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Smartphone Strategy May Cause Health Data Interoperability Problems

Posted on July 13, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Tonight I was out at my local electronics store looking over the latest in Samsung gear. While chatting with the salesman behind the Samsung counter, I picked up a wireless charging pad and asked what it cost. “Don’t bother,” he said. “That won’t work with your phone,” which happens to be a none-too-old Galaxy Note Edge.

New batteries? Same problem. I strongly suspect that the lovely VR gear, headset and smart watch on display suffer from the same limitations. And heaven knows that these devices wouldn’t work with products produced by other Android-compatible manufacturers.

Now, I am no communications industry expert. So I won’t hold forth on whether Samsung’s decision to create a network of proprietary devices is a smart strategy or not. Intuitively, my guess is that the giant manufacturer is making a mistake in trying to lock in customers this way, but I don’t have data upon which to base that claim.

But when it comes to health IT, it’s clearer to me how things might play out. And I’d argue that Samsung’s emerging strategy should generate concern among providers.

Interconnecting proprietary tech is far from new. In fact, Apple long ago won the battle to force its users onto its proprietary platform, and AFAIK, the computing and media giant has never back down from the stance, including where its telecommunications gear was concerned. But at least until recently, we’ve had interoperable Android phones and tablets to work with, which ran on a freely-available operating system that played nicely with other devices running the system.

But with the device maker moving away from “works on Android” to “works on Samsung Android devices,” the chain of interoperability is broken. This could lead to shifts in the telecommunications industry which don’t bode well for healthcare users.

On the surface, we are only looking at relatively petty IT concerns for HIT leaders, such as seeing to it that the Samsung user gets a Samsung charging pad. Like enterprises in other industries, health leaders will adapt to this inconvenience. But the problems don’t stop there.

If telecommunications manufacturers follow Samsung’s lead, and decide to add proprietary quirks to their devices, providers may pay the price. Depending on how these newly-proprietary devices are configured, and how they must be supported, it could become much harder to dig data out of them on an ongoing basis. That’s the last thing we need right now.

Not only that, what happens if proprietary differences between Android phones and tablets make it harder for them to communicate with medical devices, a tantalizing possibility which is just beginning to present itself? While we don’t yet know how devices such as infusion pumps to interoperate with mobile devices, nor the latter two with desktops, wearables and servers, we don’t want to close off options.

Bottom line, I may be crying wolf too soon, but these developments alarm me. I’d hate to see additional walls go up between various data sources, particularly before we even know what we can do with them.

Sometimes Health Is About A Simple Connection to the Right People

Posted on June 24, 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.

This post is sponsored by Samsung Business. All thoughts and opinions are my own.

One of our biggest health care costs comes from our aging population. No doubt they’re a challenging group that often has multiple chronic conditions and is generally seen as anti-technology. While their medical conditions can be a challenge, it’s unfair to say that technology can’t have a great impact for good on even senior citizens.

In fact, one of the biggest health challenges senior citizens face is loneliness. It’s amazing the health impact being lonely can have on a person. The great thing is that technology as simple as a tablet can have a dramatic impact for good on senior citizens. Here’s a great video from Samsung and Breezie that illustrates this point:

I’ve seen a number of solutions like the Breezie tablets that have made the internet extremely accessible for senior citizens. It’s extraordinary to watch the impact for good that connecting to their friends and family on a tablet can have on a person. Plus, once their emotional state is in a better place, it’s often much easier for them to deal with their physical health challenges as well.

The amazing part is that these tablets don’t need some sort of complex health apps. They don’t need an AI generated dog to be their friend (Although, people are working on this). They don’t need dozens of healthcare sensors that are constantly monitoring their every health stat (Although, people are working on this too). All these seniors need is simple apps like Facebook where they can see pictures of their grandkids and email where they can communicate with their family and friends.

I’m sure that as things progress we’ll see more and more advanced health apps on these tablets. Many seniors have a challenge traveling to see their doctor, so you can easily see how a telemedicine app would be very convenient for both patient and doctor. Plus, sometimes you don’t even need video, but just a personal message from your trusted caregiver to help a patient feel better. All of this will come to the tablets, but we can start with something much simpler. A basic connection to the right people for that person.

I heard of one project where the patient improvement came as much from the daily call these lonely, elderly patients received as it was the actual study that was being conducted. While we could throw more people at the problem, that only scales so far. If we really want to scale this type of care to seniors, we’re going to need to utilize technology. These tablets designed for seniors are a great place to start. Then, we can build from there.

I don’t think it will be long before we see doctors prescribing tablets to patients. It’s not currently in doctors normal line of thinking, but maybe it should be.

For more content like this, follow Samsung on Insights, Twitter, LinkedIn , YouTube and SlideShare.

Practice Fusion Founder Launches Wearables Startup

Posted on May 31, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Free EMR vendor Practice Fusion has always been something of a newsmaker. Since its launch in 2005, the company has drawn both praise and controversy for its revenue-generation approach, which has included the analysis and sale of de-identified patient data and advertising to physicians.

