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Possible Future EHR UIs at CES

Posted on January 16, 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.

If you haven’t been following all of my CES Digital Health coverage, you might want to check out some of the following articles:
Initial CES 2015 Observations
Wearables Explosion at CES 2015
A Video Look at the Digital Health, Fitness and Wellness Section of CES 2015
A Look at Digital Health at CES 2015

While I was mostly focused on the Digital Health section of CES, I also took note of a number of new user interface approaches that various companies were demoing at CES. Since it’s CES, some of these are still conceptual, but they got my EHR UI thoughts going.

Finger Mouse
The Motix Touch Mouse was one of the most intriguing new user interfaces I’ve ever seen in the 10 years I’ve been attending CES. Your hands basically stay on the keyboard and a motion capture device follows your finger which works like a mouse on screen. It was a really interesting evolution of the mouse. Unfortunately, they didn’t have a great form example which would replicate the EHR world in which I live. So, I’m not sure how well this finger mouse would work filling out the long forms that many have in their EHR. However, the concept was really intriguing to consider.

Here’s a video demo of the Motix Touch Mouse:

3D Rudder
The 3D Rudder really blew my mind when I tried it out. I’m not exactly sure of its application in the EHR and healthcare IT world, but the experience of controlling your computer with your feet was really amazing. Plus, the foot control was able to work in 3 dimensions which made it really unique. It took me a second to learn, but I’d love the new way to look at how an input control could work.

You can see the 3D Rudder’s Indiegogo campaign, and here’s a video demo of the 3D Rudder:

While the mouse and keyboard have been tremendously powerful input devices for computers, I’m fascinated to consider how the evolution of computer input will go. We’ve seen the amazing growth of voice and touch over the past couple years. However, I think and hope we’re just getting started with how simple it will be to control the computers of the future. I believe the small innovations like the two mentioned above are part of the process of improving computer UIs as we know them.

I-STOP, ePrescribing, and Prescription Drug Abuse Infographic

Posted on January 15, 2015 I Written By

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

I don’t know why I’d never thought about how ePrescribing could help fight prescription drug abuse. This infographic has a lot of interesting data about prescription drug abuse, ePrescribing and the New York I-STOP program. Thanks DrFirst for sharing the infographic.

I-STOP ePrescribing Infographic

At Least One Patient A Day

Posted on January 14, 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.

One of my ophthalmology friends posted this video. I’m sure that many doctors can relate to patients like this. It reminds me of someone who told me they wish their was a health grades where the doctor can rate the patients the same way that patient rate the doctors. That’s probably not a productive approach, but it definitely shares the sentiment of many doctors who have challenging patients. Like most things in life though, it only takes a few bad apples to spoil the bunch. I’m not sure what can be done to deal with these challenging patients. Either way, this video highlights one of the challenges of being a doctor: difficult patients.

Do You Know Why Patients Don’t Pay Their Doctors?

Posted on January 13, 2015 I Written By

The following is a guest blog post by Tom Furr, CEO and Founder of PatientPay.
Tom Furr Headshot
Like most people after the holidays, I am swamped by the number of bills and charges that have accumulated over the past month! It certainly has been an expensive time of year. And like most I bite the bullet and remit payments and pay my bills on time. However there is a large segment of bills that aren’t getting paid, and it’s those that are owed to physicians and hospitals.

According to a report just released by the Consumer Financial Protection Bureau, almost 43 million Americans have unpaid medical bills. The main cause for this is that many Americans are confused by the statements that they receive from their medical providers and insurance companies about the cost of treatment. Lack of transparency in their statements and understanding what they owe has put a lot of people in a tough situation.

Practices too are feeling the pain. Because of this issue they are writing off a significant amount of bad debt that through some easy fixes could translate into quicker payments and better cash flow. The average overdue debt that a patient owes is over $1,700 and the most baffling thing is that most of these patients show no signs of other financial stress. So what does this mean to for practices? Most patients who owe money have the means to pay but don’t, because of their lack of understanding about what they really owe.

Here are three easy fixes practices and hospitals can make to help patients pay their bills, and pay them faster.

