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An Intelligent Interface for Patient Diagnosis by HealthTap

Posted on January 9, 2017 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.

HealthTap, an organization that’s hard to categorize, really should appear in more studies of modern health care. Analysts are agog over the size of the Veterans Administration’s clientele, and over a couple other major institutions such as Kaiser Permanente–but who is looking at the 104,000 physicians and the hundreds of millions of patients from 174 countries in HealthTap’s database?

HealthTap allows patients to connect with doctors online, and additionally hosts an enormous repository of doctors’ answers to health questions. In addition to its sheer size and its unique combination of services, HealthTap is ahead of most other health care institutions in its use of data.

I talked with founder and CEO Ron Gutman about a new service, Dr. AI, that triages the patient and guides her toward a treatment plan: online resources for small problems, doctors for major problems, and even a recommendation to head off to the emergency room when that is warranted. The service builds on the patient/doctor interactions HealthTap has offered over its six years of operation, but is fully automated.

Somewhat reminiscent of IBM’s Watson, Dr. AI evaluates the patient’s symptoms and searches a database for possible diagnoses. But the Dr. AI service differs from Watson in several key aspects:

  • Whereas Watson searches a huge collection of clinical research journals, HealthTap searches its own repository of doctor/patient interactions and advice given by its participating doctors. Thus, Dr. AI is more in line with modern “big data” analytics, such as PatientsLikeMe does.

  • More importantly, HealthTap potentially knows more about the patient than Watson does, because the patient can build up a history with HealthTap.

  • And most important, Dr. AI is interactive. Instead of doing a one-time search, it employs artificial intelligence techniques to generate questions. For instance, it may ask, “Did you take an airplane flight recently?” Each question arises from the totality of what HealthTap knows about the patient and the patterns found in HealthTap’s data.

The following video shows Dr. AI in action:

A well-stocked larder of artificial intelligence techniques feed Dr. AI’s interactive triage service: machine learning, natural language processing (because the doctor advice is stored in plain text), Bayesian learning, and pattern recognition. These allow a dialog tailored to each patient that is, to my knowledge, unique in the health care field.

HealthTap continues to grow as a platform for remote diagnosis and treatment. In a world with too few clinicians, it may become standard for people outside the traditional health care system.

CVS Launches Analytics-Based Diabetes Mgmt Program For PBMs

Posted on December 29, 2016 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.

CVS Health has launched a new diabetes management program for its pharmacy benefit management customers designed to improve diabetes outcomes through advanced analytics.  The new program will be available in early 2017.

The CVS program, Transform Diabetes Care, is designed to cut pharmacy and medical costs by improving diabetics’ medication adherence, A1C levels and health behaviors.

CVS is so confident that it can improve diabetics’ self-management that it’s guaranteeing that percentage increases in spending for antidiabetic meds will remain in the single digits – and apparently that’s pretty good. Or looked another way, CVS contends that its PBM clients could save anywhere from $3,000 to $5,000 per year for each member that improves their diabetes control.

To achieve these results, CVS is using analytics tools to find specific ways enrolled members can better care for themselves. The pharmacy giant is also using its Health Engagement Engine to find opportunities for personalized counseling with diabetics. The counseling sessions, driven by this technology, will be delivered at no charge to enrolled members, either in person at a CVS pharmacy location or via telephone.

Interestingly, members will also have access to diabetes visit at CVS’s Minute Clinics – at no out-of-pocket cost. I’ve seen few occasions where CVS seems to have really milked the existence of Minute Clinics for a broader purpose, and often wondered where the long-term value was in the commodity care they deliver. But this kind of approach makes sense.

Anyway, not surprisingly the program also includes a connected health component. Diabetics who participate in the program will be offered a connected glucometer, and when they use it, the device will share their blood glucose levels with a pharmacist-led team via a “health cloud.” (It might be good if CVS shared details on this — after all, calling it a health cloud is more than a little vague – but it appears that the idea is to make decentralized patient data sharing easy.) And of course, members have access to tools like medication refill reminders, plus the ability to refill a prescription via two-way texting, via the CVS Pharmacy.

Expect to see a lot more of this approach, which makes too much sense to ignore. In fact, CVS itself plans to launch a suite of “Transform Care” programs focused on managing expensive chronic conditions. I can only assume that its competitors will follow suit.

