Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and EHR for FREE!

Patients Favor Tracking, Sharing Health Data

Posted on February 3, 2016 I Written By

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

To date, I’d argue, clinicians have been divided as to how useful medical statistics are when they come straight from the patient. In fact, some physicians just don’t see the benefit of amateur readings. (For example, when I brought my own cardiologist three months of dutifully-logged blood pressure and pulse readings, she told me not to bother.)

Research suggests that my experience isn’t unique. One study, released mid-last year by market research firm MedPanel, found that only 15% of physicians were recommending wearables or health apps to patients as tools for growing healthier.

But a new study has found that patients side with health-tracking fans. According to a new study released by the Society for Participatory Medicine, 84% of respondents felt that sharing self-tracking stats such as blood glucose, blood pressure, heart rate and physical activity with their clinician would help them better manage their health. And 77% of respondents said that such stats were equally important to both themselves and their healthcare professional.

And growing numbers of healthcare professionals are getting on board. A separate study released last year by Research Now found that 86% of 500 medical professionals said mHealth apps gave them a clearer understanding of a patient’s medical condition, and 76% percent felt that apps were helping patients manage chronic illnesses.

Patients surveyed by the SPM, meanwhile, seemed downright enthusiastic about health trackers and mobile health:

* 76% of adults surveyed would use a clinically-accurate and easy-to-use personal monitoring device
* 57% of respondents would like to both use such a device and share the data generated with a professional
* 81% would be more likely to use a consumer health monitoring device if their healthcare professional recommended such a device

Realistically, medical pros aren’t likely to make robust use of patient-generated data unless that data can be integrated into a patient’s chart quickly and efficiently. Some brave clinicians may actually attempt to skim and mentally integrate data from a health app or wearable, but few have the time, others doubt the data’s accuracy and yet another subgroup simply finds the process too awkward to endure.

The bottom line, ultimately, seems to be that patient-generated data won’t find much favor until hospitals and medical practices roll out technologies like Apple’s HealthKit, which pull the data directly into an EMR and present it in a clinician-friendly manner. And some medical pros won’t even be satisfied with a good presentation; they’ll only take the data seriously if it was served up by an FDA-approved device.

Still, I personally love the idea of participatory medicine, and am happy to learn that health trackers and apps might help us get closer to this approach. As I see it, there’s no downside to having the patient and the clinician understand each other better.

#HIMSS16: Some Questions I Plan To Ask

Posted on February 1, 2016 I Written By

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

As most readers know, health IT’s biggest annual event is just around the corner, and the interwebz are heating up with discussions about what #HIMSS16 will bring. The show, which will take place in Las Vegas from February 29 to March 4, offers a ludicrously rich opportunity to learn about new HIT developments — and to mingle with more than 40,000 of the industry’s best and brightest (You may want to check out the session Healthcare Scene is taking part in and the New Media Meetup).

While you can learn virtually anything healthcare IT related at HIMSS, it helps to have an idea of what you want to take away from the big event. In that spirit, I’d like to offer some questions that I plan to ask, as follows:

  • How do you plan to support the shift to value-based healthcare over the next 12 months? The move to value-based payment is inevitable now, be it via ACOs or Medicare incentive programs under the Medicare Access and CHIP Reauthorization Act. But succeeding with value-based payment is no easy task. And one of the biggest challenges is building a health IT infrastructure that supports data use to manage the cost of care. So how do health systems and practices plan to meet this technical challenge, and what vendor solutions are they considering? And how do key vendors — especially those providing widely-used EMRs — expect to help?
  • What factors are you considering when you upgrade your EMR? Signs increasingly suggest that this may be the year of the forklift upgrade for many hospitals and health systems. Those that have already invested in massiveware EMRs like Cerner and Epic may be set, but others are ripping out their existing systems (notably McKesson). While in previous years the obvious blue-chip choice was Epic, it seems that some health systems are going with other big-iron vendors based on factors like usability and lower long-term cost of ownership. So, given these trends, how are health systems’ HIT buying decisions shaping up this year, and why?
  • How much progress can we realistically expect to make with leveraging population health technology over the next 12 months? I’m sure that when I travel the exhibit hall at HIMSS16, vendor banners will be peppered with references to their population health tools. In the past, when I’ve asked concrete questions about how they could actually impact population health management, vendor reps got vague quickly. Health system leaders, for their part, generally admit that PHM is still more a goal than a concrete plan.  My question: Is there likely to be any measurable progress in leveraging population health tech this year? If so, what can be done, and how will it help?
  • How much impact will mobile health have on health organizations this year? Mobile health is at a fascinating moment in its evolution. Most health systems are experimenting with rolling out their own apps, and some are working to integrate those apps with their enterprise infrastructure. But to date, it seems that few (if any) mobile health efforts have made a real impact on key areas like management of chronic conditions, wellness promotion and clinical quality improvement. Will 2016 be the year mobile health begins to deliver large-scale, tangible health results? If so, what do vendors and health leaders see as the most promising mHealth models?

