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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://radar.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.

We’re Just Getting Started with an Internet of Healthy Things (Part 3 of 3)

Posted on November 27, 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://radar.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 sections of this article described the state of health care today and some of the impressive advances described in Joseph Kvedar’s new book, The Internet of Healthy Things. Now we’ll look at the possibilities for advancing further, and what stands in the way.

Futures postponed

Later in the book, Kvedar explores the promise of analytics. On a small scale, analytics can tie the results of traditional clinical research to recommendations for individuals. For instance, if the A1C hemoglobin of a person with diabetes hits a certain level that clinical research has established as dangerous, she can be notified. We also know what heart rates are best for exercising and other useful statistics. Walgreens and CVS also use data at this level to market their products to consumers who sign up for their fitness tracking programs.
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We’re Just Getting Started with an Internet of Healthy Things (Part 2 of 3)

Posted on November 25, 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://radar.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 dire condition of health care today. So where does Kvedar’s book, The Internet of Healthy Things,fit into all this? It encapsulates all those years of learning at his Center for Connected Health, set up by the Boston-area giant Partners HealthCare and now renamed Partners Connected Health. From these insights, the book pinpoints the areas where innovators can make headway. He shows the gap between how we approach chronic health conditions now–even among the companies experimenting with mobile health and patient engagement–and the ideal for which the Partners Connected Health is striving. In reviewing his suggestions, I’ll try also to shine lights into passageways he did not explore.

Lessons from the field

Kvedar divides the evolution of connected health into three broad phases. Most companies are now in the first phase of simply reporting statistics back to patients and doctors. You can find out from a mobile app what your blood sugar is, and from your fitness bracelet how far you’ve walked during the day. This phase can have some benefits on athletes and the small set of Quantified Selfers who love data, but has absolutely no appeal for the vast mass of people who most need support.

Partners Connected Health has entered the second phase and has its own data to show the great strides it has made. In this phase, you engage the patients by connecting him to his providers, family, and friends, making him feel watched (the Sentinel Effect) and therefore extracting healthier behavior. This starts to achieve the changes we want, but is still limited in the people we reach.

The third stage is to fit the intervention directly to the lifestyle and needs of the individual, a process Kvedar calls “hyperpersonalization.” If walking your dog is an important part of your life, the system should feed you messages encouraging you to do things that improve your endurance and walking ability. If you want to fit into smaller clothing for an upcoming wedding, focus on everything that can get your waistline down.

Kvedar’s vision does not seem to be the automated-intelligence utopia laid out by Vinod Khosla and others, where patients get automated diagnoses and treatment recommendations from the “cloud” and avoid physicians for most ailments. Rather, technology for Kvedar supports a strong relationship between patient and clinician. At the same time, the technology extends the clinician’s reach–and allows her to treat many more people with greater effectiveness–by bringing the treatment plan into the patient’s everyday life, throughout the day.

The first chapter of the book lays out a fantasy scenario for an automated coach that follows the individual around and sends messages right before he reaches for a cookie or is about to stay up too late at night. Kvedar unveiled the same scenario, which was quite amusing, in his introduction to the Connected Health conference. I covered the major aspects of this hyperpersonalization–automated, contextual, motivational, empowering, and incentivizing–in another article. It has to be done very careful in order not to appear intrusive and annoying, but it offers a greater promise to change behavior than anything else we know.

I already see one difficulty with organizations aiming at this vision of health care. Kvedar talks a great deal about apps–the little agents you download from the Apple Store or Google Play. But hyperpersonalization is not an app. It’s a whole environment for dealing with personal lifestyle–aided by apps, to be sure, but requiring a deep investigation into the patients’ needs and interests. What Kvedar is really calling for is not a prize-winning app, but a reconfiguration of our health system.