But it’d be hard to question Practice Fusion’s success, particularly given that it found its legs during a hyper-competitive period of EMR vendor growth capped by the Meaningful Use incentive program. Over the company’s lifespan, it has grown to serve over 110 million patients, and reportedly supported more than 70 million patient visits over 2015. It also attracted over $150 million in venture and private equity funding. Will it provide a great return for investors, time will tell, but they’ve definitely left their mark on the EHR industry.

At the helm of Practice Fusion until last year was CEO and Founder Ryan Howard. Howard – whom I’ve interviewed now and again over the years — certainly doesn’t lack for confidence or creative thinking. So I was intrigued to learn that Howard has stuck his toe into the wearables market. Clearly, Howard has not wasted time since August 2015, when he was booted out as Practice Fusion CEO. And if he believes a wearables startup can make money in this rapidly-maturing niche, I’m inclined to give it a look.

Howard’s new startup, dubbed iBeat, is creating a watch which constantly monitors and analyzes users’ heart activity. The device, which transmits its data to a cloud platform, can alert emergency medical services and, using an onboard GPS, provide the wearer’s location when a user has a heart attack or their heart slows down below a certain level. Unlike competitor AliveCor, whose electrocardiogram device can detect heart rhythm abnormalities such as atrial fibrillation, it has no immediate plans to get FDA approval for its technology.

iBeat expects to sell the device for less than $200, though if users want the emergency alert service they’ll have to pay an as-yet unnamed extra monthly fee. That puts it smack in the middle of the pack with competitors like the Apple Watch. However, the startup’s focus on cardiac events is fairly unusual. Another unusual aspect to the launch is that Howard is targeting the 50- to 70-year-old Baby Boomer market. (Imagine a more-focused version of the LifeAlert “I’ve fallen and I can’t get up” service, which focuses on the 75-plus market, Howard told MobiHealthNews.)

My take on all of this is that there may very well be something here. As I wrote about previously, my own heart rhythm is being monitored by a set of devices created by Medtronic, a set-up which probably cost a few thousand dollars in addition to the surgical costs of implanting the monitoring device. While Medtronic’s technology is doubtless FDA approved, for not-so-serious cases such as my own a $200+ plus smart watch might be just the ticket.

On the other hand, I doubt that uncertified devices such as the iBeat watch will attract much support from providers, as they simply don’t trust the data. So consumers are really going to have to drive sales. And without a massive consumer marketing budget, it will be difficult to gain traction in a niche contested by Apple, Microsoft, Fitbit and many, many other competitors. Not to mention all the competitors in the “I’ve fallen and I can’t get up” category as well.

Regardless of whether iBeat survives, though, I think its strategy is smart. My guess is that more-specialized wearables (think, I don’t know, iSugar for diabetics?) have a bright future.

E-patient Update: Remote Monitoring Leaves Me Out of The Loop

Posted on May 24, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

As some readers may recall, I don’t just write about digital health deployment — I live it. To be specific, my occasional heart arrhythmia (Afib) is being tracked remotely by device implanted in my chest near my heart. My cardiac electrophysiologist implanted the Medtronic device – a “loop recorder” roughly the size of a cigarette lighter though flatter — during a cardiac ablation procedure.

The setup works like this:

  • The implanted device tracks my heart rhythm, recording any events that fit criteria programmed into it. (Side note: It’s made entirely of plastic, which means I need not fear MRIs. Neat, huh?)
  • The center also includes a bedside station which comes with a removable, mouse shaped object that I can place on my chest to record any incidents that concern me. I can also record events in real time, when I’m on the road, using a smaller device that fits on my key ring.
  • Whether I record any perceived episodes or not, the bedside station downloads whatever information is stored in the loop recorder at midnight each night, then transmits it to the cardiac electrophysiologist’s office.
  • The next day, a tech reviews the records. If any unusual events show up, the tech notifies the doctor, who reaches out to me if need be.

Now, don’t get me wrong, this is all very cool. And these devices have benefited me already, just a month into their use. For example, one evening last week I was experiencing some uncomfortable palpitations, and wondered whether I had reason for concern. So I called the cardiac electrophysiologist’s after-hours service and got a call back from the on-call physician.

When she and I spoke, her first response was to send me to my local hospital. But once I informed her that the device was tracking my heart rhythms, she accessed them and determined that I was only experiencing mild tachycardia. That was certainly a relief.

No access for patients

That being said, it bugs me that I have no direct access to this information myself. Don’t get me wrong, I understand that interacting with heart rhythm data is complicated. Certainly, I can’t do as much in response to that information as I could if the device were, say, tracking my blood glucose levels.

That being said, my feeling is that I would benefit from knowing more about how my heart is working, or failing to work appropriately in the grand scheme of things, even if I can’t interpret the raw data of the device produces. For example, it would be great if I could view a chart that showed, say, week by week when events occurred and what time they took place.

Of course, I don’t know whether having this data would have any concrete impact on my life. But that being said, it bothers me that such remote monitoring schemes don’t have their core an assumption that patients don’t need this information. I’d argue that Medtronic and its peers should be thinking of ways to loop patients in any time their data is being collected in an outpatient setting. Don’t we have an app for that, and if not, why?

