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Shimmer Addresses Interoperability Headaches in Fitness and Medical Devices

Posted on October 19, 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.

The promise of device data pervades the health care field. It’s intrinsic to patient-centered medical homes, it beckons clinicians who are enamored with hopes for patient engagement, and it causes data analysts in health care to salivate. This promise also drives the data aggregation services offered by Validic and just recently, the Shimmer integration tool from Open mHealth. But according to David Haddad, Executive Director and Co-Founder of Open mHealth, devices resist attempts to yield up their data to programmers and automated tools.

Every device manufacturer has its own idiosyncratic way of handling data, focused on the particular uses for its own device. According to Haddad, for instance, different manufacturers provide completely different representations for the same data, leave out information like time zones and units, and can provide information as granular as once per second or as vague as once per day.. Even something as basic as secure connectivity is unstandardized. Although most vendors use the OAuth protocol that is widespread on the Web, many alter it in arbitrary ways. This puts barriers in the way of connecting to their APIs.

Validic and Shimmer have to overcome these hurdles one by one, vendor by vendor. The situation is just like the burdens facing applications that work with electronic health records. Haddad reports that the cacophony of standards among device vendors seems to come from lack of attention to the API side of their product, not deliberate obstructionism. With all the things device manufacturers have to worry about–the weight, feel, and attractiveness of the object itself, deals with payers and retailers offering the product, user interface issues, etc.–the API always seems to be an afterthought. (Apple may be an exception.)

So when Shimmer contacts the tool makers at these vendors, most respond and take suggestions in a positive manner. But they may have just one or two programmers working on the API, so progress is slow. It comes down to the old problem in health care: even with government emphasis on data sharing, there is still no strong advocate for interoperability in the field.

Why did Open mHealth take on this snake’s nest and develop Shimmer? Haddad says they figured that the advantages of open source–low cost of adoption and the ease of adding extensions–will open up new possibilities for app developers, clinical settings, and researchers. Most sites are unsure what to do with device data and are just starting to experiment with it. Being able to develop a prototype they can throw away later will foster innovation. Open mHealth has produced a detailed cost analysis in an appeal to researchers and clinicians to give Shimmer a try.

Shimmer, like the rest of the Open mHealth tools, rests on their own schemas for health data. The schemas in themselves can’t revolutionize health care. Every programmer maintains a healthy cynicism about schemas, harking back to xkcd’s cartoon about “one universal standard that covers everyone’s use cases.” But this schema took a broader view than most programs in health care, based on design principles that try to balance simplicity against usefulness and specificity. Of course, every attempt to maintain a balance comes up against complaints the the choices were too complex for some users, too simple for others. The true effects of Open mHealth appear as it is put to use–and that’s where open source tools and community efforts really can make a difference in health care. The schemas are showing value through their community adoption: they are already used by many sites, including some major commercial users, prestigious research sites, and start-ups.

A Pulse app translates between HL7 and the Open mHealth schema. This brings Open mHealth tools within easy reach of EHR vendors trying to support extensions, or users of the EHRs who consume their HL7-formatted data.

The Granola library translates between Apple’s HealthKit and JSON. Built on this library, the hipbone app takes data from an iPhone and puts it in JSON format into a Dropbox file. This makes it easier for researchers to play with HealthKit data.

In short, the walls separating medicine must be beaten down app by app, project by project. As researchers and clinicians release open source tools that tie different systems together, a bridge between products will emerge. Haddad hopes that more widespread adoption of the Open mHealth schema and Shimmer will increase pressure on device vendors to produce standardized data accessible to all.

Wearables Data May Prevent Health Plan Denials

Posted on August 27, 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.

This story begins, as many do, with a real-world experience. Our health plan just refused to pay for a sleep study for my husband, who suffers from severe sleep apnea, despite his being quite symptomatic. We’re following up with the Virginia Department of Insurance and fully expect to win the day, though we remain baffled as to how they could make such a decision. While beginning the complaint process, a thought occurred to me.

