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#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?

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.

Using APIs at the Department of Health and Human Services to Expand Web Content

Posted on October 21, 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.

Application Programming Interfaces (APIs) appeal mostly to statisticians and researchers whose careers depend on access to data. But these programming tools are also a useful part of a Web that is becoming increasingly supple and sophisticated. I have written a series of articles about the use of APIs to share and run analytics on patient data, but today I’ll cover a cool use of an API developed by the Department of Health and Human Services for disseminating educational material.

The locus for this activity started with the wealth of information created by the Centers for Disease Control for doctors, public health workers, and the general public. Striving to help the public understand vaccinations, West Nile fever, Ebola (when that was a major public issue), and even everyday conditions such as diabetes, the CDC realized they had to make their content simple to embed in web sites for all those audiences.

The CDC also realized that it would be helpful to let outsiders quickly choose content along a number of dimensions. Not only would a particular web site be interested in a particular topic (diabetes, for instance), but they would want to filter the content to offer information to a particular audience in a particular language. One Web page might offer content aimed at doctors in English, while another might offer content for the general public in English and yet another offer content in Spanish. To allow all these distinctions, a RESTful API called from JavaScript allows each Web page to bring in just what is needed. Topics and languages are offered now, and filtering by audience will be supported soon. At some point, the API will even recognize ICD-10 codes and find any content related to those disease conditions.

We are all familiar with Web pages that embed dynamic content from other sites, such as videos from YouTube or Vimeo. Web developers embed the content by visiting the desired page, clicking on an Embed button, and copying some dense HTML to their own pages. The CDC offers several ways for visitors to syndicate content in this manner to their own web sites. If they are using a popular content management system (WordPress, Drupal, or Joomla!) they can install a plug-in that uses familiar practices to embed the content. Mobile app support is also provided. But the API developed by the CDC takes the process to a much more advanced level.

First, as already described, the API lets each page specify filters that extract content on the desired topic for the desired audience. Second, if a new video, e-card, or microsite is added to the CDC site, the API automatically picks it up when a user revisits the embedding page. Thus, without fussing with HTML, a site can integrate CDC content that’s tailored pretty precisely to its needs.

This API is also in use at the FDA–see for instance their Center for Tobacco Products–and at HHS more broadly. A community is starting to build around the code, which is open source, and soon it will be on GitHub, the most popular site for code sharing. A terse documentation page is available.

The API from Health and Human Services offers several lessons for health IT. First, communications can be improved by using the advanced features provided by the Web. (In addition to the API, the CDC tools make sophisticated use of HTML5 and iFrames to offer dynamic content in ways that fit in smoothly with the sites that choose to embed it.) Second, sites need to consider the people at the other end of the transaction in order to design tools that deliver an easy-to-use and easy-to-understand experience. And finally, releasing code as open source maximizes its value to the health care community. These trends need to be more widely adopted.

Using Healthcare Analytics to Achieve Strong Financial Performance

Posted on September 25, 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.

Everyone is talking about analytics, but I’ve been looking for the solutions that take analytics and package it nicely. This is what I hoped for when I found this whitepaper called How Healthcare Providers Can Leverage Advanced Analytics to Achieve Strong Financial Performance. This is a goal that I think most of us in healthcare IT would like to achieve. We want healthcare providers to be able to leverage analytics to improve their business.

However, this illustration from the whitepaper shows exactly why we’re not seeing the results we want from our healthcare analytics efforts:
Advanced Analytics Impact on Healthcare

That’s a complex beast if I’ve ever seen one. Most providers I talk to want the results that this chart espouses, but they want it just to happen. They want all the back end processing of data to happen inside a black box and they just want to feed in data like they’ve always done and have the results spit out to them in a format they can use.

This is the challenge of the next century of healthcare IT. EHR is just the first step in the process of getting data. Now we have the hard work of turning that data into something more useful than the paper chart provided.