Unfortunately, no matter how patients scream and yell about this, I doubt we’ll make much progress until doctors raise their voices too. So if you’re a physician reading this, I hope you’re willing to get involved since patients deserve to know what’s going on with their bodies. And if you have the means to help them know, make it happen!

When Providing a Health Service, the Infrastructure Behind the API is Equally Important

Posted on May 2, 2016 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.

In my ongoing review of application programming interfaces (APIs) as a technical solution for offering rich and flexible services in health care, I recently ran into two companies who showed as much enthusiasm for their internal technologies behind the APIs as for the APIs themselves. APIs are no longer a novelty in health services, as they were just five years ago. As the field gets crowded, maintenance and performance take on more critical roles in offering a successful business–so let’s see how Orion Health and Mana Health back up their very different offerings.

Orion Health

This is a large analytics firm that has staked a a major claim in the White House’s Precision Medicine Initiative. Orion Health’s data platform, Amadeus, addresses population health management as well as “considering how they can better tailor care for each chronically ill individual,” as put by Dave Bennett, executive vice president for Product & Strategy. “We like to say that population health is the who and precision medicine is the how.” Thus, Amadeus can harmonize a huge variety of inputs, such as how many steps a patient takes each day at home, to prevent readmissions.

Orion Health has a cloud service, a capacity for handling huge data sets such as genomes, and a selection of tools for handling such varied sources as clinical, claims, pharmacy, genetic, and consumer device or other patient-generated data. Environmental and social data are currently being added. It has more than 90 million patient records in its systems worldwide.

Patient matching links up data sets from different providers. All this data is ingested, normalized, and made accessible through APIs to authorized parties. Customers can write their own applications, visualizations, and SQL queries. Amadeus is used by the Centers for Disease Control, and many hospitals join the chorus to submit data to the CDC.

So far, Orion Health resembles some other big initiatives that major companies in the health care space are offering. I covered services from Philips in a recent article, and another site talks about GE. Bennett says that Orion Health really distinguishes itself through the computing infrastructure that drives the analytics and data access.

Many companies use conventional relational database as their canonical data store. Relational databases are 1980s-era technology, unmatched in their robustness and sophistication in querying (through the SQL language), but becoming a bottleneck for the data sizes that health analytics deals with.

Over the past decade, every industry that needs to handle enormous, streaming sets of data has turned to a variety of data stores known collectively as NoSQL. Ironically, these are often conceptually simpler than SQL databases and have roots going much farther back in computing history (such as key/value stores). But these data stores let organizations run a critical subset of queries in real time over huge data sets. In addition, analytics are carried out by newer MapReduce algorithms and in-memory services such as Spark. As an added impetus for development, these new technologies are usually free and open source software.

Amadeus itself stores data in Cassandra, one of the most mature NoSQL data stores, and uses Spark for processing. According to Bennett, “Spark enables Amadeus to future proof healthcare organizations for long term innovation. Bringing data and analytics together in the cloud allows our customers to generate deeper insights efficiently and with increased relevancy, due to the rapidity of the analytics engine and the streaming of current data in Amadeus. All this can be done at a lower cost than traditional healthcare analytics that move the data from various data warehouses that are still siloed.” Elastic Search is also used. In short, the third-party tools used within Orion Health are ordinary and commonly found. It is simply modern in the same way as computing facilities in other industries–così fan tutte.

Mana Health

This company integrates device data into EHRs and other data stores. It achieved fame when it was chosen for the New York State patient portal. According to Raj Amin, co-founder and Executive Chairman, the company won over the judges with the convenient and slick tile concept in their user interface. Each tile could be clicked to reveal a deeper level of detail in the data. The company tries to serve clinicians, patients, and data analysts alike. Clients include HIEs, health systems, medical device manufacturers, insurers, and app developers.

Like Orion Health, Mana Health is very conscious of staying on the leading edge of technology. They are mobile-friendly and architect their solutions using microservices, a popular form of modular development that attempts to maximize flexibility in coding and deploying new services. On a lark, they developed a VR engine compatible with the Oculus Rift to showcase what can creatively be built on their API. Although this Rift project has no current uses, the development effort helps them stay flexible so that they can adapt to whatever new technologies come down the pike.

Because Mana Health developed their API some eighteen months ago, they pre-dated some newer approaches and standards. They plan to offer compatibility with emerging standards such as FHIR that see industry adoption. The company recently was announced as a partner in the Commonwell Alliance, a project formed by a wide selection of major EHR vendors to pursue interoperability.

To support machine learning, Mana Health stores data in an open source database called Neo4j. This is a very unusual technology called a graph database, whose history and purposes I described two years ago.

Graphs are familiar to anyone who has seen airline maps showing the flights between cities. Graphs are also common for showing social connections, such as your friends-of-friends on Facebook. In health care, as well, graphs are very useful tools. They show relationships, but in a very different way from relational databases. Graphs are better than relational databases at tracing connections between people or other entities. For instance, a team led by health IT expert Fred Trotter used Neo4J to store and query the data in DocGraph, linking primary care physicians to the specialists to which they refer patients.

In their unique ways, Mana Health and Orion Health follow trends in the computing industry and judiciously choose tools that offer new forms of access to data, while being proven in the field. Although commenters in health IT emphasize the importance of good user interfaces, infrastructure matters too.