Meanwhile, I should note that while I expect to see providers launch similar efforts, so far I haven’t seen many attempts. That may be because patient engagement technology is relatively new, and probably pretty expensive too. Still, as value-based care becomes the dominant payment model, providers will need to get better at managing chronic diseases systematically. Perhaps, as the CVS effort unfolds, it can provide useful ideas to consider.

Columbia-Affiliated Physician Group Plans Rollout Of Mobile Engagement Platform

Posted on December 15, 2016 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 massive multispecialty medical practice associated with Columbia University has decided to implement a mobile patient engagement platform, as part of a larger strategy aimed at boosting patient satisfaction and ease of access to care.

The vendor behind the technology, HealthGrid, describes its platform as offering the physicians the ability to “provide actionable care coordination, access to critical health information and to enable [patient] self-care management.” HealthGrid also says that its platform will help the group comply with the requirements of Meaningful Use and MIPS.

The group, ColumbiaDoctors, includes more than 1,700 physicians, surgeons, dentists and nurses, and offers more than 230 specialty and subspecialty areas of care. All of the group’s clinicians are affiliated with New York-Presbyterian hospital and serve as faculty at Columbia University Medical Center.

The group is investing heavily in making its services more accessible and patient-friendly. In April, for example, ColumbiaDoctors agreed to roll out the DocASAP platform, which is designed to offer patients advanced online scheduling capabilities, including features allowing patients to find and book patients via mobile and desktop channels, tools helping patients find the best provider for their needs and analytics tools for business process improvement.

HealthGrid, for its part, describes itself as a CRM platform whose goal is to “meet patients where they are.” The vendor has developed a rules engine, based on clinical protocols, that connects with patients at key points in the care process. This includes reaching out to patients regarding needed appointments, education, medications and screening, both before and after they get care. The system also allows patients to pay their co-pays via mobile channels.

Its other features include automated mobile check-in – with demographic information auto-populated from the EMR – which patients can update from their mobile phones. The platform allows patients to read, update and sign off on forms such as HIPAA documentation and health information using any device.

While I’d never heard of HealthGrid before, it sounds like it has all the right ideas in place for consumer engagement. Clearly it impressed ColumbiaDoctors, which must be spending a fair amount on its latest addition. I’m sure the group’s leaders feel that if it increases patient alignment with treatment goals and improves the condition of the population it serves, they’ll come out ahead.

But the truth is, I don’t think anyone knows yet whether health organizations can meet big population health goals by interacting more with patients or spending more time in dusty back rooms fussing over big data analytics. To be sure, if you have enough money to spend they can both reach out directly to patients and invest heavily in next-generation big data infrastructure. However, my instinct is that very few institutions can focus on both simultaneously.

Without a doubt, sophisticated health IT leaders know that it pays to take smart chances, and ColumbiaDoctors is probably wise to pick its spot rather than play catch-up. Still, it’s a big risk as well. I’ll be most eager to see whether tools like HealthGrid actually impact patients enough to be worth the expense.

E-Patient Update:  Is Technology Getting Ahead Of Medical Privacy?

Posted on December 9, 2016 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.

I don’t know about y’all, but I love, love, love interacting with Google’s AI on my smartphone. It’s beyond convenient – it seems to simply read my mind and dish out exactly the content I needed.

That could have unwelcome implications, however, when you bear in mind that Google might be recording your question. Specifically, for a few years now, Google’s AI has apparently been recording users’ conversations whenever it is triggered. While Google makes no secret of the matter, and apparently provides directions on how to erase these recordings, it doesn’t affirmatively ask for your consent either — at least not in any terribly conspicuous way — though it might have buried the request in a block of legal language.

Now, everybody has a different tolerance for risk, and mine is fairly high. So unless an entity does something to suggest to me that it’s a cybercrook, I’m not likely to lose any sleep over the information it has harvested from my conversations. In my way of looking at the world, the odds that gathering such information will harm me are low, while the odds collection will help me are much greater. But I know that others feel much differently than myself.