In the face of such a challenge, several organizations are stepping up. Among their ranks are scattered a few traditional health care organizations (providers such as Kaiser Permanente and Kvedar’s own Partners HealthCare, insurers such as Aetna) but most come from the outside. Kvedar concentrates on the clinics and wellness programs set up by Walgreens pharmacy. Their integration of convenience and support for ongoing behavior change is much more thorough than most people realize.

Another example of an integrated strategy is provided by a single teenager whose caretakers are monitoring his diabetes remotely. The process brings the teen’s doctor and mother into the picture with technologies that include an unusual skin sensor, Apple HealthKit, and an Epic health record. The solution is not an open one.

It’s great for Walgreen’s to fix sore throats and minor cuts, and even to start offering primary care. But people with serious health needs will eventually need to interact with a traditional clinic or hospital. If these institutions still can’t accept data from the urgent health clinic (some already can), the same old inefficiencies and errors will re-emerge. And this failure to evolve with the times is a danger even though, as Dr. Kvedar repeatedly warns, it threatens the continued existence of the traditional hospitals.

The final section of this article will look at the gap between where we are now and where The Internet of Healthy Things would like us to be.

We’re Just Getting Started with an Internet of Healthy Things (Part 1 of 3)

Posted on November 24, 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://radar.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 release of Joseph Kvedar’s book The Internet of Healthy Thingscoincided with the 15th annual symposium on Connected Health, which he runs every year and which I reported on earlier. Now, more than ever, a health field in crisis needs his pointed insights into the vision widely shared by all observers: collaborative, data-rich, technology-enabled, transparent, and patient-centered.

The promise and the imminent threat

A big part of Dr. Kvedar’s observations concern cost savings and “scaling” clinicians’ efforts to allow a smaller team to treat a larger community of patients with more intensive attention. As I review this book, shock waves about costs are threatening the very foundations of the Affordable Care Act. Massive losses by insurers and providers alike have led to the abandonment of Accountable Care Organizations by many who tried them. The recent bail-out by UnitedHealth was an ominous warning, eagerly jumped on by Fox News. Although other insurers issued assurances that they stay with the basic ACA program, most are reacting to the increased burden of caring for newly signed up patients by imposing insufferably high deductibles as well as extremely narrow networks of available providers. This turns the very people who should benefit from the ACA against the system.

There is nothing surprising about this development, which I have labeled a typical scam against consumers. If you sign up very sick people for insurance and don’t actually make them better, your costs will go up. T.R. Reid averred in his book The Healing of America: A Global Quest for Better, Cheaper, and Fairer Health Care that this is the sequence all countries have to follow: first commit to universal healthcare, then institute the efficiencies that keep costs under control. So why hasn’t that happened here?

Essentially, the health care system has failed us. Hospitals have failed to adopt the basic efficiency mechanisms used in other industries and still have trouble exchanging records or offering patients access to their data. A recent study finds that only 40% of physicians shared data within their own networks, and a measly 5% share data with providers outside their networks.

This is partly because electronic health records still make data exchange difficult, particularly with the all-important behavioral health clinics that can creat lifestyle changes in patients. Robust standards were never set up, leading to poor implementations. On top of that, usability is poor.

The federal government is well aware of the problem and has been pushing the industry toward more interoperability and patient engagement for years. But as health IT leader John Halamka explains, organizations are not ready for the necessary organizational and technological changes.

Although video interviews and home monitoring are finding footholds, the health industry is still characterized by hours of reading People magazine in doctors’ waiting rooms. The good news is that patients are open to mobile health innovations–the bad news is that most doctors are not.

The next section of this article will continue with lessons learned–and applied–both by Dr. Kvedar’s organization, Partners Connected Health, and by other fresh actors in the health care space.

The Future of Health Involves Human-Agent Collectives (Part 2 of 2)

Posted on February 3, 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://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The first part of this article looked at the basic idea of devices and computer systems that can deal with loosely connected actors, human and mechanical. This part takes it further into current experiments in health care.