Randomized Controlled Trials and Longitudinal Analysis for Health Apps at Twine Health (Part 2 of 2)

Posted on February 18, 2016 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 previous section of this article described the efforts of Dr. John Moore of Twine Health to rigorously demonstrate the effectiveness of a digital health treatment platform. As Moore puts it, Twine Health sought out two of the most effective treatment programs in the country–both Harvard’s diabetes treatment and MGH’s hypertension treatment are much more effective than the standard care found around the country–and then used their most effective programs for the control group of patients. The control group used face-to-face visits, phone calls, and text messages to keep in touch with their coaches and discuss their care plans.

The CollaboRhythm treatment worked markedly better than these exemplary programs. In the diabetes trial, they achieved a 3.2% reduction in diabetic patients’ A1C levels over three months (the control group achieved 2.0%). In the hypertension trial, 100% of patients reached a controlled blood pressure of less than 140/90 and the average reduction in blood pressure was 26mmHg (the control group had an average 16mmHg reduction and fewer than one-third of the patients went down less than 140/90).

What clinical studies can and cannot ensure

I see a few limitations with these clinical studies:

  • The digital program being tested combines several different intervention, as described before: reminders, messaging, virtual interactions, reports, and so on. Experiments show that all these things work together. But one can’t help wondering: what if you took out some time-consuming interaction? Could the platform be just as successful? But testing all the options would lead to a combinatorial explosion of tests.

    It’s important that interventions by coaches started out daily but decreased over the course of the study as the patient became more familiar and comfortable with the behavior called for in the care plans. The decrease in support required from the human coach suggests that the benefits are sustainable, because the subjects are demonstrating they can do more and more for themselves.

  • Outcomes were measured over short time frames. This is a perennial problem with clinical studies, and was noted as a problem in the papers. The researchers will contact subjects in about a year to see whether the benefits found in the studies were sustained. Even one year, although a good period to watch to see whether people bounce back to old behaviors, isn’t long enough to really tell the course of chronic illness. On the other hand, so many other life events intrude over time that it’s unfair to blame one intervention for what happens after a year.

  • Despite the short time frame for outcomes, the studies took years to set up, complete, and publish. This is another property of research practice that adds to its costs and slows down the dissemination of best practices through the medical field. The time frames involved explain why the researchers’ original Media Lab app was used for studies, even though they are now running a company on a totally different platform built on the same principles.

  • These studies also harbor all the well-known questions of external validity faced by all studies on human subjects. What if the populations at these Boston hospitals are unrepresentative of other areas? What if an element of self-selection skewed the results?

Bonnie Feldman, DDS, MBA, who went from dentistry to Wall Street and then to consulting in digital health, comments, “Creating an evidence base requires a delicate balancing act, as you describe, when technology is changing rapidly. Right now, chronic disease, especially autoimmune disease is affecting more young adults than ever before. These patients are in desperate need of new tools to support their self-care efforts. Twine’s early studies validate these important advances.”

Later research at Twine Health

Dr. Moore and his colleagues took stock of the tech landscape since the development of CollaboRhythm–for instance, the iPhone and its imitators had come out in the meantime–and developed a whole new platform on the principles of CollaboRhythm. Twine Health, of which Moore is co-founder and CEO, offers a platform based on these principles to more than 1,000 patients. The company expects to expand this number ten-fold in 2016. In addition to diabetes and hypertension, Twine Health’s platform is used for a wide range of conditions, such as depression, cholesterol control, fitness, and diet.

With a large cohort of patients to draw on, Twine Health can do more of the “big data” analysis that’s popular in the health care field. They don’t sponsor randomized trials like the two studies cited early, but they can compare patients’ progress to what they were doing before using Twine Health, as well as to patients who don’t use Twine Health. Moore says that results are positive and lasting, and that costs for treatment drop one-half to two-thirds.

Clinical studies bring the best scientific methods we know to validating health care apps. They are being found among a small but growing number of app developers. We still don’t know what the relation will be between randomized trials and the longitudinal analysis currently conducted by Twine Health; both seem of vital importance and they will probably complement each other. This is the path that developers have to take if they are to make a difference in health care.

Randomized Controlled Trials and Longitudinal Analysis for Health Apps at Twine Health (Part 1 of 2)

Posted on February 17, 2016 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.

Walking into a restaurant or a bus is enough to see that any experience delivered through a mobile device is likely to have an enthusiastic uptake. In health care, the challenge is to find experiences that make a positive difference in people’s lives–and proving it.

Of course, science has a time-tested method for demonstrating the truth of a proposition: randomized tests. Reproducibility is a big problem, admittedly, and science has been shaken by the string of errors and outright frauds perpetrated in scientific journals. Still, knowledge advances bit by bit through this process, and the goal of every responsible app developer in the health care space is the blessing offered by a successful test.

Consumer apps versus clinical apps

Most of the 165,000 health apps will probably always be labeled “consumer” apps and be sold without the expense of testing. They occupy the same place in the health care field as the thousands of untested dietary supplements and stem cell injection therapies whose promise is purely anecdotal. Consumer anger over ill-considered claims have led to lawsuits against the Fitbit device manufacturer and Lumosity mental fitness app, leading to questions about the suitability of digital fitness apps for medical care plans.