The whitepaper does suggest these three steps we need to take to get value from our analytics efforts:
1. Data capture, storage, and access
2. Big data and analytics
3. Cognitive computing

If you read the whitepaper they talk more about all three of these things. However, it’s very clear that most organizations are still at step 1 with only a few starting to dabble in step 2. Some might see this as frustrating or depressing. I see it as exciting since it means that the best uses of healthcare IT are still to come. However, we’re going to need these solutions to be packaged in a really easy to use package. Otherwise no one will adopt them.

Providers Still Have Hope For HIEs

Posted on July 10, 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.

Sometimes, interoperability alone doesn’t cut it.  Increasingly, providers are expecting HIEs to go beyond linking up different organizations to delivering “actionable” data, according to a new report from NORC at the University of Chicago. The intriguing follow-on to the researchers’ conclusions is that HIEs aren’t obsolete, though their obsolescence seemed all but certain in the past.

The study, which was written up by Healthcare Informatics, conducted a series of site visits and 37 discussions with providers in Iowa, Mississippi, New Hampshire, Vermont, Utah and Wyoming. The researchers, who conducted their study in early 2014, hoped to understand how providers looked at HIEs generally and their state HIE program specifically. (The research was funded by ONC.)

One major lesson for the health IT types reading this article is that providers want data sharing models to reflect new care realities.  With Meaningful Use requirements and changes in payment models bearing down on providers, and triggering changes in how care is delivered, health IT-enabled data exchange needs to support new models of care.

According to the study, providers are intent on having HIEs deliver admission, discharge, and transfer alerts, interstate data exchange and data services that assist in coordinating care. While I don’t have comprehensive HIE services research to hand, maybe you do, readers. Are HIEs typically meeting these criteria? I doubt it, though I could be wrong.

That being said, providers seem to be willing to pay for HIE services if the vendor can meet their more stringent criteria.  While this may be tough to swallow for existing HIE technology sellers, it’s good news for the HIE model generally, as getting providers to pay for any form of community data exchange has been somewhat difficult historically.

Some of the biggest challenges in managing HIE connectivity identified by the study include getting good support from both HIE and EMR vendors, as well as a lack of internal staff qualified to manage data exchange, competing priorities and problems managing multiple funding streams. But vendors can work to overcome at least some of these problems.

As I noted previously, hospitals in particular have had many beliefs which have discouraged them from participating in HIEs. As one HIE leader quoted in my previous post noted, many have assumed that HIE connection costs would be in the same range as EMR adoption expenses; they’re been afraid that HIEs would not put strong enough data security in place to meet HIPAA obligations; and they assumed that HIE participation wasn’t that important.

Today, given the growing importance of sophisticated data management has come to the forefront, and most providers know that they need to have the big picture widespread data sharing can provide. Without the comprehensive data set cutting across the patient care environment — something few organizations are integrated enough to develop on their own — they’re unlikely to mount a successful population health management initiative or control costs sufficiently. So it’s interesting to see providers see a future for HIEs.

EMRs Should Include Telemedicine Capabilities

Posted on May 22, 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.

The volume of telemedicine visits is growing at a staggering pace, and they seem to have nowhere to go but up. In fact, a study released by Deloitte last August predicted that there would be 75 million virtual visits in 2014 and that there was room for 300 million visits a year going forward.

These telemedicine visits are generating a flood of medical data, some in familiar text formats and some in voice and video form. But since the entire encounter takes place outside of any EMR environment, huge volumes of such data are being left on the table.

Given the growing importance of telemedicine, the time has come for telemedicine providers to begin integrating virtual visit results into EMRs.  This might involve adopting specialized EMRs designed to capture video and voice, or EMR vendors might go with the times and develop ways of categorizing and integrating the full spectrum of telemedical contacts.

And as virtual visit data becomes increasingly important, providers and health plans will begin to demand that they get copies of telemedical encounter data.  It may not be clear yet how a provider or payer can effectively leverage video or voice content, which they’ve never had to do before, but if enough care is taking place in virtual environments they’ll have to figure out how to do so.

