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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.

Full Disclosure: Modernizing Medicine is an advertiser on this site.

By Supporting Digital Health, EMRs To Create Collective Savings of $78B Over Next Five Years

Posted on December 1, 2014 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.

Here’s the news EMR proponents have been insisting would emerge someday, justifying their long-suffering faith in the value of such systems.  A new study from Juniper Research has concluded that EMRs will save $78 billion cumulatively across the globe over the next five years, largely by connecting digital health technologies together.

While I’m tempted to get cynical about this — my poor heart has been broken by so many unsupportable or conflicting claims regarding EMR savings over the years — I think the study definitely bears examination. If digital health technologies like smart watches, fitness trackers, sensor-laden clothing, smart mobile health apps, remote monitoring and telemedicine share a common backbone that serves clinicians, the study’s conclusions look reasonable on first glance.

According to Juniper, the growth of ACOs is pushing providers to think on a population health level and that, in turn, is propelling them to adopt digital health tech.  And it’s not just top healthcare leaders that are getting excited about digital health. Juniper found that over the last 18 months, healthcare workers have become significantly more engaged in digital healthcare.

But how will providers come to grips with the floods of data generated by these emerging technologies? Why, EMRs will do the job. “Advanced EHRs will provide the ‘glue’ to bring together the devices, stakeholders and medical records in the future connected healthcare environment,” according to Juniper report author Anthony Cox.

But it’s important to note that at present, EMRs aren’t likely to have the capacity sort out the growing flood of connected health data on their own. Instead, it appears that healthcare providers will have to rely on data intermediary platforms like Apple’s HealthKit, Samsung’s SAMI (Samsung Architecture for Multimodal Interactions) and Microsoft Health. In reality, it’s platforms like these, not EMRs, that are truly serving as the glue for far-flung digital health data.

I guess what I’m trying to say is that on reflection, my cynical take on the study is somewhat justified. While they’ll play a very important role, I believe that it’s disingenuous to suggest that EMRs themselves will create huge healthcare savings.

Sure, EMRs are ultimately where the buck stops, and unless digital health data can be consumed by doctors at an EMR console, they’re unlikely to use it. But even though using EMRs as the backbone for digital health collection and population health management sounds peachy, the truth is that EMR vendors are nowhere near ready to offer robust support for these efforts.

Yes, I believe that the combination of EMRs and digital health data will prove to be very powerful over time. And I also believe that platforms like HealthKit will help us get there. I even believe that the huge savings projected by Juniper is possible. I just think getting there will be a lot more awkward than the study makes it sound.

Ebola Lapse in Dallas Offers Few Lessons, Except About Our Over-reliance on Technology

Posted on October 8, 2014 I Written By

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

Of all the EHR problems encountered daily across the country, the only one to hit the major news outlets was a non-story about a missed Ebola diagnosis in Dallas, Texas. Before being retracted, the hospital’s claim of an Epic failure launched a slew of commentary in the health IT field. These swirled through my head last night as I tried to find a lesson in the incident.

The facts seem to be as follows. A 42-year-old man named Thomas Eric Duncan arrived from Liberia and checked in to the emergency room at Texas Health Presbyterian Hospital Dallas complaining of symptoms consistent with an Ebola diagnosis. He told the admitting nurse he had come from Liberia, and the nurse entered the data into the Epic EHR.

The purpose of recording the patient’s travel history, however, seemed to be simply to determine the need for immunizations, so the EHR kept it within a nurse’s section of the data (which the hospital called a “workflow”) and did not display it to the doctor. The doctor sent Duncan home, where he came into contact with about 100 people who were potentially infected. His symptoms worsened and he returned to the hospital two days later, where he was finally diagnosed correctly and admitted.

Late night musing #1: If Texas Health Presbyterian Hospital Dallas can’t diagnose a case of Ebola, why do they think they can treat one? The hospital has won numerous awards, including one for patient safety–I guess you’re safe once you’re admitted.

Meanwhile, the city of Dallas waited several extra days to clean up infected sheets and other belongings from the Duncan home. In Africa, such detritis are recognized as a major source of new Ebola infections.

Late night musing #2: Does this reflect the competence of public health officials in this country? Maybe we should turn the job over to the Secret Service.

It’s really a shame that the national press jumped on the hospital’s announcement that the EHR was the source of the problem. Commenters criticized the hospital right away, asking why the nurse didn’t simply tell the doctor, and why the doctor didn’t ask on his own.