For these reasons, I think it’s time to stop and take a look at whether we should regulate potential medical conversations with intermediaries like Google, whether or not they have a direct stake in the healthcare world. As this example illustrates, just because they’re neither providers, payers or business associates doesn’t mean they don’t manage highly sensitive healthcare information.

In thinking this over, my first reaction is to throw my hands in the air and give up. After all, how can we possibly track or regulate the flow of medical information falls outside the bounds of HIPAA or state privacy laws? How do we decide what behavior might constitute an egregious leak of medical information, and what could be seen as a mild mistake, given that the rules around provider and associate behavior may not apply? This is certainly a challenging problem.

But the more I consider these issues, the more I am convinced that we could at least develop some guidelines for handling of medical information by non-medical third parties, including what type of consumer disclosures are required when collecting data that might include healthcare information, what steps the intermediary takes to protect the data and how to opt out of data collection.

Given how complex these issues are, it’s unlikely we would succeed at regulating them effectively the first time, or even the fourth or fifth. And realistically, I doubt we can successfully apply the same standards to non-medical entities fielding health questions as we can to providers or business associates. That being said, I think we should pay more attention to such issues. They are likely to become more important, not less, as time goes by.

Vendor Study Says Wearables Can Promote Healthy Behavior Change

Posted on November 28, 2016 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 new study backed by a company that makes an enterprise health benefits platform has concluded that wearables can encourage healthy behavior change, and also, serve as an effective tool to engage employees in their health.

The data from the study, which was sponsored by Mountain View, CA-based Jiff, comes from a two-year research project on employer-sponsored wearables. Rajiv Leventhal, who wrote about the study for Healthcare Informatics, argues that these findings challenge common employer beliefs about these type of programs, including that participation is typically limited to young and healthy employees, and that engagement with these rules can’t be sustained over time.

The data, which was drawn from 14 large employers with 240,000 employees, apparently suggests that wearable adoption and long-term engagement is possible for employees of all ages. The company reported that among the employers offered the wearables program via its enterprise health platform, 53% of employees under 40 years old participated, and 36% of employees over 50 years participated as well.

Jiff researchers also found that employee engagement had not measurably fallen for more than nine months following the program rollout, and that for one employer, levels of engagement have been progressively increasing for more than 18 months, the company reported.

According to Jiff, they have helped sustain employee engagement by employing three tactics:  Using “challenges,” time-bound immersive and social games that encourage healthy actions, “device credits,” subsidies that offset the cost of purchasing wearables and “behavioral incentives,” rewards for taking healthy actions such as walking a minimum number of steps per day.

The thing is, as interesting as these numbers might be — and they do, if nothing else, underscore the role of engaging consumers rather than waiting for them to engage with healthier behaviors on their own — the story doesn’t address one absolutely crucial issue, to wit, what concrete health impact are companies seeing from employee use of these devices.

I don’t think I’m asking for too much here when I demand some quantitative data suggesting that the setup can actually achieve measurable health results. Everything I’ve read about employee wellness initiatives to date suggests that they’ve been a giant bust, with few if any accomplishing anything measurable.

And here we have Jiff, a venture-backed hotshot company, which I’m guessing had the resources to report on results if it found any. After all, if I understand the study right, with their researchers had access to 540,000 employees for significant amount of time.  So where are the health conclusions that can be drawn from this population?

And by the way, no, I don’t accept that patient engagement (no matter how genuine) can be used as a proxy or predictive factor for health improvement. It’s a promising step in the right direction but it isn’t the real thing yet.

So, I shared the study with you because I thought you might find it interesting. I did. But I wouldn’t take it too seriously when it comes to signs of real change — either for wearables used for employee wellness initiatives. At this point both are more smoke than substance.

Are Healthcare Data Streams Rich Enough To Support AI?

Posted on November 21, 2016 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.

As I’ve noted previously, artificial intelligence and machine learning applications are playing an increasingly important role in healthcare. The two technologies are central to some intriguing new data analytics approaches, many of which are designed to predict which patients will suffer from a particular ailment (or progress in that illness), allowing doctors to intervene.

For example, at New York-based Mount Sinai Hospital, executives are kicking off a predictive analytics project designed to predict which patients might develop congestive heart failure, as well as to care for those who’ve are done so more effectively. The hospital is working with AI vendor CloudMedx to make the predictions, which will generate predictions by mining the organization’s EMR for clinical clues, as well as analyzing data from implantable medical devices, health tracking bands and smartwatches to predict the patient’s future status.