1. Integrate bill payment into your Practice Management software. Practices today should have one place where they can go to get a full picture of a patient’s payment history and not have to switch between applications.

2. Simplify your statements. Make it easy for patients to understand what your charges are, what insurance has paid by providing a statement that matches up to the patient’s Explanation of Benefits (EOB), and most importantly what they still owe. With this information they are much more likely to remit payment quickly or start a conversation with you so that you can resolve any outstanding issues.

3. Ditch paper billing. It’s 2015 and according to the USPS more than 60% of Americans across all demographics are paying their bills online. Online bills get paid faster and you can create your online statements to match the EOBs. If the majority of patients want to pay their bills online…let them!

With deductibles now resetting, practices will be collecting a significant amount of their revenue directly from patients…on average for the first five months of the year. It’s time to help patients pay their bills and practices collect what they’re owed.

About Tom Furr
Tom Furr is the CEO and founder of PatientPay, an application that enables practices to use “Paperless Billing” instead of paper statements to help them reduce their costs and errors while making it easier for patients to pay their bills. You can reach Tom at tf@patientpay.com.

What Happens When An EHR Vendor is Acquired?

Posted on January 12, 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.

With meaningful use money running out, and as the EHR industry matures, we’re going to see more and more consolidation in the EHR market. Many EHR vendors are going to start running out of money. Other larger EHR vendors are going to want to try and buy up market share. In some ways this has already begun. See Greenway being purchased by Vitera Healthcare Solutions and Cerner acquiring Siemens to name some of the larger ones that have happened recently. Although, anyone that’s been a user of Bond EHR (people still miss that EHR software), Allscripts MyWay, Misys, etc etc etc knows the challenges of when your EHR vendor gets acquired.

While your EHR being acquired by another EHR vendor is almost never a good thing for your EHR software’s future, L Nelms visited this post on EMR and EHR News and offered an even worse story of an EHR being acquired and the fallout the doctors felt. I’ve removed the name of the vendors since the principle could apply to many vendors that get acquired.

After completing Stage one of Meaningful Use, I am now dropping out of the whole damn thing. This decision is based entirely on my continued dissatisfaction with the EMR program I chose. I started using EHR Vendor A in 2012. As many know, EHR Vendor A was subsequently bought by ABC corporation who refused to honor the original contract which promised no additional fees. ABC corporation, knowing that they had customers “right where they wanted them” — knowing that switching programs would incur tremendous costs and disruption to the practices’ work flow, immediately imposed a $250.00 monthly “support fee”, requiring automatic payments from the customers credit card. I do not know what constitutes “support” from this company, as I had problems with the program and attempted to contact them numerous times from Nov 19, 2014 to Dec 9, without a SINGLE reply in any form from them. On Jan 1, 2015, they increased this fee to $300.00.

They continue to inundate us with newsletters telling us how wonderful they are, including an alert urging us to “respond today” to arrange to get the new certified software installed. This was sent on Christmas Eve! They warned us repeatedly that we must be using the new software ON Jan 1,2015, in order to meet MU. What they didn’t mention until the day before the install, was that there is a “one-time installation fee of $99.00” (charged immediately, of course, to you credit card).

I asked if I could do the install myself and was told “yes, but we’re not really charging for the install, we’re charging for the SQL server update (which actually can be done oneself ). But I was told I had to pay. And now, the new certified software, which is COMPLETELY different from the previous version, is a nightmare. It is agonizingly slow, painstakingly labor intensive, and heaven forbid I should require tech support who, on top of being nowhere to be found, are so disrespectful (the last one one I spoke to actually said — when I expressed my dissatisfaction with not being able to get my data when I terminate my contract — “well we didn’t force you to buy our program”

Which doesn’t explain why I feel so violated…..

I should clarify that my data from EHR Vendor A is “available”: after many cryptic replies from them over several days, I was finally told that I can access the data from the server, but then — and you all know the story– I must take out a second mortgage on my home to have the data converted to some semblance of a usable format. This may not be illegal (only because the the recklessness of the companies has not yet been regulated), but it is certainly of questionable ethicacy

I think this is a fear that many doctors have when selecting and purchasing their EHR software. It’s why many of them still choose to go with the big name EHR vendors. Stories like this one scare doctors away from a small EHR vendor with an uncertain future. Although, I’ve written previously about the uncertain future of large EHR vendors as well.