What if wearables were able to detect wakefulness and sleepiness, and my husband was being tracked 24 hours a day?  If so, assuming he was wearing one, wouldn’t it be harder for a health plan to deny him the test he needed? After all, it wouldn’t be the word of one doctor versus the word of another, it would be a raft of data plus his sleep doctor’s opinion going up against the health plan’s physician reviewer.

Now, I realize this is a big leap in several ways.

For one thing, today doctors are very skeptical about the value generated by patient-controlled smartphone apps and wearables. According to a recent survey by market research firm MedPanel, in fact, only 15% of doctors surveyed see wearables of health apps as tools patients can use to get better. Until more physicians get on board, it seems unlikely that device makers will take this market seriously and nudge it into full clinical respectability.

Also, data generated by apps and wearables is seldom organized in a form that can be accessed easily by clinicians, much less uploaded to EMRs or shared with health insurers. Tools like Apple HealthKit, which can move such data into EMRs, should address this issue over time, but at present a lack of wearable/app data interoperability is a major stumbling block to leveraging that data.

And then there’s the tech issues. In the world I’m envisioning, wearables and health apps would merge with remote monitoring technologies, with the data they generate becoming as important to doctors as it is to patients. But neither smartphone apps nor wearables are equipped for this task as things stand.

And finally, even if you have what passes for proof, sometimes health plans don’t care how right you are. (That, of course, is a story for another day!)

Ultimately, though, new data generates new ways of doing business. I believe that when doctors fully adapt to using wearable and app data in clinical practice, it will change the dynamics of their relationship with health plans. While sleep tracking may not be available in the near future, other types of sophisticated sensor-based monitoring are just about to emerge, and their impact could be explosive.

True, there’s no guarantee that health insurers will change their ways. But my guess is that if doctors have more data to back up their requests, health plans won’t be able to tune it out completely, even if their tactics issuing denials aren’t transformed. Moreover, as wearables and apps get FDA approval, they’ll have an even harder time ignoring the data they generate.

With any luck, a greater use of up-to-the-minute patient monitoring data will benefit every stakeholder in the healthcare system, including insurers. After all, not to be cliched about it, but knowledge is power. I choose to believe that if wearables and apps data are put into play, that power will be put to good use.

Cracking Open the Shell on the Personal Health Record

Posted on November 5, 2014 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 concept of maintaining your own health data enjoyed a brief flurry of activity a few years ago with Google Health (now defunct) and Microsoft HealthVault (still active but not popular). It has gotten a second chance with Apple HealthKit, Google Fit, and other corporate offerings explicitly tied in with the convenience of mobile devices. Microsoft itself has galvanized HealthVault with a Microsoft Health initiative similar to Apple’s HealthKit. Recently I’ve been talking to health care reformers about the business and political prospects for personal health records (PHRs).

Patient access to data was enshrined as a right back when HIPAA was passed and is still championed by the US government through Meaningful Use (whose Stage 3 may well focus on it) and other initiatives, and has been endorsed by the industry as well. But this requirement won’t be satisfied by the limited patient portals that hospitals and clinics are hanging out on the Web. Their limitations include:

  • Many provide only viewing data, not downloading or transmitting it (all of these are mandated by Meaningful Use).
  • Data maintained by providers can’t easily be combined into a holistic, comprehensive view, which is what providers need to provide good care.
  • Data on portals is usually a thin sliver of all the data in the record: perhaps prescriptions, appointments, and a few other bare facts without the rich notes maintained by clinicians.
  • You can’t correct errors in your own data through a portal.
  • Clinicians rarely accept data that you want to put in the record, whether personal observations or output from fitness devices and other technical enhancements.

All these problems could be solved by flexible and well-designed personal health records. But how does the health care field navigate the wrenching transition to giving people full control over their own data?