However, I recently read an article questioning whether all health IT infrastructures are capable of handling the influx of data that are part and parcel with using AI and machine learning — and it gave me pause.

Artificial intelligence, the article notes, functions on collected data, and the more data AI solution has access to, the more successful the implementation will be, contends Elizabeth O’Dowd in HIT Infrastructure. And there are some questions as to whether healthcare IT departments can integrate this data, especially Internet of Things datapoints such as wearables and other personal devices.

After all, O’Dowd notes, for the AI solution to crawl data from IoT wearables, mobile apps and other connected devices, the data must be integrated into the patient’s medical record in a format which is compatible with the organization’s EMR technology. Otherwise, the organization’s data analytics solution won’t be able to process the data, and in turn, the AI solution won’t be able to evaluate it, she writes.

Without a doubt, O’Dowd has raised some important issues here. But the real question, as I see it, is whether such data integration is really the biggest bottleneck AI and machine learning must pass through before becoming accessible to a wide range of users. For example, healthcare AI-based Lumiata offers a FHIR-compliant API to help organizations integrate such data, which is certainly relevant to this discussion.

It seems to me that giving the AI every possible scrap of data to feed on isn’t the be all and end all, and may even actually less important than the clinical rationale developers uses to back up its work. In other words, in the case of Lumiata and its competitors, it appears that creating a firm foundation for the predictions is still as much the work of clinicians as much is AI.

I guess what I’m getting to here is that while AI is doubtless more effective at predicting events as it has access to more data, using what data we have with and letting skilled clinicians manage it is still quite valuable. So let’s not back off on harvesting the promise of AI just because we don’t have all the data in hand yet.

HealthTap Announces a Comprehensive Health App Platform

Posted on November 10, 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.

For the past five years, HealthTap has been building a network of doctors and patients who exchange information and advice through information forums, messaging, video teleconferencing, and other integrated services. According to CEO Ron Gutman, all that platform building has taught them a lot about what health app developers need–knowledge that they’ve expanded by listening to hospitals and third-party app developers over the years. On Tuesday, November 1, HealthTap announced a comprehensive cloud platform pulling together all these ideas. The features in the press release read like a wish list from health app developers:

  • Text, voice, and video messaging

  • Telemedicine

  • Population health

  • Predictive modeling

  • Device input and other patient-generated data

  • Handling clinical data from electronic health records

  • Aggregated data on patient groups, such as the frequency of concepts in the population

  • The ability to view timelines on patients

  • Searchable content from the huge library of clinical advice posted to HealthTap by its roster of more than 100,000 doctors

  • Identity management, so that patients and clinicians can verify who they are and connect securely

  • Customer relationship management through messaging

Many of the APIs covering these topics are covered in the developer documentation, and others are available by application from qualified developers.

Gutman told me that three to four years of work went into this platform, and that he hopes it can reduce the multi-year developments efforts his team had to deal with to just weeks for other developers hoping to innovate in the health care field. Transparency is promoted as a key value, because the developer terms required developers to “Clearly inform users what data you collect (with their consent) as well as and how you use the data you collect or that we (HealthTap) provides to you.” Even so, some items are restricted even more, such as adherence data and health goals.

In addition to RESTful APIs, the platform has SDKs for iOS, Android, and JavasScript. CTO Sastry Nanduri says that these SDKs permit apps to incorporate some workflows, such as making virtual appointments. His philosophy is that, “We do the work and make it easy for the developers.”

HealthTap has created its own formats and APIs instead of using existing standards such as the Open mHealth defined for medical devices (described in another article). A diversity of formats may make adoption harder. But the platform does harmonize diverse data from different sources into predictable formats, so that things such as blood glucose and body weight are shown in fixed units. Nanduri points out that most of their work has not been done by other organizations in an open, API format.

In any case, central to HealthTap’s goals and efforts is the sharing of data among organizations. If Partners Healthcare or Kaiser Permanente can open their data through HealthTap’s APIs, it can all be combined with the aggregated data from millions of records HealthTap has built up over time.