Finally, the hospital backed off from blaming Epic, thus making the hospital look even stupider and more guilty than it already appeared. Nevertheless, EHRs at some hospitals may be designed to flag warning signals.

Clearly, there are many layers to this health care failure. I don’t blame the nurse, or even the doctor. ERs are always busy, and the nurse might never have known who would see the patient or even be in the ER when the doctor finally saw him.

But I do find a small lesson in the brief appearance of the EHR as a pivotal character in the story. The nurse thought he or she was doing their job just by entering the data into the EHR, and the doctor thought he was doing his job by reading it. The EHR had loomed as a magical solution to health care workflow–in the minds of hospital administrators, if not the ER staff.

Maybe if the nurse knew that the travel history was for the purpose of immunizations, he or she would not have relied on the EHR to use that information for diagnosis. Besides showing the need for training, some of my colleagues suggest that this problem calls for FDA regulation of EHR interfaces. They also suggest that systems use good user interface design to highlight important information (which would require a definition of what’s “important”) or at least allow searches for critical elements of the record.

Late night musing #3: Behind this also lies the mindlessness of much data collected by EHRs. I’m sure the nurse knew whether the unfortunate Mr. Duncan was a smoker and whether he suffered from depression, because regulations require these things to be recorded. Travel history became just another one of these automatic requirements to be tossed into the EHR and forgotten.

My story also concerns the musings of other health IT commentators, who suggested that EHRs be better integrated into “workflows”–as if every clinician follows a mechanical path of treatment and the EHR can figure out what it is.

Another thoughtful posting calls for integrating infectious diseaess into clinical decision support. But as my colleague Sandra Raup (R.D., J.D., M.P.H.) points out, CDS depends on a long history of clinical data collection. One can’t instantly add a new disease.

It might have been useful for some international health organization to realize, when the Ebola outbreak began to spread, that it would eventually break out of central Africa, and then to provide an app to hospitals around the world for checking symptoms and travel history. There is certainly a creative role for health IT to play.

I think the messiness of the Texas Health Presbyterian Hospital Dallas story shows why EHR failures, numerous as they are, don’t get reported in the press. There are just too many complicating factors. The EHR is partly configured by the clinic’s staff, who thereby become responsible for some of its decisions. The EHR failure usually comes when the staff is under stress, when they have communication problems, when the patient’s condition is rare. Ascribing blame becomes a tangled mess; one must start designing systems with multiple, redundant points to catch failures that can fall through the cracks.

So one level, this is just another sad story of humanity’s tendency to trust too much in its technology, a story that ranges from the flight of Icarus to the sail of the Titanic and the failure of the Fukushima Daiichi nuclear power plant. On other, it’s a familiar story of a systemic problem leading to what’s sometimes called a “normal failure.” Not much new to learn, but lots of work to do. Clinicians have to evaluate EHRs and know how the data is used, a more open system in all directions.

Jonathan Bush Loves Health Data–But How Will We Get As Much As He Wants?

Posted on September 24, 2014 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://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 fervent hope of health care reformers is that someday we will each know as much about our bodies–our vital signs, the health of our organs, the contents of our genomes-as corporations know about our marketing habits. One of the recent expressions of this dream comes in Jonathan Bush’s engaging and readable account of the healthcare system, Where Does It Hurt?.

Bush is a tireless advocate for bottom-up, disruptive forces in healthcare, somewhat in the same camp as Vinod Khosla (whose Health Datapalooza keynote I covered) and Clayton Christensen (who wrote the forward to Bush’s book). What Bush brings to the discussion is hands-on experience at confronting the healthcare behemoth in an explicitly disruptive way (which failed) as well as fitting into the system while providing a bit more light by building athenahealth (which succeeded).

Bush’s book tours the wreckage of the conventional health care system–the waste, errors, lack of communication, and neglect of chronic conditions that readers of this blog know about–as well as some of the promising companies or non-profits that offer a way forward. His own prescription for the health care system rests on two main themes: the removal of regulations that prevent the emergence of a true market, and the use of massive data collection (on physicians and patients alike) to drive a rational approach to health care.

Both government and insurers would have a much smaller role in Bush’s ideal health care system. He recognizes that catastrophic conditions should be covered for all members of society, and that the industry will need (as all industries do) a certain minimum of regulation. (Bush even admitted that he “whined” to the ONC about the refusal of a competitor to allow data exchange.) But he wants government and insurers to leave a wide open field for the wild, new ideas of clinicians, entrepreneurs, and software developers.