Devices Must Adapt to Collaborators’ Needs

To be a useful agent, a computer system must understand the context in which it is operating. Take pulse oximetry–the measurement of oxygen in the blood. It’s an easy procedure to perform, and is used in hospitals to tell whether a sick patient, such as one with lung problems, is in danger. The same technology can also be used by fitness buffs to tell whether they’re getting a good workout.

These are obviously very different goals–and the device used for pulse oximetry will also be used in different ways. In a risk monitoring situation, samples may be taken less often than during a healthy fitness workout. At the minimum, a device should be configurable so that it gives the timing and accuracy needed in a particular setting. It should also be easy to turn a device on and off if it is needed for a limited time period, such as a workout.

Diego Alonso, a researcher at MD PnP, points to analgesia (the administration of pain killers) in the hospital as an example of competing needs that must be reconciled by a supervisor, human or machine. So long as the patient is stable, the pain killer should be administered. But if a monitor notices a drop in the patient’s vital signs, the painkiller’s dose must be reduced.

A popular standard for exchanging data among devices is the Data Distribution Service (DDS). The standard is rich and complex, typical of those produced by the Object Management Group. But among its virtues are an ability to specify how often you want data from a particular device. OpenICE uses DDS, among many other systems.

In short, the frequency and accuracy of data collection should be configurable. As patterns of human behavior are better understood, devices may become even more responsive to the contexts in which they are needed.

Even before the current move to standards, Capsule Tech managed to get devices to talk to EHRs through the grueling effort of interpreting the inputs and outputs of each system and crafting protocols to make them work together.

Started in 1997, the company has recently expanded from merely sharing data to developing useful tools based on data, such as alerts and a modest amount of analytics. Some of these tools demonstrate a kind of adaptability reminiscent of a human-agent collective.

For instance, alerts are crucial in any hospital environment, but notorious for crying wolf–90% can be false. In addition to sending data to the EHR, Capsule’s SmartLinx’s Medical Device Information System sends near-real-time alarm data to its Alarm Management System. This helps hospitals manage their alarms, in line with the Joint Commission’s National Patient Safety Goals.

SmartLinx does not suppress any information, but when reporting it through the Alarm Management System to the clinician’s mobile device, includes some context to help the clinician decide whether the alert needs a response. Some context involves basics such as who, where, when, and which device was activated. Other context can consist of physiological data such as the patient’s heart rate and how long the alarm has been sounding.

Additionally, to provide actionable, timely information that aids in human decision making, Capsule has built an early warning scoring system application that uses vital sign information to calculate an immediate general health status score for patients and to identify those likely to deteriorate. The application also guides the care team through appropriate actions. This may be the beginning of an intelligent, integrated health system.

Computer Systems Must Be Sensitive to Bad Input and Failure

An unfortunate tenet of human-agent collectives is that agents can’t be trusted. The most basic example is system failure. If you don’t hear from a device, does that mean the patient is fine or that the device’s battery has run out of power? DDS offers a handshake or heartbeat, the common way for distributed computing systems to determine whether part of the system has gone bust.

Provenance is another requirement for collaborative environments. This means recording when a measurement was taken, and what person or device was responsible. There must also be ways to protect against data that arrives late or is assigned the wrong timestamp. When data is entered by humans, errors can be assumed as a matter of course, even in something as simple as spelling the name of a medication manufactured by your company.

More subtle is input from inexact devices, and worse still is the potential for malicious manipulation. I heard of instances where people who got rewards by their employers for reporting exercise put their fitness devices on their dogs. Using analytics, a health care system should be able to tell that a series of sudden 20-mile-per-hour rushes interrupted by inactivity are not a human activity.

Ethical and Technical Considerations

Lots of issues come up as simple human-computer interaction evolves into collaboration among agents. I’ve already mentioned error detection and provenance. Other issues include flexibility in computers taking or relinquishing control (agile teaming), legal responsibility, providing each agent with the right incentives, considering when to engage the user’s attention (instead of taking action behind the scenes), and offering the proper interface to do so. Connected health is a deep concept offering a lot to explore, and technologies will get better as we understand more of it.

