hydration levels or heart rate the little one has.

If you see all the above in the description of a product – run! At the moment, it is impossible to apply artificial intelligence solutions, blockchain technology, the advancement of genetics as well as sensory oversight into one device credibly. In many cases, it’s even problematic to create an accurate and reliable product by only using one of the buzzwords. So, we recommend you to be careful and watch out for A.I., blockchain, DNA-based offerings or big data solutions. And if you see something suspicious, reach out to us!