Besides good old-fashioned human ingenuity, the active ingredient in this mix is data–good data (not what we have now), and lots of it. Bush’s own first healthcare business failed, as he explains, through lack of data along with the inconsistency of insurance payments. A concern for data runs through this book, and motivates his own entrance into the electronic health records market.

What’s missing from the Where Does It Hurt?, I think, is the importance of getting things in the right order: we can’t have engaged patients making free choices until an enormous infrastructure of data falls into place. I have looked at the dependencies between different aspects of health IT in my report, The Information Technology Fix for Health: Barriers and Pathways to the Use of Information Technology for Better Health Care. Let’s look at some details.

Bush wants patients to have choice–but there’s already a lot of choice in where they get surgery or other procedures performed. As he points out, some of the recent regulations (such as accountable care organizations) and trends in consolidations go in the wrong direction, removing much of this choice. (I have also written recently about limited networks.) One of Bush’s interesting suggestions is that hospitals learn to specialize and pay to fly patients long distances for procedures, a massive extension of the “medical tourism” affluent people sometimes engage in.

But even if we have full choice, we won’t be able to decide where to go unless quality measures are rigorously collected, analyzed, and published. Funny thing–quality measures are some of the major requirements for Meaningful Use, and the very things that health IT people complain about. What I hear over and over is that the ONC should have focused laser-like on interoperability and forgone supposedly minor quests like collecting quality measurements.

Well, turns out we’ll need these quality measures if we want a free market in health care. Can the industry collect these measures without being strong-armed by government? I don’t see how.

If I want a space heater, I can look in the latest Consumer Reports and see two dozen options rated for room heating, spot heating, fire safety, and many other characteristics. But comparable statistics aren’t so easy to generate in health care. Seeing what a mess the industry has made of basic reporting and data sharing in the data that matters most–patient encounters–we can’t wait for providers to give us decent quality measures.

There’s a lot more data we need besides provider data. Bush goes into some detail about the Khosla-like vision of patients collecting and sharing huge amounts of information in the search for new cures. Sites such as PatientsLikeMe suggest a disruptive movement that bypasses the conventional health care system, but most people are not going to bother collecting the data until they can use it in clinical settings.

And here we have the typical vicious cycle of inertia in health care: patients don’t collect data because their doctors won’t use it, doctors say they can’t even accept the data because their EHRs don’t have a place for it, and EHR vendors don’t make a place for it because there’s no demand. Stage 3 of Meaningful Use tries to mandate the inclusion of patient data in records, but the tremendous backward tug of industry resistance saps hope from the implementation of this stage.

So I like Bush’s vision, but have to ask: how will we get there? athenahealth seems to be doing its part to help. New developments such as Apple’s HealthKit may help as well. Perhaps Where Does It Hurt? can help forward-thinking vendors, doctors, health information exchanges, entrepreneurs, and ordinary people pull together into a movement to make a functioning system out of the pieces lying around the landscape.

Ten-year Vision from ONC for Health IT Brings in Data Gradually

Posted on August 25, 2014 I Written By

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

This is the summer of reformulation for national U.S. health efforts. In June, the Office of the National Coordinator (ONC) released its 10-year vision for achieving interoperability. The S&I Framework, a cooperative body set up by ONC, recently announced work on the vision’s goals and set up a comment forum. A phone call by the Health IT Standards Committeem (HITSC) on August 20, 2014 also took up the vision statement.

It’s no news to readers of this blog that interoperability is central to delivering better health care, both for individual patients who move from one facility to another and for institutions trying to accumulate the data that can reduce costs and improve treatment. But the state of data exchange among providers, as reported at these meetings, is pretty abysmal. Despite notable advances such as Blue Button and the Direct Project, only a minority of transitions are accompanied by electronic documents.

One can’t entirely blame the technology, because many providers report having data exchange available but using it on only a fraction of their patients. But an intensive study of representative documents generated by EHRs show that they make an uphill climb into a struggle for Everest. A Congressional request for ideas to improve health care has turned up similar complaints about inadequate databases and data exchange.

This is also a critical turning point for government efforts at health reform. The money appropriated by Congress for Meaningful Use is time-limited, and it’s hard to tell how the ONC and CMS can keep up their reform efforts without that considerable bribe to providers. (On the HITSC call, Beth Israel CIO John Halamka advised the callers to think about moving beyond Meaningful Use.) The ONC also has a new National Coordinator, who has announced a major reorganization and “streamlining” of its offices.