The Future of Health Involves Human-Agent Collectives (Part 1 of 2)

Posted on February 2, 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://radar.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.

Everyone understands that isolated interventions in the doctor’s office will not solve the chronic health conditions that plague developed nations and inflate health care costs. So as the health field shyly tries on new collaborative styles–including coordinated care, patient-centered medical homes, and accountable care organizations–participants are learning that the supporting technologies must also enable collaboration in ways vastly more sophisticated than current EHRs and devices.
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Digital Health, Connected Health, Wireless Health, Mobile Health, Telehealth – You Choose

Posted on May 7, 2014 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.

Neil Versel posted a great poll asking people which term they prefer. You can vote on it below:

I usually don’t dig into the terminology and branding side of things. At the end of the day, for me it’s all about making sure that we understand each other. If you call something digital health or connected health or mobile health, they’re all the same genre of item. To be honest, I mostly ignore all of those words and want to know what the application actually does.

However, Neil brought up a good point in his post about the lack of consensus in his poll. Here’s his summary of the poll results:

In any case, these results, however unscientific they may be, are representative of the fact that it is so hard to reach consensus on anything in health IT. They also are symbolic of the silos that still exist in newer technologies.

Consensus in healthcare is really hard. I’m reminded of what someone at the Dell Healthcare Think Tank event I participated in said, “Healthcare is second only to florists when it comes to market fragmentation.” It’s like steering a ship with hundreds of rudders all pointing different directions. Certainly not an easy task and not something I see changing soon.

EMR Farce, Connected Health, and Lusty Love Affair with Magic EMR

Posted on February 24, 2013 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 is a well reasoned take from John Mandrola, MD on the challenges that EMR has with many doctors. Another entry in the EHR Physician Revolt. The tone of the article is right. Dr. Mandrola isn’t against EHR and technology in general. He’s just against them in their current form. When I say current form, I suggest that is thanks to current billing requirements and other government regulations.


This is related to the first tweet. This shouldn’t be the case.


Wouldn’t we all love an EHR that was connected? Yes, I’m using connected in the broadest terms. I’m talking about connected to patients, connected to hospitals, connected to labs, radiology, insurance companies, nurses, doctors, etc etc etc. A few of those in the list are connected, but far too many of the others aren’t.


This comment by Linda was too good not to point out. She’s right. EMR is here to stay, but the honeymoon period for EMR’s is over. Doctors are starting to ask the right questions when evaluating EHRs. This will make some EHR vendors very happy and others not as much.

EMRs Are A Transitional Technology

Posted on May 2, 2011 I Written By

Katherine Rourke 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.

OK, I’m probably going to raise some people’s blood pressure, but here it is:  Is it possible that EMRs are a transitional technology which the industry will outgrow within the next several years?

I contend that with telemedicine  expanding rapidly, connected/remote health changing the focus of care and smart phones evolving along their own path — just to name a few factors — that which we call an EMR might not be up to managing care of the future.  Given the need for corporate and medical security, EMRs are also ill-equipped to give the emerging class of e-patients the data access they demand.

Yes, you can connect telehealth sites with a health system or clinic network.  You can burn through developer time making sure  your EMR supports the latest developments in mobile health applications.  You can find ways to integrate the data generated by remote patient monitoring and make it usable. But will the final result, the application which governs all of this, be the EMR we know today?

Today’s EMR, let’s face it, is not great at connecting beyond the institution where it lives. Sure, we’re building HIEs, but there’s a reason why so many are still at an embryonic stage;  forming such networks is a damnably hard job.

So what will happen when medical interactions and care shift decisively to environments and platforms outside of a hospital or clinic?  I don’t know, but I think it will take a different type of system — focused on coordination rather than just data storage and analytics.  It will need to be wherever patients are, collect data in whatever form it’s generated and support care delivery in ways that are in their infancy today.

So, that’s my opinion and I’m sticking to it.  What about you?