Of course, these questions reflect my interests and prejudices. What are some of the questions that you hope to answer when you go to Vegas?

Patient Engagement Distracts the Health Care Field From Reform (Part 2 of 2)

Posted on January 12, 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://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 segment of this article looked at the movement for patient engagement, or the patient experience. Now I’ll highlight a true reform in the health care system.

Patients Left Out in the Cold
What activist patients and doctors have been demanding for years is not engagement or a better experience, but a central role for the patient in choosing treatment and carrying it out when they leave the doctor’s office. Patient empowerment is the key to all the things doctors profess to care about, such as preventing readmissions. It’s even more critical with chronic diseases that have a lifestyle component, such as congestive heart failure and diabetes.

Some patients come to the clinical setting endowed with more education than others, or a personality suited to pushing back and demanding rights. But some fight for years for such basics as access to their records. I was dejected to read just a few weeks ago of an attempt to improve care in Rhode Island, endorsed no less by the American College of Physicians, that boasts about giving access to everybody except the patient to health records.

The American College of Physicians is concerned about the hypothetical patient who “doesn’t know the name of the peach-colored pill that the orthopedist prescribed.” That particular patient is clearly not asking for empowerment. But millions do keep track of their medications and deserve equal knowledge about the rest of the information about their medical condition. If the peach-colored pill had been recorded in a patient health record, accessible to the patient (or a responsible care-giver) wherever she goes, all the complex Health Information Exchange infrastructure praised in the article could go by the wayside. Another article describes an emerging PHR solution.

Another recent example of the disdain for patients comes in a complaint by AHIMA about the difficulties of matching records for a single patient. Duplicate records are undeniably a serious problem (as is information mistakenly entered in a different person’s record). But instead of recognizing the obvious solution of a PHR, all they can come up with is a universal identifier (which is a privacy risk as well as a target for security attacks) and more determined efforts to match patients the old-fashioned way.

Empowered patients have control over their own information. Doctors guide them to make reasonable choices that affect their health, which includes sharing those records. Empowered patients set their own goals and timetables. A grant of power and information to patients will inevitably empower and inform the other health professionals with whom those patients interact, leading to a learning health system and a true team approach to care.

What’s the difference?
As I eventually admitted, the movement for patient engagement offers many good ideas that can contribute not only to a better experience in the health care center but to patient empowerment and better outcomes. What I complain about is the motive behind patient engagement.

Let’s take patient portals. To proponents of patient engagement, it serves a few purposes related to public relations. The portal hopefully:

  • Indulges people’s preference for fast information, endearing them to the practice

  • Keeps them more “engaged,” meaning that they’ll come back and spend more money at the health care center.

  • Delivers information in more appealing ways (such as through video, when practices use it).

  • Takes routine tasks off the shoulders of staff, freeing them to do other things that improve the patient experience.

This poverty of vision is why most portals lack useful information that patients can use to actually improve their care. Discharge instructions are usually a crumpled page. Doctor notes are hidden away, available to malicious attackers more easily than to patients. Medical codes and raw numbers appear on the portal without further elucidation.