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Could Population Health Be Considered Discrimination?

Posted on August 19, 2014 I Written By

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

Long time reader of my site, Lou Galterio with the SunCoast RHIO, sent me a really great email with a fascinating question:

Are only the big hospitals who can afford the very expensive analytics pop health programs going to be allowed to play because only they can afford to and what does that do to the small hospital and clinic market?

I think this is a really challenging question. Let’s assume for a moment that population health programs are indeed a great way to improve the healthcare we provide a patient and also are an effective way to lower the cost of healthcare. Unfortunately, Lou is right that many of these population health programs require a big investment in technology and processes to make them a reality. Does that mean that as these population health programs progress, that by their nature these programs discriminate against the smaller hospitals who don’t have the money to invest in such programs?

I think the simple answer is that it depends. We’re quickly moving to a reimbursement model (ACOs) which I consider to be a form of population health management. Depending on how those programs evolve it could make it almost impossible for the small hospital or small practice to survive. Although, the laws could take this into account and make room for the smaller hospitals. Plus, most smaller hospitals and healthcare organizations can see this coming and realize that they need to align themselves to survive.

The other side of the discrimination coin comes when you start talking about the patient populations that organizations want to include as one of their “covered lives.” When the government talks about population health, they mean the entire population. When you start paying organizations based on the health of their patient population, it changes the dynamic of who you want to include in your patient population. Another possible opportunity for discrimination.

Certainly there are ways to avoid this discrimination. However, if we’re not thoughtful in our approach to how we design these population health and ACO programs, we could run into these problems. The first step is to realize the potential issues. Now, hopefully we can think about them going forward.

Hospital M&A Cost Boosted Significantly By Health IT Integration

Posted on August 18, 2014 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.

Most of the time, hospital M&A is sold as an exercise in saving money by reducing overhead and leveraging shared strengths. But new data from PricewaterhouseCoopers suggests that IT integration costs can undercut that goal substantially. (It also makes one wonder how ACOs can afford to merge their health IT infrastructure well enough to share risk, but that’s a story for another day.)

In any event, the cost of integrating the IT systems of hospitals that merge can add up to 2% to the annual operating costs of the facilities during the integration period, according to PricewaterhouseCoopers. That figure, which comes to $70,000 to $100,000 per bed over three to five years, is enough to reduce or even completely negate benefits of doing some deals. And it clearly forces merging hospitals to think through their respective IT strategies far more thoroughly than they might anticipated.

As if that stat isn’t bad enough, other experts feel that PwC is understating the case. According to Dwayne Gunter, president of Parallon Technology Solutions — who spoke to Hospitals & Health Networks magazine — IT integration costs can be much higher than those predicted by PwC’s estimate. “I think 2% being very generous,” Gunter told the magazine, “For example, if the purchased hospital’s IT infrastructure is in bad shape, the expense of replacing it will raise costs significantly.”

Of course, hospitals have always struggled to integrate systems when they merge, but as PwC research notes, there’s a lot more integrate these days, including not only core clinical and business operating systems but also EMRs, population health management tools and data analytics. (Given be extremely shaky state of cybersecurity in hospitals these days, merging partners had best feel out each others’ security systems very thoroughly as well, which obviously adds additional expenses.) And what if the merging hospitals use different enterprise EMR systems? Do you rip and replace, integrate and pray, or do some mix of the above?

On top of all that, working hospital systems have to make sure they have enough IT staffers available, or can contract with enough, to do a good job of the integration process. Given that in many hospitals, IT leaders barely have enough staff members to get the minimum done, the merger partners are likely costly consultants if they want to finish the process for the next millennium.

My best guess is that many mergers have failed to take this massive expense into account. The aftermath has got to be pretty ugly.

Population Health Polls

Posted on August 11, 2014 I Written By

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

I was thinking about population health today. It’s become a hot topic of discussion now that a lot more healthcare data is available for population health management thanks to EHR adoption. Although, in many ways, the various value based reimbursement and ACO programs are a form of population health. I guess, for me I classify all of these efforts to improve the health of a population as population health.

I just wonder how many organizations are really working on these types of solutions and how much of the population health is just talk. Let’s find out in the poll below.

I’ll be interested to hear how organizations are approaching population health. Also, let’s do another poll to see how much people will be working on population health in the future.

I’d love to hear more details to your responses in the comments. If you are working on population health, what programs are you doing and what IT solutions are you using to support it?