Dr. Adrian Gropper has investigated PHRs for years and even considered building a simple device to store and serve individual’s health data. Now he says, “I can’t recall any physician in my medical society that has ever said they wished their patient had a PHR. Nor do I, after many years on the Society for Participatory Medicine list, ever recall a patient praising the role of their PHR in their care. Today’s PHRs are clinically irrelevant.”

This is not a condemnation of PHRs, but of the environment in which vendors try to deploy them. Many health reformers feel that several aspects of this care environment must evolve for PHRs to be accepted:

  • PHR data must become appealing to doctors. This means that device manufacturers (and perhaps patients themselves) must demonstrate that the data is accurate. Doctors have to recognize value in receiving at least summaries and alerts. Many benefits can also accrue from collecting vital statistics, behavioral data, and other aspects of patients’ daily lives.
  • The doctor’s EHR must seamlessly provide data to the patient, and (we hope) seamlessly accept data from the patient–data that the doctor acts on. Currently, most manufacturers store the data on their own sites and offer access through APIs. Another programming step is required to get the data into the PHR or the doctor’s EHR.
  • Clinicians have to agree on how to mark and collect the provenance of data. “Provenance” deals with assertions such as, “this data was generated by a Fitbit on October 10, 2014” or “this diagnosis was challenged by the patient and changed on August 13, 2010.”
  • Add-on services must make the data interesting and usable to both patients and physicians. For instance, such apps can alert the patient, clinician, or family members when something seems wrong, let them visualize data taken from the PHR and EHR over time, get useful advice by comparing their data to insights from research, and track progress toward the goals they choose.

“A critical force in increasing consumer engagement in digital health is the development of compelling, easy to use tools that make it simple to collect, understand and use health information to reach the goals consumers define for themselves, whether that’s managing a chronic condition, saving money, or fitting into their ‘skinny jeans’,” writes Lygeia Ricciardi, former director of the Office of Consumer e-Health at the ONC. “In an age of ‘one click purchasing,’ it must become incredibly easy for patients to access and share their own health information digitally–if it’s too complex or time consuming, most people probably won’t do it.”

In addition to sheer inertia, a number of disincentives keep PHRs from congealing.

  • Many doctors are afraid of letting patients see clinical notes, either because the patient will ask too many questions or will be upset by the content.
  • Hospitals and clinics want control over records so that patients will return to them for future treatment.
  • Marketing firms live off of rich data lodes on our health data.
  • Other organizations with dubious goals, commercial and governmental, want to track us so they can deny us insurance or control our lives in other ways.

Wait–what about the patients themselves? Why haven’t they risen up over the past several years to demand control over their data? Well, maintaining your health data is intimidating. The data is highly detailed and full of arcane medical concepts and terminology. Most patients don’t care until they really need to–and then they’re too sick and disabled to form an effective movement for patient control.

Still, several leaders in health care believe that a viable business model can be built on PHRs. The spark of hope comes from the success of apps that make people pay for privacy, notably SnapChat and Whatsapp. Although some sloppy privacy practicies render these services imperfect, their widespread use demonstrates that people care about protecting their personal data.

Private storage can be offered both in the cloud and by personal devices, using standardized services such as Direct and Blue Button. These will start out as high-end services for people who are affluent and have particular concerns about storing their own data and choosing how it is shared. It will then become commoditized and come down in price.

What about people who can’t afford even the modest prices for cloud storage? They can turn patient data into a civil rights issue. There’s a potent argument that everyone has the right to determine who can get access to their health data, and a right to have data generated during their daily lives taken into account by doctors.

We don’t need one big central service–that’s insecure and subject to breaches. Multiple services and distributed storage reduce security risks.

We’ll see change when a substantial group of people start to refuse to fill out those convoluted forms handed to them as them enter a clinic, saying instead, “Get it from my web site before you treat me.” Before that protest begins, there’s a lot of work in store for technologists and businesses to offer patients a usable record system open to the wide range of data now available for health.