The impenetrability of consumer apps to objective judgment comes through in a recent study from the Journal of Medical Internet Research (JMIR) that asked mHealth experts to review a number of apps. The authors found very little agreement about what makes a good app, thus suggesting that quality cannot be judged reliably, a theme in another recent article of mine. One might easily anticipate that subjective measures would produce wide variations in judgment. But in fact, many subjective measures produced more agreement (although not really strong agreement) than more “objective” measures such as effectiveness. If I am reading the data right, one of the measures found to be most unreliable was one of the most “objective”: whether an app has been tested for effectiveness.

Designing studies for these apps is an uncertain art. Sometimes a study may show that you don’t know what to measure or aren’t running the study long enough. These possible explanations–gentler than the obvious concern that maybe fitness devices don’t achieve their goals–swirl about the failure of the Scripps “Wired for Health” study.

The Twine Health randomized controlled trials

I won’t talk any more about consumer apps here, though–instead I’ll concentrate on apps meant for serious clinical use. What can randomized testing do for these?

Twine Health and MIT’s Media Lab took the leap into rigorous testing with two leading Boston-area partners in the health care field: a diabetes case study with the Joslin Diabetes Center and a hypertension case study with Massachusetts General Hospital. Both studies compared a digital platform for monitoring and guiding patients with pre-existing tools such as face-to-face visits and email. Both demonstrated better results through the digital platform–but certain built-in limitations of randomized studies leave open questions.

When Dr. John Moore decided to switch fields and concentrate on the user experience, he obtained a PhD at the Media Lab and helped develop an app called CollaboRhythm. He then used it for the two studies described in the papers, while founding and becoming CEO of Twine Health. CollaboRhythm is a pretty comprehensive platform, offering:

  • The ability to store a care plan and make it clear to the user through visualizations.

  • Patient self-tracking to report taking medications and resulting changes in vital signs, such as glycemic levels.

  • Visualizations showing the patient her medication adherence.

  • Reminders when to take medication and do other aspects of treatment, such as checking blood pressure.

  • Inferences about diet and exercise patterns based on reported data, shown to the patient.

  • Support from a human coach through secure text messages and virtual visits using audio, video, and shared screen control.

  • Decision support based on reported vital statistics and behaviors. For instance, when diabetic patients reported following their regimen but their glycemic levels were getting out of control, the app could suggest medication changes to the care team.

The collection of tools is not haphazard, but closely follows the modern model of digital health laid out by the head of Partners Connected Health, Joseph Kvedar, in his book The Internet of Healthy Things (which I reviewed at length). As in Kvedar’s model, the CollaboRhythm interventions rested on convenient digital technologies, put patients’ care into their own hands, and offered positive encouragement backed up by clinical staff.

As an example of the patient empowerment, the app designers deliberately chose not to send the patient an alarm if she forgets her medication. Instead, the patient is expected to learn and adopt responsibility over time by seeing the results of her actions in the visualizations. In exit interviews, some patients expressed appreciation for being asked to take responsibility for their own health.

The papers talk of situated learning, a classic education philosophy that teaches behavior in the context where the person has to practice the behavior, instead of an artificial classroom or lab setting. Technology can bring learning into the home, making it stick.

There is also some complex talk of the relative costs and time commitments between the digital interventions and the traditional ones. One important finding is that app users expressed significantly better feelings about the digital intervention. They became more conscious of their health and appreciated being able to be part of decisions such as changing insulin levels.

So how well does this treatment work? I’ll explore that tomorrow in the next section of this article, along with strengths and weaknesses of the studies.

Time For A Health Tracking Car?

Posted on December 30, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Several years ago, I attended a conference on advanced health technologies in DC. One of the speakers was Dr. Jay Sanders, president and CEO of The Global Telemedicine Group. And he had some intriguing things to say — especially given that no one had heard of a healthcare app yet and connected health was barely a vision.

One of Dr. Sanders’ recommendations was that automobile seat belts should integrate sensors that tracked your heart rhythm. After all, he noted, many of us spend hours a day behind the wheel, often under stressful conditions — so why not see how your heart is doing along the way? After all, some dangerous arrhythmias don’t show up at the moment you’re getting a checkup.

Flash forward to late 2015, and it seems Dr. Sanders’ ideas are finally being taken seriously. In fact, Ford Motor Co. and the Henry Ford Health System are co-sponsoring a contest offering $10,000 in prize money to employees creating smartphone apps linking healthcare with vehicles. While this doesn’t (necessarily) call for sensors to be embedded in seat belts, who knows what employees will propose?

To inspire potential entrants, the Connected Health Challenge sponsors have suggested a few ideas for possible designs, including in-vehicle monitoring and warnings and records access from the road. Other suggestions included appointment check-ins and technology allowing health data to be transmitted to providers. The contest kicks off on January 20th.

In some ways, this isn’t a huge surprise. After all, connected vehicles are already a very hot sector in the automotive business. According to research firm Parks Associates, there will be 41 million active Internet connections in U.S. vehicles by the end of this year.