Ultimately, both enterprise and ambulatory EMRs will include technology allowing providers to search video, voice and text records from virtual consults.  These newest-gen EMRs may include software which can identify critical words spoken during a telemedical visit, such as “pain,” or “chest” which could be correlated with specific conditions.

It may be years before data gathered during virtual visits will stand on equal footing with traditional text-based EMR data and digital laboratory results.  As things stand today, telemedicine consults are used as a cheaper form of urgent care, and like an urgent care visit, the results are not usually considered a critical part of the patient’s long-term history.

But the more time patients spend getting their treatment from digital doctors on a screen, the more important the mass of medical data generated becomes. Now is the time to develop data structures and tools allowing clinicians and facilities to mine virtual visit data.  We’re entering a new era of medicine, one in which patients get better even when they can’t make it to a doctor’s office, so it’s critical that we develop the tools to learn from such encounters.

Customizable EMRs Are Long Overdue

Posted on May 5, 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.

EMRs can be customized to some extent today, but not that much. Providers can create interfaces between their EMR and other platforms, such as PACS or laboratory information systems, but you can’t really take the guts of the thing apart. The reality is that the EMR vendor’s configuration shapes how providers do business, not the other way around.

This has been the state of affairs for so long that you don’t hear too much complaining about it, but health IT execs should really be raising a ruckus. While some hospitals might prefer to have all of their EMR’s major functions locked down before it gets integrated with other systems, others would surely prefer to build out their own EMR from widgetized components on a generic platform.

Actually, a friend recently introduced me to a company which is taking just this approach. Ocean Informatics, which has built an eHealth base on the openEHR platform, offers end users the chance to build not only an EMR application, but also use clinical modules including infection control, care support, decision support and advanced care management, and a mobile platform. It also offers compatible knowledge-based management modules, including clinical modeling tools and a clinical modeling manager.

It’s telling that the New South Wales, Australia-based open source vendor sells directly to governments, including Brazil, Norway and Slovenia. True, U.S. government is obviously responsible for VistA, the VA’s universally beloved open source EMR, but the Department of Defense is currently in the process of picking between Epic and Cerner to implement its $11B EMR update. Even VistA’s backers have thrown it under the bus, in other words.

Given the long-established propensity of commercial vendors to sell a hard-welded product, it seems unlikely that they’re going to switch to a modular design anytime soon.  Epic and Cerner largely sell completely-built cars with a few expensive options. Open source offers a chassis, doors, wheels, a custom interior you can style with alligator skin if you’d like, and plenty of free options, at a price you more or less choose. But it would apparently be too sensible to expect EMR vendors to provide the flexible, affordable option.

That being said, as health systems are increasingly forced to be all things to all people — managers of population health, risk-bearing ACOs, trackers of mobile health data, providers of virtual medicine and more — they’ll be forced to throw their weight behind a more flexible architecture. Buying an EMR “out of the box” simply won’t make sense.

When commercial vendors finally concede to the inevitable and turn out modular eHealth data tools, providers will finally be in a position to handle their new roles efficiently. It’s about time Epic and Cerner vendors got it done!

Why Meaningful Use Should Balance Interoperability With More Immediate Concerns

Posted on March 12, 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.

Frustration over the stubborn blockage of patient data sharing is spreading throughout the health care field; I hear it all the time. Many reformers have told me independently that the Office of the National Coordinator should refocus their Meaningful Use incentives totally on interoperability and give up on all the other nice stuff in the current requirements. Complaints have risen so high up that the ONC is now concentrating on interoperability, while a new Congressional bill proposes taking the job out of their hands.
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Parkinson’s Disease and Health Data: A Personal Story

Posted on March 5, 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.

For 20 years, I’ve been writing about clinical data management, analytics and what has now come to be known as Big Data. Like everyone else who follows this sector, I’ve been exposed to many examples of brilliant thinking about leveraging health data, and of late, a growing number of examples where data analytics has improved care and saved lives.