Modern health facilities use web sites along with text messaging, old-fashioned phone calls, and other tools as part of a strategy to keep patients on their treatment plans. They may have full discharge instructions, along with instructional videos for such important tasks as changing bandages, on a patient’s personal site. The patient is encouraged to report her progress along with any setbacks, and gets quick feedback when there is a change. Many face-to-face visits can be averted, and patients who can update their caretakers without leaving home are less likely to exhaust themselves at vulnerable times. The patient’s family members can easily keep up with changes and find out what they need to do, as can other professionals working on the case.

For every element of empowerment, there is a tawdry alternative that can be offered as “engagement.” That’s the risk in the patient experience movement. Unless the health care institutions start out with the philosophy of empowerment, it’s just another distraction from the work we need to do.

Time For A Health Tracking Car?

Posted on December 30, 2015 I Written By

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

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

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

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

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

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

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

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

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

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

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

FDA Limitations Could Endanger Growth Of mHealth

Posted on December 28, 2015 I Written By

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

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

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

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

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

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

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

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

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

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

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

The New World of Health Monitoring

Posted on December 23, 2015 I Written By

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

I thought that this image was really interesting in the context of another post about the medical smart phone. Ironically, I think the image below actually only depicts a small part of the health monitoring that’s coming. I’m sure that scares the heck out of many people and excites many people. It’s a hard balance. Personally, I’m on the excited side of things. Chew on this graphic as you open your various health tracking devices this Christmas.
New Extreme Health Monitoring

PHR Interaction with Doctors, A Shakespearean Tangle, and an iPhone EHR

Posted on December 18, 2015 I Written By

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

I regularly like to do a post that highlights interesting tweets from around the EHR and Healthcare IT twittersphere. Plus, I add in a bit of my own commentary. I hope you enjoy.


We’ve all known this for a long time. Glad to see that most doctors are finally realizing it too. With that said, I think we still have a long way to go when it comes to how we interact with patients through a PHR. However, we’re finally getting comfortable with the idea.


You need this part of the link above to understand the tweet:

Is ownership of medical data or workflow a Shakespearean comedy (happy ending) or tragedy (sad ending). At this point in time, the end result is not clear nor can an ending really be predicted. However, recognizing the issues can help draw focus and hopefully influence a better outcome.

It’s a fun question to ask. I think for most people it will be a generally happy ending. We usually end up with the right thing after we’ve exhausted all of our options (to modify a similar famous quote about the US). My only caution is that there may not be an ending to this. It will likely be a battle that will rage forever with give and take that goes on at least for our lifetimes.


I found this tweet ironic since I’d just had some searches to my website looking for an iOS EHR. It might be worth linking to my previous Apple EHR post. DrChrono built its brand on the back of an iPad EHR, so this isn’t a surprise. Of course, the proof is in the pudding as they say. I’ll hold out my judgment until I can hear from the doctors who actually use their iPhone as their EHR. As for the comment in the tweet above, I’m not sure it changes everything. We’ll still hear plenty of complaints from doctors on Epic and Cerner that they can’t do their EHR on their iPhone.

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.

How Open mHealth Designed a Popular Standard (Part 3 of 3)

Posted on December 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 section of this article introduced the common schemas for mobile health designed by Open mHealth, and the second section covered the first two design principles driving their schemas. We’ll finish off the design principles in this section.

Balancing permissiveness and constraints

Here, the ideal is to get accurate measurements to the precision needed by users and researchers. But many devices are known to give fuzzy results, or results that are internally consistent but out of line with absolute measurements.

The goal adopted by Open mHealth is to firm up the things that are simple to get right and also critical to accuracy, such as units of measurement discussed earlier. They also require care in reporting the time interval that a measurement covers: day, week, month. There’s no excuse if you add up the walks recorded for the day and the sum doesn’t match the total steps that the device reports for that day.

Some participants suggested putting in checks, such as whether the BMI is wildly out of range. The problem (in terms of public health as well as technology) is that there are often outlier cases in health care, and the range of what’s a “normal” BMI can change. The concept of a maximum BMI is therefore too strict and ultimately unhelpful.

Designing for data liquidity

Provenance is the big challenge here: where does data come from, how was it collected, and what algorithm was used to manipulate it? Open mHealth expects data to go far and wide among researchers and solution providers, so the schema must keep a trail of all the things done to it from its origin.