At present, according to Parks, the connect car applications consumers are most interested in include mapping/navigation, information about vehicle performance, Bluetooth technology and remote control of vehicles using mobile phones. But that could change quickly if someone finds a way to interest the well-off users of wearables in car-based health tracking. (A possible direction for Fitbit, perhaps?)

Ordinarily, I’d have some doubts about Henry Ford Health System employees’ ability to grasp this market. But as I’ve reported elsewhere on Healthcare Scene, Henry Ford takes employee innovation very seriously.

For example, last year HFHS awarded a total of $10,000 in prizes to employees who submitted the best ideas for clinical applications of wearable technology. Not only that, the health system offers employees a 50% share of future revenues generated by their product ideas which reach the marketplace.

Now, it’s probably worth bearing in mind that the wearables industry is far more mature than the market for connected health apps in automobiles. (In fact, as far as I can tell, it’s still effectively zero.) Employees who participate in the challenge will be swinging at a far less-defined target, with less chance of seeing their ideas be adopted by the automotive industry.

Still, it’s interesting to see Ford Motor Co. and HFHS team up on this effort. I think something intriguing will come of it.

FDA Limitations Could Endanger Growth Of mHealth

Posted on December 28, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

mHealth technology has virtually unlimited potential. But until the FDA begins putting its stamp of approval on mHealth tools, many providers won’t take them seriously. And that could be a big problem for mHealth’s future.

Unfortunately, early signs seem to suggest that the FDA is in over its head when it comes to regulating mHealth. According to speakers at a recent FDA Law Institute conference, it could be years before the agency even has a solid idea of how to proceed, Bloomberg reports.

Jeffrey Shapiro, a member of the Washington, D.C. law firm of Hyman Phelps & McNamara P.C., told the conference the FDA just isn’t equipped to handle the flood of new mHealth approaches. “Experience has shown that the FDA’s almost 40-year-old regulatory framework is a bad fit for much of today’s health IT with its networked ecosystems, rapid iterative improvement, deep collaboration between providers and end-users and focus on clinical decision support rather than direct diagnosis or treatment,” he told the audience.

The FDA dismisses the notion that it’s not prepared to regulate mHealth technologies. Bakul Patel, the agency’s associate director for digital health, told Reuters that the agency is planning to fill three new senior health scientist positions focused on digital health soon. That’s an encouraging step, though given that there are more than 165,000 health apps on the market, probably an inadequate one.

Sure, few of those app developers will apply for FDA approval. And the agency only plans to demand approval for technologies that are designed to be used as an accessory to a regulated medical devices, or transform a mobile platform into a regulated medical device. mHealth devices it has already approved include Airstrip Remote Patient Monitoring, the AliveCor Heart Monitor for iPhone and McKesson Cardiology’s ECG Mobile.

On the other hand, if Shapiro is right, the FDA could become a bottleneck which could severely stunt the growth of the U.S. mHealth industry. If nothing else, mHealth developers who seek FDA approval could be faced with a particularly prolonged approval process. While vendors wait for approval, they can keep innovating, but if their proposed blockbuster product is in limbo, it won’t be easy for them to stay solvent.

Not only that, if the FDA doesn’t have the institutional experience to reasonably evaluate such technologies, the calls it makes as to what is safe and efficacious may be off base. After all, apps and remote monitoring tools don’t bear much resemblance to traditional medical devices.

In theory, upstart mHealth companies which don’t have the resources to go through the FDA approval process can just proceed with their rollout. After all, the agency’s guidelines for requiring its approval are reasonably narrow.

But in reality, it seems unlikely that providers will adopt mHealth devices and apps wholesale until they get the FDA stamp of approval.  Whether they geniunely consider non-approved devices to be too lightweight for use, or fear being sued for using questionable technology, providers seem unlikely to integrate mHealth technology into their daily practice without the agency’s green light.

Given these concerns, we’d best hope that the FDA doesn’t begin requiring its approval for EMRs. Or at the very least, we should be glad that it didn’t jump in early. Who knows where EMR infrastructure would be if vendors had had to play patty-cake with the FDA from day one?

Significant Articles in the Health IT Community in 2015

Posted on December 15, 2015 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.

Have you kept current with changes in device connectivity, Meaningful Use, analytics in healthcare, and other health IT topics during 2015? Here are some of the articles I find significant that came out over the past year.

The year kicked off with an ominous poll about Stage 2 Meaningful Use, with implications that came to a head later with the release of Stage 3 requirements. Out of 1800 physicians polled around the beginning of the year, more than half were throwing in the towel–they were not even going to try to qualify for Stage 2 payments. Negotiations over Stage 3 of Meaningful Use were intense and fierce. A January 2015 letter from medical associations to ONC asked for more certainty around testing and certification, and mentioned the need for better data exchange (which the health field likes to call interoperability) in the C-CDA, the most popular document exchange format.

A number of expert panels asked ONC to cut back on some requirements, including public health measures and patient view-download-transmit. One major industry group asked for a delay of Stage 3 till 2019, essentially tolerating a lack of communication among EHRs. The final rules, absurdly described as a simplification, backed down on nothing from patient data access to quality measure reporting. Beth Israel CIO John Halamka–who has shuttled back and forth between his Massachusetts home and Washington, DC to advise ONC on how to achieve health IT reform–took aim at Meaningful Use and several other federal initiatives.