Offering this platform in HealthTap’s cloud gives it many advantages. Foremost is the enormous data repository of both patients and content served up by the platform. Second, identity management is automatically provided through the secure and robust platform HealthTap has always used for signing up patients and clinicians. Clinicians are carefully validated. Theoretically, a developer could also use an independent means of authenticating patients, so that someone can use apps built on the platform without a HealthTap account.

They are also exploring a blockchain solution for tracking permissions and contracts.

The proof of this huge undertaking will be in its adoption. I’m sure HealthTap’s partners and many other organizations will play with the platform and try to bring apps to life through it, either for internal use or for widespread distribution. Nanduri says that they are ramping up carefully, reviewing applications one by one, and will talk to each of their early developers to find out their goals and offer guidance to creating a successful app. Time will tell whether HealthTap has, as Gutman says, created the platform their developers wish they had when they started the company.

A New Meaning for Connected Health at 2016 Symposium (Part 4 of 4)

Posted on November 8, 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 continued our exploration of the integration of health care into daily life. This section wraps up the article with related insights, including some thoughts about the future.

Memorable moments
I had the chance to meet with Casper de Clercq, who has set up a venture capital plan devoted to health as a General Partner at Norwest Venture Partners. He recommends that manufacturers and clinicians give patients a device that collects data while doing something else they find useful, so that they are motivated to keep wearing it. As an example, he cited the Beddit sleep tracker, which works through sensors embedded (no pun intended) in the user’s bed.

He has found that successful companies pursue gradual, incremental steps toward automated programs. It is important to start with a manual process that works (such as phoning or texting patients from the provider), then move to semi-automation and finally, if feasible, full automation. The product must also be field-tested; one cannot depend on a pilot. This advice matches what Glen Tullman, CEO of Livongo Health, said in his keynote: instead of doing a pilot, try something out in the field and change quickly if it doesn’t work.

Despite his call for gradual change, de Clercq advises that companies show an ROI within one year–otherwise, the field of health care may have evolved and the solution may be irrelevant.

He also recommends a human component in any health program. The chief barrier to success is getting the individual to go along with both the initial activation and continuing motivation. Gamification, behavioral economics, and social connections can all enhance this participation.

A dazzling keynote on videogames for health was delivered by Adam Gazzaley, who runs Neuroscience labs at the University of California at San Francisco. He pointed out that conventional treatments get feedback on patient reactions far too slowly–sometimes months after the reaction has occurred. In the field of mental health, His goal is to supplement (not replace) medications with videogames, and to provide instant feedback to game players and their treatment staff alike. Videogames not only provide a closed-loop system (meaning that feedback is instantaneous), but also engage patients by being fun and offering real-time rewards. Attention spans, anxiety, and memory are among the issues he expects games to improve. Education and wellness are also on his game plan. This is certainly one talk where I did not multitask (which is correlated with reduced performance)!

A future, hopefully bigger symposium
The Connected Health symposium has always been a production of the Boston Partners Health Care conglomerate, a part of their Connected Health division. The leader of the division, Dr. Joseph Kvedar, introduced the symposium by expressing satisfaction that so many companies and organizations are taking various steps to make connected health a reality, then labeled three areas where leadership is still required:

  • Reassuring patients that the technologies and practices work for them. Most people will be willing to adopt these practices when urged by their doctors. But their privacy must be protected. This requires low-cost solutions to the well-known security problems in EHRs and devices–the latter being part of the Internet of Things, whose vulnerability was exposed by the recent attack on Dyn and other major Internet sites.

  • Relieving the pressures on clinicians. Kvedar reported that 45 percent of providers would like to adopt connected health practices, but only 12 percent do so. One of the major concerns holding them back is the possibility of data overload, along with liability for some indicator of ill health that they miss in the flood of updates. Partners Connected Health will soon launch a provider adoption initiative that deals with their concerns.

  • Scaling. Pilot projects in connected health invest a lot of researcher time and offers a lot of incentives to develop engagement among their subjects. Because engagement is the whole goal of connected health, the pilot may succeed but prove hard to turn into a widespread practice. Another barrier to scaling is consumers’ lack of tolerance for the smallest glitches or barriers to adoption. Providers, also, insist that new practices fit their established workflows.