Dr. Sim said the ecosystem is not yet ready to ensure quality. For instance, a small error introduced at each step of data collection and processing can add up to a yawning gap between the reported measure and the truth. This can make a difference not only to researchers, but to the device’s consumers. Think, for instance, of a payer basing the consumer’s insurance premium on analytics performed on data from the device over time.

Alignment with clinical data standards

Electronic health records are starting to accept medical device data. Eventually, all EHRs will need to do this so that monitoring and connected health can become mainstream. Open mHealth adopted widespread medical ontologies such as SNOMED, which may seem like an obvious choice but is not at all what the devices do. Luckily, Open mHealth’s schemas come pre-labelled with appropriate terminology codes, so device developers don’t need to get into the painful weeds of medical coding.

Modeling of Time

A seemingly simple matter, time is quite challenging. The Open mHealth schema can represent both points in time and time intervals. There are still subtleties that must be handled properly, as when a measurement for one day is reported on the next day because the device was offline. These concerns feed into provenance, discussed under “Designing for data liquidity.”

Preliminary adoption is looking good. The schema will certainly evolve, hopefully allowing for diversity while not splintering into incompatible standards. This is the same balance that FHIR must strike under much more difficult circumstances. From a distance, it appears like Open mHealth, by keeping a clear eye on the goal and a firm hand on the development process, have avoided some of the pitfalls that the FHIR team has encountered.

How Open mHealth Designed a Popular Standard (Part 2 of 3)

Posted on December 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.

The previous section of this article introduced the intensive research and consultation strategy used by Open mHealth to develop a common schema for exploiting health data by app developers, researchers, clinicians, individuals, and manufacturers of medical and fitness devices. Next we’ll go through the design principles with a look at specific choices and trade-offs.

Atomicity

Normally, one wants to break information down into chunks as small as possible. By doing this, you allow data holders to minimize the amount of data they need to send data users, and data users are free to scrutinize individual items or combine them any way they want. But some values in health need to be chunked together. When someone requests blood pressure, both the systolic and diastolic measures should be sent. The time zone should go with the time.

On the other hand, mHealth doesn’t need combinations of information that are common in medical settings. For instance, a dose may be interesting to know, but you don’t need the prescribing doctor, when the prescription was written, etc. On the other hand, some app developers have asked the prescription to include the number of refills remaining, so the app can issue reminders.

Balancing parsimony and complexity

Everybody wants all the data items they find useful, but don’t want to scroll through screenfuls of documentation for other people’s items. So how do you give a bewildering variety of consumers and researchers what they need most without overwhelming them?

An example of the process used by Open mHealth was the measurement for blood sugar. For people with Type 1 or Type 2 diabetes, the canonical measurement is fasting blood sugar first thing in the morning (the measurement can be very different at different times of the day). This helps the patients and their clinicians determine their overall blood sugar control. Measurements of blood sugar in relation to meals (e.g., two hours after lunch) or to sleep (e.g., at bedtime) is also clinically useful for both patients and clinicians.

Many of these users are curious what their blood sugar level is at other times, such as after a run. But to extend the schema this way would render it mind-boggling. And Dr. Sim says these values have far less direct clinical value for people with Type 2 diabetes, who are the majority of diabetic patients. So the schema sticks with reporting blood sugar related to meals and sleep. If users and vendors work together, they are free to extend the standard–after all, it is open source.

Another reason to avoid fine-grained options is that it leads to many values being reported inconsistently or incorrectly. This is a concern with the ICD-10 standard for diagnoses, which has been in use in europe for a long time and became a requirement for billing in the US since early October. ICD-9 is woefully outdated, but so much was dumped into ICD-10 that its implementation has left clinicians staying up nights and ignoring real opportunities for innovation. (Because ICD is aimed mostly at billing, it is not used for coding in Open mHealth schemas.)

Thanks to the Open mHealth schema, a dialog has started between users and device manufacturers about what new items to include. For instance, it could include average blood sugar over a fixed period of time, such as one month.

In the final section of this article, we’ll cover the rest of the design principles.