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Has Amazon Brought Something New To Healthcare Data Analytics?

Posted on November 29, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Amazon’s announcement that it was getting into healthcare data analytics didn’t come as a major surprise. It was just a matter of time.

After all, the retail giant has been making noises about its health IT ambitions for a while now, and its super-sneaky 1492 team’s healthcare feints have become common knowledge.

Now, news has broken that its massive hosting division, Amazon Web Services, is offering its Comprehend Medical platform to the healthcare world. And at the risk of being a bit too flip, my reaction is “so?” I think we should all take a breath before we look at this in apocalyptic terms.

First, what does Amazon say we’re looking at here?

Like similar products targeting niches like travel booking and supply-chain management, the company reports, Comprehend Medical uses natural language processing and machine learning to pull together relevant information from unstructured text.

Amazon says Comprehend Medical can pull needed information from physician notes, patient health records and clinical trial reports, tapping into data on patient conditions and medication dosage, strength and frequency.

The e-retailer says that users can access the platform through a straightforward API call, accessing Amazon’s machine learning expertise without having to do their own development or train models of their own. Use cases it suggests include medical cohort analysis, clinical decision support and improving medical coding to tighten up revenue cycle management.

Comprehend Medical customers will be charged a fee each month based on the amount of text they process each month, either $0.01 per 100-character unit for the NERe API, which extracts entities, entity relationships, entity traits and PHI, or $0.0014 per unit if they use its PHId API, which only supports identifying PHI for data protection.

All good. All fine. Making machine learning capabilities available in a one-off hosting deal — with a vendor many providers already use — can’t be wrong.

Now, let’s look coldly at what Amazon can realistically deliver.

Make no mistake, I understand why people are excited about this announcement. As with Microsoft, Google, Apple and other top tech influencers, Amazon is potentially in the position to change the way things work in the health IT sector. It has all-star brainpower, the experience with diving into new industries and enough capital to buy a second planet for its headquarters. In other words, it could in theory change the healthcare world.

On the other hand, there’s a reason why even IBM’s Watson Health stumbled when it attempted to solve the data analytics puzzle for oncologist. Remember, we’re talking IBM here, the last bastion of corporate power. Also, bear in mind that other insanely well-capitalized, globally-recognized Silicon Valley firms are still biding their time when it comes to this stuff.

Finally, consider that many researchers think NLP is only just beginning to find its place in healthcare, and an uncertain one at that, and that machine learning models are still in their early stages, and you see where I’m headed.

Bottom line, if Google or Microsoft or Epic or Salesforce or Cerner haven’t been able to pull this off yet, I’m skeptical that Amazon has somehow pole-vaulted to the front of the line when it comes to NLP-based mining of medical text. My guess is that this product launch announcement is genuine, but was really issued more as a stake in the ground. Definitely something I would do if I worked there.

Does NLP Deserve To Be The New Hotness In Healthcare?

Posted on August 30, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Lately, I’ve been seeing a lot more talk about the benefits of using natural language processing technology in healthcare. In fact, when I Googled the topic, I turned up a number of articles on the subject published over the last several weeks. Clearly, something is afoot here.

What’s driving the happy talk? One case in point is a new report from health IT industry analyst firm Chilmark Research laying out 12 possible use cases for NLP in healthcare.

According to Chilmark, some of the most compelling options include speech recognition, clinical documentation improvement, data mining research, computer-assisted coding and automated registry reporting. Its researchers also seem to be fans of clinical trial matching, prior authorization, clinical decision support and risk adjustment and hierarchical condition categories, approaches it labels “emerging.”

From what I can see, the highest profile application of NLP in healthcare is using it to dig through unstructured data and text. For example, a recent article describes how Intermountain Healthcare has begun identifying heart failure patients by reading data from 25 different free text documents stored in the EHR. Clearly, exercises like these can have an immediate impact on patient health.

However, stories like the above are actually pretty unusual. Yes, healthcare organizations have been working to use NLP to mine text for some time, and it seems like a very logical way to filter out critical information. But is there a reason that NLP use even for this purpose isn’t as widespread as one might think? According to one critic, the answer is yes.