Dr. Kvedar announced at this symposium that they would be doing future symposia in conjunction with the Personal Connected Health Alliance (Formerly the mHealth Summit owned by HIMSS), a collaboration that makes sense. Large as Partners Health Care is, the symposium reaches much farther into the health care industry. The collaboration should bring more resources and more attendees, establishing the ideals of connected health as a national and even international movement.

A New Meaning for Connected Health at 2016 Symposium (Part 3 of 4)

Posted on November 7, 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 paused during a discussion of the accuracy and uses of devices. At a panel on patient generated data, a speaker said that one factor holding back the use of patient data was the lack of sophistication in EHRs. They must be enhanced to preserve the provenance of data: whether it came from a device or from a manual record by the patient, and whether the device was consumer-grade or a well-tested medical device. Doctors invest different levels of trust in different methods of collecting data: devices can provide more objective information than other ways of asking patients for data. A participant in the panel also pointed out that devices are more reliable in the lab than under real-world conditions. Consumers must be educated about the proper use of devices, such as whether to sit down and how to hold their arms when taking their blood pressure.

Costantini decried the continuing silos in both data sharing and health care delivery. She said only half of doctors share patient data with other doctors or caretakers. She also praised the recent collaboration between Philips and Qualcomm to make it easier for device data to get into medical records. Other organizations that have been addressing that issue for some time include Open mHealth, which I reviewed in an earlier article, and Validic.

Oozing into workflow
The biggest complaint I hear from clinicians about EHRs–aside from the time wasted in their use, which may be a symptom of the bigger problem-is that the EHRs disrupt workflow. Just as connected health must integrate with patient lives as seamlessly as possible, it should recognize how teams work and provide them with reasonable workflows. This includes not only entering existing workflows as naturally as capillary action, but helping providers adopt better ones.

The Veterans Administration is forging into this area with a new interface called the Enterprise Health Management Platform (eHMP). I mentioned it in a recent article on the future of the VA’s EHR. A data integration and display tool, eHMP is agnostic as to data source. It can be used to extend the VistA EHR (or potentially replace it) with other offerings. Although eHMP currently displays a modern dashboard format, as described in a video demo by Shane Mcnamee, the tool aims to be much more than that. It incorporates Business Process Modeling Notation (BPMN) and the WS-Human Task Specification to provide workflow support. The Activity Management Service in eHMP puts Clinical Best Practices directly into the workflow of health care providers.

Clinicians can use eHMP to determine where a consultation request goes; currently, the system is based on Red Hat’s BPMN engine. If one physician asks another to examine the patient, that task turns up on the receiving physician’s dashboard. Teams as well as individuals can be alerted to a patient need, and alerts can be marked as routine or urgent. The alerts can also be associated with time-outs, so that their importance is elevated if no one acts on them in the chosen amount of time.

eHMP is just in the beginning stages of workflow support. Developers are figuring out how to increase the sophistication of alerts, so that they offer a higher signal-to-noise ratio than most hospital CDS systems, and add intelligence to choose the best person to whom an alert should be directed. These improvements will hopefully free up time in the doctor’s session to discuss care in depth–what both patients and providers have long said they most want from the health care field.

At the Connected Health symposium, I found companies working on workflow as well. Dataiku (whose name is derived from “haiku”) has been offering data integration and analytics in several industries for the past three years. Workflows, including conditional branches and loops, can be defined through a graphical interface. Thus, a record may trigger a conditional inquiry: does a lab value exceed normal limits? if not, it is merely recorded, but if so, someone can be alerted to follow up.

Dataiku illustrates an all-in-one, comprehensive approach to analytics that remains open to extensions and integration with other systems. On the one hand, it covers the steps of receiving and processing data pretty well.

To clean incoming data (the biggest task on most data projects), their DSS system can use filters and even cluster data to find patterns. For instance, if 100 items list “Ohio” for their location, and one lists “Oiho”, the system can determine that the outlier is a probably misspelling. The system can also assign data to belonging to broad categories (string or integer) as well as more narrowly defined categories (such as social security number or ZIP code).