I’ve also reported on dozens of notable case studies in which combing EMRs for telltale signs of disease has resulted in finding dangerous or even life-threatening conditions, including heart disease, diabetes and to a more limited degree cancer. What’s even more remarkable is that we’re likely to see the list of conditions detectable by data analytics expand greatly, particularly if we make smart use of the growing flood of mobile health data.

The problem is, we’re still extremely far from achieving universal health data interoperability, and no amount of inspiring speeches by HIT thought leaders or Congressional bellyachers will achieve this goal on their own. We need a shift comparable to cultural transformation that fueled the astonishing progress of our space efforts. (Maybe someone should claim that the Russians are ahead of us in the interoperability race — we can’t let them Russkys achieve national health data interoperability before we do, durn it!)

And none of this will help me get the last few years of my life back.

You see, while the diagnosis hasn’t been all-out finalized, it appears that I have a case of early-onset Parkinson’s Disease. I won’t bore any clinicians with a detailed description of the illness, but suffice it to say that it’s neurological in origin, potentially disabling and at present, uncurable and unstoppable.  I can probably still live a good life, particularly if I respond well to standard drugs, but all told, this thing is a major buzz kill.

I’ve had signs and symptoms that fit the diagnosis for at least a couple of years, and I dutifully reported them to the caregivers I saw. That included several encounters with doctors associated with the large, high-quality health system which serves the region where I live.  The health system providers entered the symptoms into their jet-fueled Epic EMR, but it seems that despite that, they never put two and two together.  (And as is still the norm, the data gathered at PCP visits has been in no way connected to the data living in the hospital Epic system.)

Fortunately, picking up on the earlier signs of Parkinson’s — if that is indeed my condition — wouldn’t have done anything to slow the progression of the illness. (If I had a malignant cancer, of course, this would be a different story.)  But heaven knows I would have had the clarity I needed to make good self-care choices.

For example, I could have seen physical therapists to help with growing muscle weakness, occupational therapists to help me adjust my work style, joined patient groups to gather support and volunteered for clinical trials. (I live in the DC metro, not too far from NIH, so that may well have been an option.) And most importantly, as I see it, I wouldn’t have had to live with the vague but growing dread that something was Just Not Right for years.

Because I’m not a clinician, I’ll never know how likely it is that I could have been diagnosed earlier if all my caregivers had all of my health data.  But I’m confident that interoperability and the accumulation of population data will help with earlier diagnosis and treatment of many unpleasant, disabling or even fatal conditions.

So when you go about the business  of improving data analytics tools and interoperability, mining population health databases for trends and leveraging mHealth to improve chronic disease management, I invite you to think of me — not a tragic figure by any means, but someone who’s counting on you to keep connecting the dots.  Never doubt that the human value of what you do is extraordinary, but never forget that real people are waiting in the wings for you to supply insights that can give them their life back.

Exploring the Role of Clinical Documentation: a Step Toward EHRs for Learning

Posted on January 19, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://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.

We need more clinicians weighing in on the design of the tools they use, so I was gratified to see a policy paper from the American College of Physicians about EHRs this week. In a sporadic and tentative manner, the paper recognizes that our digital tools for clinical documentation are part of a universal health care system that requires attention to workflow, care coordination, outcomes, and research needs.

The strong points of this paper include:

  • A critique of interfaces that hobble the natural thought processes of the clinician trying to record an encounter

  • A powerful call to direct record-keeping away from billing and regulatory requirements, toward better patient care

  • An endorsement of patient access to records (recommendation 6 under Clinical Documentation) and even more impressively, the incorporation of patient-generated data into clinical practice (recommendation 5 under EHR System Design)

  • A nod toward provenance (recommendation 3 under EHR System Design), which tells viewers who entered data and when, thus allowing them to judge its accuracy

Although the authors share my interests in data sharing and making data available for research, their overarching vision is of an electronic record that supports critical thinking. An EHR should permit the doctor to record ideas about a patient’s condition as naturally as they emerge from his or her head. And it should support other care-takers in making treatment decisions.