The EHR industry should do better than this. I hope this story is an aberration, but I’m afraid we’re going to see more and more stories like it as the EHR industry consolidates. There will still be many good EHR actors out there that are appalled by these stories like I am. Hopefully, more and more doctors will find those good actors who are sincere in their efforts to provide a quality product with a quality user experience for the doctor. They’re out there, but bad actors like what’s described above give the good apples a bad name.

Apervita Creates Health Analytics for the Millions

Posted on January 9, 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://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.

Health officials are constantly talking up the importance of clinical decision support, more popularly known now as evidence-based medicine. We’re owning up to the awkward little fact–which really should embarrass nobody–that most doctors lack expertise on many of the conditions they encounter and can’t read the thousands of relevant studies published each year. New heuristics are developed all the time for things such as predicting cardiac arrest or preventing readmissions after surgery. But most never make their way into the clinic.

Let’s look at what has to happen before doctors and patients can benefit from a discovery:

  1. The researcher has to write a paper with enough detail to create a working program from the heuristic, and has to publish the paper, probably in an obscure journal.

  2. A clinician or administrator has to find the article and line up staff to write and thoroughly test a program.

  3. If the program is to be used outside the hospital where it was created, it has to be disseminated. The hospital is unlikely to have an organization set up to package and market the program. Even if it is simply put out for free use, other institutions have to learn about it and compile it to work on their systems, in order for it to spread widely. Neither the researcher nor the hospital is likely to be compensated for the development of the program.

  4. The program has to be integrated into the doctor’s workflow, by being put on a menu or generating an alert.

Evidence-based medicine, therefore, is failing to tap a lot of resources that could save lives. A commonly cited observation is that research findings take 17 years to go into widespread practice. That’s 17 years of unnecessary and costly suffering.

I have often advocated for better integration of analytics into everyday medical practice, and I found a company called Apervita (originally named Pervasive Health) that jumps off in the right direction. Apervita, which announced a Series A round of funding on January 7, also has potential users outside of clinical settings. Pharma companies can use it to track adverse drug events, while payers can use it to predict fraud and risks to patients. There is not much public health data in the platform yet, but they’re working on it. For instance, Leapfrog group has published hospital safety info through their platform, and Diameter Health provides an all-cause 30-day readmissions prediction for all non-maternal, non-pediatric hospitalizations.

Here’s how the sequence of events I laid out before would go using Apervita:

  1. The researcher implements her algorithm in Python, chosen because Python is easy for non-programmers to learn and is consequently one of the most popular programming languages, particularly in the sciences. Apervita adds functions to Python to make it easy, such as RangeCompute or tables to let you compute with coefficients, and presents these through an IDE.

  2. The researcher creates an analytic on the Apervita platform that describes and publishes the analytic, along with payment terms. Thus, the researcher derives some income from the research and has more motivation to offer the analytic publicly. Conversely, the provider pays only for usage of the analytic, and does not have to license or implement a new software package.

  3. Clinicians search for relevant analytics and upload data to generate reports at a patient or population level. Data in popular formats such as Excel or comma-separated value (CSV) files can be uploaded manually, while programmers can automate data exchange through a RESTful web service, which is currently the most popular way of exchanging data between cooperating programs. Rick Halton, co-founder and Chief Marketing Officer of Apervita, said they are working on support for HL7’s CCD, and are interested in Blue Button+ button, although they are not ready yet to support it.

  4. Clinicians can also make the results easy to consume through personalized dashboards (web pages showing visualizations and current information) or by triggering alerts. A typical dashboard for a hospital administrator might show a graphical thermometer indicating safety rankings at the hospital, along with numbers indicating safety grades. Each department or user could create a dashboard showing exactly what a clinician cares about at the moment–a patient assessment during an admission, or statistics needed for surgical pre-op, for instance.