In a recent piece, Dale Sanders, president of technology at HealthCatalyst, goes after the use of comparative data, predictive analytics and NLP in healthcare, arguing that their benefits to healthcare organizations have been oversold.

Sanders, who says he came to healthcare with a deep understanding of NLP and predictive analytics, contends that NLP has had ”essentially no impact” on healthcare. ”We’ve made incremental progress, but there are fundamental gaps in our industry’s data ecosystem– missing pieces of the data puzzle– that inherently limit what we can achieve with NLP,” Sanders argues.

He doesn’t seem to see this changing in the near future either. Given how much money has already been sunk in the existing generation of EMRs, vendors have no incentive to improve their capacity for indexing information, Sanders says.

“In today’s EMRs, we have little more than expensive word processors,” he writes. “I keep hoping that the Googles, Facebooks and Amazons of the world will quietly build a new generation EMR.” He’s not the only one, though that’s a topic for another article.

I wish I could say that I side with researchers like Chilmark that see a bright near-term future for NLP in healthcare. After all, part of why I love doing what I do is exploring and getting excited about emerging technologies with high potential for improving healthcare, and I’d be happy to wave the NLP flag too.

Unfortunately, my guess is that Sanders is right about the obstacles that stand in the way of widespread NLP use in our industry. Until we have a more robust way of categorizing healthcare data and text, searching through it for value can only go so far. In other words, it may be a little too soon to pitch NLP’s benefits to providers.

Healthcare Execs Investing In Intelligent Technologies Face Roadbumps

Posted on July 16, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A recent report from Accenture concludes that healthcare executives are enthusiastic about “intelligence technologies” such as AI and IoT. It also suggests, however, that health organizations will need to add new capabilities to be sure they can manage these technologies responsibly.

The report, based on a survey of 100 health executives, found that 77% of respondents expect to invest in IoT and smart sensors and that 53% expect to invest in AI systems.  Presumably, they expect these technologies to offer benefits more quickly.

Why the gap in adoption? The truth is that healthcare leaders haven’t yet gotten their arms around AI just yet. While IoT and smart sensor technology can boost the flexibility and “judgment” of enterprise systems, AI arguably has the potential to be far more flexible and wide-reaching — and ultimately less than predictable.

This unpredictability makes AI investment a bit trickier to implement than other emerging technologies. Just over four-fifths of health leaders said they were not prepared to explain AI-based conclusions to their internal stakeholders nor outsiders.

To address this deficit, 73% said they plan to develop internal ethical standards for AI to make sure these systems can act responsibly. Before that, they’ll need to determine what “acting responsibly” actually means — and as far as I know there are no accepted guidelines for developing such standards. (They might want to start off by reviewing Google’s ethical principles for AI use here.)

Adding AI to the enterprise IT mix could also wreak havoc. I for one was surprised to read that almost one-fourth of respondents said that they had been the target of adversarial AI behaviors, including falsified location data or bot fraud. (This stat blew my mind. Why haven’t we heard more about these “adversarial behaviors” and what are they?)

This certainly adds another element of uncertainty for CIOs interested in AI investments. While AI technologies can’t “think” in the traditional sense, they can create a range of problems previous-gen technology couldn’t.

This is part of a larger picture in which health organizations aren’t sure if their data has been corrupted. In fact, 86% of health execs said they hadn’t yet invested in technologies which could verify their data sources. Adding AI to the mix could potentially compound these problems, as it might create a cascade in which the AI then draws false inferences and takes inappropriate actions.

Meanwhile, respondents were excited about blockchain and smart contracts technology, with 91% reporting that they believed it would be a critical tool for supporting frictionless businesses over the next three years. All told, expect to see IoT and blockchain investments right away, with AI lagging until health IT leaders can teach it to play nicely.