That’s a fine goal in itself, but I wish the authors also laid out a clearer vision of records within a learning health care system. Currently a popular buzzword, a learning health care system collects data from clinicians, patients, and the general population to look for evidence and correlations that can improve the delivery of health care. The learning system can determine the prevalence of health disorders in an area, pick out which people are most at risk, find out how well treatments work, etc. It is often called a “closed loop system” because it can draw on information generated from within the system to change course quickly.

So at the start of the policy paper I was disappointed to read, “The primary goal of EHR-generated documentation should be concise, history-rich notes that reflect the information gathered and are used to develop an impression, a diagnostic and/or treatment plan, and recommended follow-up.” What about supporting workflows? Facilitating continuous, integrated care such as in a patient-centered medical home? Mining data for new treatments and interventions? Interfacing with personal health and fitness devices?

Fortunately, the authors massage their initial claim by the time they reach their first policy recommendation under Clinical Documentation: “The primary purpose of clinical documentation should be to support patient care and improve clinical outcomes through enhanced communication.” The primary purpose gets even better later on: “As value-based care and accountable care models grow, the primary purpose of the EHR should remain the facilitation of seamless patient care to improve outcomes while contributing to data collection that supports necessary analyses.”

One benefit of reading this paper is its perspective on how medical records evolved to their current state. It notes a swelling over the decades in the length of notes and the time spent on them, “the increased documentation arguably not improving patient care.” Furthermore, it details how the demands of billing drove modern documentation, blaming this foremost on CMS’s “issuance of the evaluation and management (E&M) guidelines in 1995 and 1997.” I suspect that private insurers are just as culpable. In any case, the distortion of diagnosis in the pursuit of payments hasn’t worked well for either goal: 40% of diagnoses are wrongly coded.

The pressures of defensive medicine also reveal the excessively narrow view of the EHR currently as an archive rather than a resource.

The article calls for each discipline to set standards for its own documentation. I think this could help doctors use fields consistently in structured documentation. But although the authors endorse the use of macros, templates, and (with care) copy/forward, they are distinctly unfriendly toward structured data. Their distemper stems from the tendency of structured interfaces to disrupt the doctor’s thinking–the presevervation of which, remember, is their main concern–and to make him jump around from field to field in an unnatural way.

Yet the authors recognize that structured data is needed “for measurement of quality, public health reporting, research, and regulatory compliance” and state in their conclusion: “Vendors need to improve the ability of systems to capture and manage structured data.” We need structured data for our learning health care system, and we can’t wait for natural language processing to evolve to the point where it can reliably extract the necessary elements of a document. But a more generous vision could resolve the dilemma.

Certainly, current systems don’t handle structured data well. For instance, the article restates the well-known problem of redundant data entry, particularly to meet regulatory requirements, a problem that could be solved with minimally intelligent EHR processing engines. The interactive features available on modern mobile devices and web interfaces could also let the clinician enter data in any manner suited to her thinking, imposing structure as she goes, instead of forcing her into a rigid order of data entry chosen by the programmer.

Already, Modernizing Medicine claims to make structured data as easy to enter as writing in a paper chart. As I cover in another article, they are not yet a general solution, but work only with a few fields that deal with a distinct set of health conditions. The tool is a model for what we can do in the future, though.

The common problem of physicians copying observations from a previous encounter and pasting them into the current encounter is a trivial technical failure. On the web, when I want to cite material from a previous article, I don’t copy it and paste it in. I insert a hyperlink, I did in the previous paragraph. EHRs could similarly make reporting simple and accurate by linking to previous encounters where relevant.

The ACP recommendations are sensible and well-informed. If implemented by practitioners and EHR developers who keep the larger goals of health care in mind, they can help jump over the chasm between where EHRs and documentation are today, and where we need them to be.

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