Another harbinger of emerging issues in health IT came in January with a speech about privacy risks in connected devices by the head of the Federal Trade Commission (not an organization we hear from often in the health IT space). The FTC is concerned about the security of recent trends in what industry analysts like to call the Internet of Things, and medical devices rank high in these risks. The speech was a lead-up to a major report issued by the FTC on protecting devices in the Internet of Things. Articles in WIRED and Bloomberg described serious security flaws. In August, John Halamka wrote own warning about medical devices, which have not yet started taking security really seriously. Smart watches are just as vulnerable as other devices.

Because so much medical innovation is happening in fast-moving software, and low-budget developers are hankering for quick and cheap ways to release their applications, in February, the FDA started to chip away at its bureaucratic gamut by releasing guidelines releasing developers from FDA regulation medical apps without impacts on treatment and apps used just to transfer data or do similarly non-transformative operations. They also released a rule for unique IDs on medical devices, a long-overdue measure that helps hospitals and researchers integrate devices into monitoring systems. Without clear and unambiguous IDs, one cannot trace which safety problems are associated with which devices. Other forms of automation may also now become possible. In September, the FDA announced a public advisory committee on devices.

Another FDA decision with a potential long-range impact was allowing 23andMe to market its genetic testing to consumers.

The Department of Health and Human Services has taken on exceedingly ambitious goals during 2015. In addition to the daunting Stage 3 of Meaningful Use, they announced a substantial increase in the use of fee-for-value, although they would still leave half of providers on the old system of doling out individual payments for individual procedures. In December, National Coordinator Karen DeSalvo announced that Health Information Exchanges (which limit themselves only to a small geographic area, or sometimes one state) would be able to exchange data throughout the country within one year. Observers immediately pointed out that the state of interoperability is not ready for this transition (and they could well have added the need for better analytics as well). HHS’s five-year plan includes the use of patient-generated and non-clinical data.

The poor state of interoperability was highlighted in an article about fees charged by EHR vendors just for setting up a connection and for each data transfer.

In the perennial search for why doctors are not exchanging patient information, attention has turned to rumors of deliberate information blocking. It’s a difficult accusation to pin down. Is information blocked by health care providers or by vendors? Does charging a fee, refusing to support a particular form of information exchange, or using a unique data format constitute information blocking? On the positive side, unnecessary imaging procedures can be reduced through information exchange.

Accountable Care Organizations are also having trouble, both because they are information-poor and because the CMS version of fee-for-value is too timid, along with other financial blows and perhaps an inability to retain patients. An August article analyzed the positives and negatives in a CMS announcement. On a large scale, fee-for-value may work. But a key component of improvement in chronic conditions is behavioral health which EHRs are also unsuited for.

Pricing and consumer choice have become a major battleground in the current health insurance business. The steep rise in health insurance deductibles and copays has been justified (somewhat retroactively) by claiming that patients should have more responsibility to control health care costs. But the reality of health care shopping points in the other direction. A report card on state price transparency laws found the situation “bleak.” Another article shows that efforts to list prices are hampered by interoperability and other problems. One personal account of a billing disaster shows the state of price transparency today, and may be dangerous to read because it could trigger traumatic memories of your own interactions with health providers and insurers. Narrow and confusing insurance networks as well as fragmented delivery of services hamper doctor shopping. You may go to a doctor who your insurance plan assures you is in their network, only to be charged outrageous out-of-network costs. Tools are often out of date overly simplistic.

In regard to the quality ratings that are supposed to allow intelligent choices to patients, A study found that four hospital rating sites have very different ratings for the same hospitals. The criteria used to rate them is inconsistent. Quality measures provided by government databases are marred by incorrect data. The American Medical Association, always disturbed by public ratings of doctors for obvious reasons, recently complained of incorrect numbers from the Centers for Medicare & Medicaid Services. In July, the ProPublica site offered a search service called the Surgeon Scorecard. One article summarized the many positive and negative reactions. The New England Journal of Medicine has called ratings of surgeons unreliable.

2015 was the year of the intensely watched Department of Defense upgrade to its health care system. One long article offered an in-depth examination of DoD options and their implications for the evolution of health care. Another article promoted the advantages of open-source VistA, an argument that was not persuasive enough for the DoD. Still, openness was one of the criteria sought by the DoD.

The remote delivery of information, monitoring, and treatment (which goes by the quaint term “telemedicine”) has been the subject of much discussion. Those concerned with this development can follow the links in a summary article to see the various positions of major industry players. One advocate of patient empowerment interviewed doctors to find that, contrary to common fears, they can offer email access to patients without becoming overwhelmed. In fact, they think it leads to better outcomes. (However, it still isn’t reimbursed.)

Laws permitting reimbursement for telemedicine continued to spread among the states. But a major battle shaped up around a ruling in Texas that doctors have a pre-existing face-to-face meeting with any patient whom they want to treat remotely. The spread of telemedicine depends also on reform of state licensing laws to permit practices across state lines.