Google And Fitbit Partner On Wearables Data Options

Posted on May 7, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Fitbit and Google have announced plans to work together, in a deal intended to “transform the future of digital health and wearables.” While the notion of transforming digital health is hyperbole even for companies the size of Google and Fitbit, the pairing does have plenty of potential.

In a nutshell, Fitbit and Google expect to take on both consumer and enterprise health projects that integrate data from EMRs, wearables and other sources of patient information together. Given the players involved, it’s hard to doubt that at least something neat will emerge from their union.

Among the first things the pair plans to use Google’s new Cloud Healthcare API to connect Fitbit data with EMRs. Of course, readers will know that it’s one thing to say this and another to actually do it, but gross oversimplifications aside, the idea is worth pursuing.

Also, using services such as those offered by Twine Health– a recent Fitbit acquisition — the two companies will work to better manage chronic conditions such as diabetes and hypertension. Twine offers a connected health platform which leverages Fitbit data to offer customized health coaching.

Of course, as part of the deal Fitbit is moving to the Google Cloud Platform, which will supply the expected cloud services and engineering support.

The two say that moving to the Cloud Platform will offer Fitbit advanced security capabilities which will help speed up the growth of Fitbit Health Solutions business. They also expect to make inroads in population health analysis. For its part, Google also notes that it will bring its AI, machine learning capabilities and predictive analytics algorithms to the table.

It might be worth a small caution here. Google makes a point of saying it is “committed” to meeting HIPAA standards, and that most Google Cloud products do already. That “most” qualifier would make me a little bit nervous as a provider, but I know, why worry about these niceties when big deals are afoot. However, fair warning that when someone says general comments like this about meeting HIPAA standards, it probably means they already employ high security standards which are likely better than HIPAA. However, it also means that they probably don’t comply with HIPAA since HIPAA is about more than security and requires a contractual relationship between provider and business associate and the associated liability of being a business associate.

Anyway, to round out all of this good stuff, Fitbit and Google said they expect to “innovate and transform” the future of wearables, pairing Fitbit’s brand, community, data and high-profile devices with Google’s extreme data management and cloud capabilities.

You know folks, it’s not that I don’t think this is interesting. I wouldn’t be writing about if I didn’t. But I do think it’s worth pointing out how little this news announcement says, really.

Yes, I realize that when partnerships begin, they are by definition all big ideas and plans. But when giants like Google, much less Fitbit, have to fall back on words like innovate and transform (yawn!), the whole thing is still pretty speculative. Just sayin’.

More Ways AI Can Transform Healthcare

Posted on April 25, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

You’ve probably already heard a lot about how AI will change healthcare. Me too. Still, given its potential, I’m always interested in hearing more, and the following article struck me as offering some worthwhile ideas.

The article, which was written by Humberto Alexander Lee of Tesser Health, looks at ways in which AI tools can reduce data complexity and detect patterns which would be difficult or even impossible for humans to detect.

His list of AI’s transformative powers includes the following:

  • Identifying diseases and providing diagnoses

AI algorithms can predict when people are likely to develop heart disease far more accurately than humans. For example, at Google healthcare technology subsidiary Verily, scientists created an algorithm that can predict heart disease by looking at the back of a person’s eyes and pinpoint early signs of specific heart conditions.

  • Crowdsourcing treatment options and monitoring drug response

As wearable devices and mobile applications mature, and data interoperability improves thanks to standards such as FHIR, data scientists and clinicians are beginning to generate new insights using machine learning. This is leading to customizable treatments that can provide better results than existing approaches.

  • Monitoring health epidemics

While performing such a task would be virtually impossible for humans, AI and AI-related technologies can sift through staggering pools of data, including government intelligence and millions of social media posts, and combine them with ecological, biogeographical and public health information, to track epidemics. In some cases, this process will predict health threats before they blossom.

  • Virtual assistance helping patients and physicians communicate clearly

AI technology can improve communication between patients and physicians, including by creating software that simplifies patient communication, in part by transforming complex medical terminology into digestible information. This helps patients and physicians engage in a meaningful two-way conversation using mobile devices and portals.