For analysis, Dataiku offers generic algorithms that are in wide use, such as linear regressions, and a variety of advanced machine learning (artificial intelligence) algorithms in the visual backend of the program–so the users don’t need to write a single line of code. Advanced users can also add their own algorithms coded in a variety of popular languages such as Python, R, and SQL. The software platform offers options for less technically knowledgeable users, pre-packaged solutions for various industries such as health care, security features such as audits, and artificial intelligence to propose an algorithm that works on the particular input data.

Orbita Health handles workflows between patients and providers to help with such issues as pain management and medication adherence. The company addresses ease of use by supporting voice-activated devices such as Amazon Echo, as well as some 250 other devices. Thus, a patient can send a message to a provider through a single statement to a voice-activated device or over another Internet-connected device. For workflow management, the provider can load a care plan into the system, and use Orbita’s orchestration engine (similar to the Business Process Modeling Notation mentioned earlier) to set up activities, such as sending a response to a patient’s device or comparing a measurement to the patient’s other measurements over time. Orbita’s system supports conditional actions, nests, and trees.

CitiusTech, founded in 2005, integrates data from patient devices and apps into provider’s data, allowing enterprise tools and data to be used in designing communications and behavioral management in the patient’s everyday life. The company’s Integrated Analytix platform offer more than 100,000 apps and devices from third-party developers. Industry studies have shown effective use of devices, with one study showing a 40% reduction in emergency room admissions among congestive heart failure patients through the use of scales, engaging the patients in following health protocols at home.

In a panel on behavior change and the psychology of motivation, participants pointed out that long-range change requires multiple, complex incentives. At the start, the patient may be motivated by a zeal to regain lost functioning, or even by extrinsic rewards such as lower insurance premiums. But eventually the patient needs to enfold the exercise program or other practice into his life as a natural activity. Rewards can include things like having a beer at the end of a run, or sharing daily activities with friends on social media.

In his keynote on behavioral medicine, the Co-founder & CEO of Omada Health, Sean Duffy, put up a stunningly complex chart showing the incentives, social connections, and other factors that go into the public’s adoption of health practices. At a panel called “Preserving the Human Touch in the Expanding World of Digital Therapies”, a speaker also gave the plausible advice that we tell patients what we can give back to them when collecting data.

The next section of this article offers some memorable statements at the conference, and a look toward the symposium’s future.

A New Meaning for Connected Health at 2016 Symposium (Part 2 of 4)

Posted on November 4, 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 talked about making health a routine part of everyday life, particularly where consumer devices are concerned. We’ll continue in this section with other considerations aired at the symposium.

Tullman’s principles of simplicity, cited in the previous section, can be applied to a wide range of health IT. For instance, AdhereTech pill bottles can notify the patient with a phone call or text message if she misses a dose. Another example of a technology that is easily integrated into everyday life is a thermometer built into a vaginal ring that a woman can insert and use without special activation. This device was mentioned by Costantini during her keynote. The device can alert a woman–and, if she wants, her partner–to when she is most fertile.

Super-compact devices and fancy interfaces are not always necessary for a useful intervention. In a keynote, John Dwyer, Jr., President of the Global Alzheimer’s Platform Foundation, discussed a simple survey that his organization got large numbers of people to take. They uncovered a lot of undiagnosed cases of mental decline. I imagine that the people who chose to take the survey were experiencing possible symptoms and therefore were concerned about their mental abilities. Yet they apparently had not expressed concerns to their doctors; instead they responded to the online suggestion to take a survey.

Most of us spend a large chunk of our day at work, so wellness programs there are theoretically promising. A panel on workplace-connected health solutions talked about some of the barriers:

  • Inadequate communications. Employees need to be informed regularly that a program is available, and its benefits

  • Privacy guarantees. Employees must feel assured of a firewall between their employer and the organization handling their sensitive data.

  • Clear goals. A wellness program is not just a check-off box. Employers must know what they want to achieve and design programs around these goals.

I would add that employers should examine their own environment honestly before setting up a wellness program. It’s pretty hypocritical to offer a wellness program on the one hand while subjecting employees to stress, overwork, and bad ergonomics on the other.

Telehealth is also likely to grow, and in fact, 200 bills to improve regulation of telehealth are pending in Congress. A speaker at a panel on preserving the human touch said that the Centers for Medicare & Medicaid Services are held back by uncertainty about how to measure telehealth’s value. Another speaker pointed out that we have a severe shortage of mental health professionals, and that many areas lack access to them. Telehealth may improve access.