Much wailing and tears welled up over the required transition from ICD-9 to ICD-10. The AMA, with some good arguments, suggested just waiting for ICD-11. But the transition cost much less than anticipated, making ICD-10 much less of a hot button, although it may be harmful to diagnosis.

Formal studies of EHR strengths and weaknesses are rare, so I’ll mention this survey finding that EHRs aid with public health but are ungainly for the sophisticated uses required for long-term, accountable patient care. Meanwhile, half of hospitals surveyed are unhappy with their EHRs’ usability and functionality and doctors are increasingly frustrated with EHRs. Nurses complained about technologies’s time demands and the eternal lack of interoperability. A HIMSS survey turned up somewhat more postive feelings.

EHRs are also expensive enough to hurt hospital balance sheets and force them to forgo other important expenditures.

Electronic health records also took a hit from ONC’s Sentinel Events program. To err, it seems, is not only human but now computer-aided. A Sentinel Event Alert indicated that more errors in health IT products should be reported, claiming that many go unreported because patient harm was avoided. The FDA started checking self-reported problems on PatientsLikeMe for adverse drug events.

The ONC reported gains in patient ability to view, download, and transmit their health information online, but found patient portals still limited. Although one article praised patient portals by Epic, Allscripts, and NextGen, an overview of studies found that patient portals are disappointing, partly because elderly patients have trouble with them. A literature review highlighted where patient portals fall short. In contrast, giving patients full access to doctors’ notes increases compliance and reduces errors. HHS’s Office of Civil Rights released rules underlining patients’ rights to access their data.

While we’re wallowing in downers, review a study questioning the value of patient-centered medical homes.

Reuters published a warning about employee wellness programs, which are nowhere near as fair or accurate as they claim to be. They are turning into just another expression of unequal power between employer and employee, with tendencies to punish sick people.

An interesting article questioned the industry narrative about the medical device tax in the Affordable Care Act, saying that the industry is expanding robustly in the face of the tax. However, this tax is still a hot political issue.

Does anyone remember that Republican congressmen published an alternative health care reform plan to replace the ACA? An analysis finds both good and bad points in its approach to mandates, malpractice, and insurance coverage.

Early reports on use of Apple’s open ResearchKit suggested problems with selection bias and diversity.

An in-depth look at the use of devices to enhance mental activity examined where they might be useful or harmful.

A major genetic data mining effort by pharma companies and Britain’s National Health Service was announced. The FDA announced a site called precisionFDA for sharing resources related to genetic testing. A recent site invites people to upload health and fitness data to support research.

As data becomes more liquid and is collected by more entities, patient privacy suffers. An analysis of web sites turned up shocking practices in , even at supposedly reputable sites like WebMD. Lax security in health care networks was addressed in a Forbes article.

Of minor interest to health IT workers, but eagerly awaited by doctors, was Congress’s “doc fix” to Medicare’s sustainable growth rate formula. The bill did contain additional clauses that were called significant by a number of observers, including former National Coordinator Farzad Mostashari no less, for opening up new initiatives in interoperability, telehealth, patient monitoring, and especially fee-for-value.

Connected health took a step forward when CMS issued reimbursement guidelines for patient monitoring in the community.

A wonky but important dispute concerned whether self-insured employers should be required to report public health measures, because public health by definition needs to draw information from as wide a population as possible.

Data breaches always make lurid news, sometimes under surprising circumstances, and not always caused by health care providers. The 2015 security news was dominated by a massive breach at the Anthem health insurer.

Along with great fanfare in Scientific American for “precision medicine,” another Scientific American article covered its privacy risks.

A blog posting promoted early and intensive interactions with end users during app design.

A study found that HIT implementations hamper clinicians, but could not identify the reasons.

Natural language processing was praised for its potential for simplifying data entry, and to discover useful side effects and treatment issues.

CVS’s refusal to stock tobacco products was called “a major sea-change for public health” and part of a general trend of pharmacies toward whole care of the patient.

A long interview with FHIR leader Grahame Grieve described the progress of the project, and its the need for clinicians to take data exchange seriously. A quiet milestone was reached in October with a a production version from Cerner.

Given the frequent invocation of Uber (even more than the Cheesecake Factory) as a model for health IT innovation, it’s worth seeing the reasons that model is inapplicable.

A number of hot new sensors and devices were announced, including a tiny sensor from Intel, a device from Google to measure blood sugar and another for multiple vital signs, enhancements to Microsoft products, a temperature monitor for babies, a headset for detecting epilepsy, cheap cameras from New Zealand and MIT for doing retinal scans, a smart phone app for recognizing respiratory illnesses, a smart-phone connected device for detecting brain injuries and one for detecting cancer, a sleep-tracking ring, bed sensors, ultrasound-guided needle placement, a device for detecting pneumonia, and a pill that can track heartbeats.

The medical field isn’t making extensive use yet of data collection and analysis–or uses analytics for financial gain rather than patient care–the potential is demonstrated by many isolated success stories, including one from Johns Hopkins study using 25 patient measures to study sepsis and another from an Ontario hospital. In an intriguing peek at our possible future, IBM Watson has started to integrate patient data with its base of clinical research studies.

Frustrated enough with 2015? To end on an upbeat note, envision a future made bright by predictive analytics.