  • Developing better care management by improving clinical documentation

Machine learning technology can improve documentation, including user-written patient notes, by analyzing millions of rows of data and letting doctors know if any data is missing or clarification is needed on any procedures. Also, Deep Neural Network algorithms can sift through information in written clinical documentation. These processes can improve outcomes by identifying patterns almost invisible to human eyes.

Lee is so bullish on AI that he believes we can do even more than he has described in his piece. And generally speaking, it’s hard to disagree with him that there’s a great deal of untapped potential here.

That being said, Lee cautions that there are pitfalls we should be aware of when we implement AI. What risks do you see in widespread AI implementation in healthcare?

Nokia May Exit Digital Health Business

Posted on March 2, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

The digital health market has become phenomenally competitive over the last few years, with giants like Google and Apple duking it out with smaller, fast-moving startups over the choicest opportunities in the sector.

Even with a behemoth like Google, you expect to see some stumbles, and the Internet giant has taken a few. But seldom have we seen a billion-dollar company walk away from the digital health market, which arguably stands to grow far more. Still, according to a recent news report, that’s just what Nokia may be doing.

A story published in The Verge reports that the Finnish telecom giant has launched a strategic review of its health division. While Nokia apparently isn’t spilling the beans on its plans, the news site got a look at an internal company memo which suggests that its digital health business is indeed in trouble.

In the memo, The Verge says, Nokia chief strategy officer Kathrin Buvac wrote that “our digital health business has struggled to scale and meet its growth expectations… [And] currently, we don’t see a path for [the digital health business] to become a meaningful part of a company as large as Nokia.”

While it’s hard to tell much from a press release, it notes that Nokia’s digital health division makes and sells an ecosystem of hybrid smart watches, scales and digital health devices to consumers and enterprises. Its digital health history includes the acquisition of Withings, a French startup with a sexy line up of connected health-focused digital health devices.

This may be in part because it just hasn’t been aggressive enough or offered anything unique. In the wake of the Withings acquisition, Nokia doesn’t seem to have done much to build on Withings’ product line. Though much of the success in this market depends on execution, its current roster of products doesn’t sound like anything too exciting or differentiated.

It’s interesting to note that Buvac blames at least part of the failure of its digital health excursion on Nokia’s size. That doesn’t seem to be a problem for industry-leading companies like Apple, which seems to be carving out its digital health footprint one launch at a time and cultivating health leaders along the way. For example, Apple recently partnered with Stanford Medicine launch an app using its smartwatch to collect data on irregular heart rhythms. Arguably, this is the way to win markets and influence people — slow and steady.

In the end, though, Buvac is probably right about is digital health prospects. Nokia’s seeming failure may indeed be attributed to its sprawling portfolio, and probably an inflexible internal culture as well. The moral of the story may be that winning at the digital health game has far more to do with understanding the market than it does with having very deep pockets.

Key Articles in Health IT from 2017 (Part 2 of 2)

Posted on January 4, 2018 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The first part of this article set a general context for health IT in 2017 and started through the year with a review of interesting articles and studies. We’ll finish the review here.

A thoughtful article suggests a positive approach toward health care quality. The author stresses the value of organic change, although using data for accountability has value too.

An article extolling digital payments actually said more about the out-of-control complexity of the US reimbursement system. It may or not be coincidental that her article appeared one day after the CommonWell Health Alliance announced an API whose main purpose seems to be to facilitate payment and other data exchanges related to law and regulation.

A survey by KLAS asked health care providers what they want in connected apps. Most apps currently just display data from a health record.

A controlled study revived the concept of Health Information Exchanges as stand-alone institutions, examining the effects of emergency departments using one HIE in New York State.

In contrast to many leaders in the new Administration, Dr. Donald Rucker received positive comments upon acceding to the position of National Coordinator. More alarm was raised about the appointment of Scott Gottlieb as head of the FDA, but a later assessment gave him high marks for his first few months.