It all comes down to the environment
Health care has to fully acknowledge the role of environmental factors in creating sickness. These include the marketing of fatty and sugary foods, the trapping of poor and minority people in areas with air and water pollution, the barriers to getting health care (sick leave, geography, insurance gaps, ignorance of gender issues, and so forth), the government subsidization of gambling, and much more. Similar issues came up during a keynote by David Torchiana, President & CEO and Partners HealthCare.

In her keynote, Jo Ann Jenkins, the CEO of AARP, quoted Atul Gawande as saying that we have medicalized aging and are failing to support the elderly. We have to see them as functioning individuals and help to support their health instead of focusing on when things go wrong. This includes focusing on prevention and ensuring that they have access to professional health care while they are still well. It also means restructuring our living spaces and lifestyles so the elderly can remain safely in their homes, get regular exercise, and eat well.

These problems call for a massive legislative and regulatory effort. But as a participant said on the panel of disruptive women in health care, plenty of money goes into promoting the interests of large hospitals, insurers, and device manufacturers, but nobody knows how to actually lobby for health care. Look at the barriers reached by Michelle Obama’s Let’s Move campaign, which fell short of ambitious goals in improving American’s nutrition.

Grounding devices on a firm foundation
A repeated theme at this symposium was making data collection by patients easier–so easy in fact that they can just launch data collection and not think about it. To be sure, some people are comfortable with health technology: according to Costantini, 60 percent of US smartphone users manage their health in some way through those devices. Nevertheless, if people have to consciously choose when to send data–even a click of a button–many will drop out of the program.

At a break-out session during the 2015 Health Datapalooza, I heard prospective device makers express anxiety over the gargantuan task of getting their products accepted by the industry. The gold standard for health care adoption, of course, is FDA approval based on rigorous clinical trials. One participant in the Datapalooza workshop assured the others that he had gotten his device through the FDA process, and that they could to.

Attitudes seem to have shifted over the past year, and many more manufacturers are treating FDA approval as a natural step in their development process, keeping their eyes on the prize of clinical adoption. Keith Carlton, CEO of HUINNO, in a panel on wearables, said that accuracy is critical to stand out in the marketplace and to counter the confusion caused by manufacturers that substitute hype for good performance.

Clinical trials for devices don’t have to be the billion-dollar, drawn-out ordeals suffered by pharma companies. Devices are rarely responsible for side effects (except for implantables) and therefore can be approved after a few months of testing.

A representative of BewellConnect told me that their road to approval took 9-12 months, and involved comparing the results of their devices to those of robust medical devices that had been previously approved. Typical BewellConnect devices include blood pressure cuffs and an infrared thermometer that quickly shows the patient’s temperature after being held near his temple. This thermometer has been used around the world in situations where it’s important to avoid contact with patients, such as in Ebola-plagued regions.

What’s new over the past three years is Bluetooth-enabled devices that can transmit their results over the network. BewellConnect includes this networking capability in 17 current devices. The company tries to provide a supremely easy path for the patient to transmit the device over a phone app to the cloud. The patient can register multiple family members on the app, and is prompted twice to indicate who was using the device so as to prevent errors. BewellConnect is working on an alert system for providers, a simple use case for data collection.

Many products from BewellConnect are in widespread use in France, where the company is based, and they have launched a major entry into the US market. I asked BewellConnect’s CEO, Olivier Hua, whether the US market presents greater problems than France. He said that the two markets are more similar than we think.

Health care in the US has historically been fragmented, whereas in France it was unified under government control. But the Affordable Care Act in the US has brought more regulation to the market here, whereas private health care providers (combining insurance and treatment) have been growing in France. As of January 1 of this year, France has required all employers to include a private option in their health care offerings. For the first time, French individuals are being hit with the copays and deductibles familiar to Americans, and are weighing how often to go to the doctor. Although the US market is still more diverse, and burdened by continuing fee-for-service plans, it is comparable to the French market for a vendor such as BewellConnect.

The next section of this article will continue with a discussion of barriers in the use of patient data, and other insights from the Connected Health symposium.