Before Dr. Gottlieb got there, the FDA was already loosening up. The 21st Century Cures Act instructed it to keep its hands off many health-related digital technologies. After kneecapping consumer access to genetic testing and then allowing it back into the ring in 2015, the FDA advanced consumer genetics another step this year with approval for 23andMe tests about risks for seven diseases. A close look at another DNA site’s privacy policy, meanwhile, warns that their use of data exploits loopholes in the laws and could end up hurting consumers. Another critique of the Genetic Information Nondiscrimination Act has been written by Dr. Deborah Peel of Patient Privacy Rights.

Little noticed was a bill authorizing the FDA to be more flexible in its regulation of digital apps. Shortly after, the FDA announced its principles for approving digital apps, stressing good software development practices over clinical trials.

No improvement has been seen in the regard clinicians have for electronic records. Subjective reports condemned the notorious number of clicks required. A study showed they spend as much time on computer work as they do seeing patients. Another study found the ratio to be even worse. Shoving the job onto scribes may introduce inaccuracies.

The time spent might actually pay off if the resulting data could generate new treatments, increase personalized care, and lower costs. But the analytics that are critical to these advances have stumbled in health care institutions, in large part because of the perennial barrier of interoperability. But analytics are showing scattered successes, being used to:

Deloitte published a guide to implementing health care analytics. And finally, a clarion signal that analytics in health care has arrived: WIRED covers it.

A government cybersecurity report warns that health technology will likely soon contribute to the stream of breaches in health care.

Dr. Joseph Kvedar identified fruitful areas for applying digital technology to clinical research.

The Government Accountability Office, terror of many US bureaucracies, cam out with a report criticizing the sloppiness of quality measures at the VA.

A report by leaders of the SMART platform listed barriers to interoperability and the use of analytics to change health care.

To improve the lower outcomes seen by marginalized communities, the NIH is recruiting people from those populations to trust the government with their health data. A policy analyst calls on digital health companies to diversify their staff as well. Google’s parent company, Alphabet, is also getting into the act.

Specific technologies

Digital apps are part of most modern health efforts, of course. A few articles focused on the apps themselves. One study found that digital apps can improve depression. Another found that an app can improve ADHD.

Lots of intriguing devices are being developed:

Remote monitoring and telehealth have also been in the news.

Natural language processing and voice interfaces are becoming a critical part of spreading health care:

Facial recognition is another potentially useful technology. It can replace passwords or devices to enable quick access to medical records.

Virtual reality and augmented reality seem to have some limited applications to health care. They are useful foremost in education, but also for pain management, physical therapy, and relaxation.

A number of articles hold out the tantalizing promise that interoperability headaches can be cured through blockchain, the newest hot application of cryptography. But one analysis warned that blockchain will be difficult and expensive to adopt.

3D printing can be used to produce models for training purposes as well as surgical tools and implants customized to the patient.

A number of other interesting companies in digital health can be found in a Fortune article.

We’ll end the year with a news item similar to one that began the article: serious good news about the ability of Accountable Care Organizations (ACOs) to save money. I would also like to mention three major articles of my own:

I hope this review of the year’s articles and studies in health IT has helped you recall key advances or challenges, and perhaps flagged some valuable topics for you to follow. 2018 will continue to be a year of adjustment to new reimbursement realities touched off by the tax bill, so health IT may once again languish somewhat.

Google Fit and Other Fitness Trackers

Posted on February 10, 2016 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I’ve always been intrigued by the various fitness trackers. I’ve never been that excited about their pure healthcare value, but I do believe that the amount we move (or don’t move) matters to our health. So, it makes since to track how much we move as one element of your health.

The problem I’ve had with all the fitness trackers I’ve used is that they end up in a drawer far too quick. In fact, I could never reliably wear one. My wife did better and made it a few weeks, but I just hated having a device attached to me. So, it never worked for me. (Side Note: HIMSS16 has a fitness challenge and they’re even accepting donations of fitness tracker devices you have gathering dust in your drawer.)

The closest I’ve come to a fitness tracker working for me is my cell phone. I was excited when my Samsung Galaxy S5 had the S Health app loaded on it and would track my steps and it could even do my heart rate. It was novel to see my step counts and see the trend over time. I was always excited when I’d go dancing and my step count would go through the roof and blow away all the goals that it had set for me.

I’ve since switched to the Google Nexus phone which has Google Fit built in. It has a similar step tracker and I definitely turned on Google Fit when I started with the phone. However, then I never heard or saw any notifications about it. I did’t really even realize it was on. Then, this week I got the notification from it that Google Fit was going to be disabled to save my battery since I hadn’t opened it in a long time (I can’t remember how many months they said).

What can I say? I totally forgot that it was even tracking me and it didn’t tell me that it was doing it. I do remember getting a notification or two that I’d had an active hour or something, but I’d just give myself a pat on the back and swipe off the notification. I guess that’s not considered using the app.

The other reason I probably didn’t care as much about the Google Fit tracking is that I knew that it was only tracking a small part of my movement since the cell phone is often with me, but not always. I work from home and so when I’m home I take my cell phone out of my pocket and it sits on my desk all day. That means it’s not tracking any of my movement during most days. I also play a lot of sports and I don’t want my cell phone in my pocket while I play. I guess that’s why all the Fitness trackers are these little devices that you could potentially wear while playing. Although, that feels like work and for what value?

Many have been dealing with this for years. What’s interesting is that I’ve been watching it for years as well and not much has changed. Is it nice that Google Fit is tracking my activity with almost no effort from me? Definitely, but with all the gaps in data it’s collecting, is that data really all that meaningful?

Would love to hear other people’s experiences with these trackers. Is there something new that’s changed your perspective on things?

Fitness Tracking Apps and Cell Phone Batteries

Posted on November 4, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

One of the big challenges of any mobile health app is how much it drains your battery. While processing power, storage, and pretty much every other technology in a cell phone has improved the one nut we haven’t yet cracked is batteries. Although, I’m hopeful that we’re close to cracking the innovation in batteries soon too.

Until we do, battery usage is always a concern with mobile health applications. This is particularly true with passive activity tracking apps. They can suck your battery dry if they’re not designed properly and we all know how quickly apps get removed from our phones if they’re responsible for reducing our battery life.

One passive fitness tracker, Human, has tackled this problem head on. Here’s how Techcrunch describes their efforts to minimize Human’s drain on your battery:

The app now relies as much as possible on the motion coprocessor in your iPhone 5s, 6 or 6s. Human now has 50 percent less battery impact. And if you really need to get the most out of your phone, there is a new low power mode to reduce battery usage by up to 90 percent.

Until we solve the batter problems we all face, we’re going to see more effort spent on how we manage battery usage. We saw the same problem with the original Google Glass. The battery on the original Google Glass was about 30 minutes of active usage (ie. video). I read one report that Google Glass 2.0 is going to last 22 hours by comparison.

What other battery improvements do you see happening to help mobile health applications?

Future Google Medical Tracking Watch

Posted on July 8, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I don’t know how I missed the news that Google is making a medical watch focused on tracking your health. Here’s an excerpt from The Verge article:

The wristband is being developed by Google X, the secretive lab behind projects like Glass, Loon, and the company’s self-driving cars. It won’t be available to general consumers. Instead, Google intends for the device to be used in clinical trials and prescribed to medical patients.

Talk about a fundamentally different way to approach a smart watch. The last line begs the question of whether the Google Watch is going to be FDA cleared. It seems like it would need to be if it’s being “prescribed” to patients.

I find this approach absolutely intriguing and a welcome site in healthcare. I’ve often said that a company whose built in the capability of getting a device or app FDA cleared is going to have a big advantage over the thousands of mHealth companies which are just skirting by without an FDA clearance. It seems that Google is building this capability which will put it in a prime place to really disrupt healthcare.

Obviously, it’s very early in the process of them creating an FDA cleared (assuming they go that direction) Google smart watch, but the idea is intriguing. I think it’s going to take an FDA cleared smart watch to really get the attention of doctors.