  5. Apervita builds in version control, and can automatically update user sites with corrections or new versions.

I got a demo of Apervita and found the administration pretty complex, but this seems to be a result of its focus on security and the many options it offers large enterprises to break staff into groups or teams. The bottom line is that Apervita compresses the difficult processes required to turn research into practice and offers them as steps performed through a Web interface or easy programming. Apervita claims to have shown that one intern can create as many as 50 health analytics in one week on their platform, working just from the articles in journals and web resources.

The platform encrypts web requests and is HIPAA-compliant. It can be displayed off-platform, and has been integrated with at least one EHR (OpenMRS).

Always attuned to the technical difficulties of data use, I asked Halton how the users of Apervita analytics could make sure their data formats and types match the formats and types defined by the people who created the analytics. Halton said that the key was the recognition of different ontolgies, and the ability to translate between them using easy-to-create “codesets.”

An ontology is, in general, a way of representing data and the relationships between pieces of data. SNOMED and ICD are examples of common ontologies in health care. An even simpler ontology might simply be a statement that units of a particular data field are measured in milliliters. Whether simple or complex, standard or custom-built, the ontology is specified by the creator of an analytic. If the user has data in a different ontology, a codeset can translate between the two.

As an example of Apervita’s use, a forward prediction algorithm developed by Dr. Dana Edelson and others from the University of Chicago Medical Center can predict cardiac arrests better than the commonly used VitalPAC Early Warning Score (ViEWS) or Modified Early Warning Score (MEWS). Developed from a dataset of over 250,000 patient admissions across five hospitals, “eCART” (electronic Cardiac Arrest Triage) can identify high-risk hospital ward patients and improve ICU triage decisions, often as much as 48 hours in advance.

The new funding will allow Apervita to make their interface even easier for end-users, and to solicit algorithms from leading researchers such as the Mayo Clinic.

Halton heralds Apervita as a “community” for health care analytics for authors and providers. Not only can the creators of analytics share them, but providers can create dashboards or other tools of value to a wide range of colleagues, and share them. I believe that tools like Apervita can bridge the gap between the rare well-funded health clinic with the resources to develop tools, and the thousands of scattered institutions struggling to get the information that will provide better care.

The New Congressional Rider: Unique Patient ID Lemonade?

Posted on January 8, 2015 I Written By

When Carl Bergman isn't rooting for the Washington Nationals or searching for a Steeler bar, he’s Managing Partner of EHRSelector.com.For the last dozen years, he’s concentrated on EHR consulting and writing. He spent the 80s and 90s as an itinerant project manager doing his small part for the dot com bubble. Prior to that, Bergman served a ten year stretch in the District of Columbia government as a policy and fiscal analyst, a role he recently repeated for a Council member.

Note: Previous versions referred to Rand Paul as the author of the first congressional rider. That was in error. The first rider was authored by then Representative Ron Paul. I regret the error. CB

Last month, I posted that Ron Paul’s gag rule on a national patient identifier was gone. Shortly, thereafter, Brian Ahier noted that the gag rule wasn’t dead. It just used different words. Now, it looks as if we were both right and both wrong. Here’s why. Paul’s rider’s gone, but its replacement, though daunting, isn’t as restrictive.

The gag rules are appropriation bill riders. Paul’s, which began in 1998, was aimed at a HIPAA provision, which called for identifiers for:

…. [E]ach individual, employer, health plan, and health care provider for use in the health care system. 42 US Code Sec. 1320d-2(b)

It prohibited “[P]lanning, testing, piloting, or developing a national identification card.” This was interpreted to prohibit a national patient id.

As I noted in my post, Paul’s language was dropped from the CRomnibus appropriation act. Brian, however, found new, restrictive language in CRomnibus, which says:

Sec. 510. None of the funds made available in this Act may be used to promulgate or adopt any final standard under section 1173(b) of the Social Security Act providing for, or providing for the assignment of, a unique health identifier for an individual (except in an individual’s capacity as an employer or a health care provider), until legislation is enacted specifically approving the standard.

Gag Rule’s Replacement Language

Unlike Paul’s absolutist text, the new rider makes Congress the last, biggest step in a formal ID process. The new language lets ID development go ahead, but if HHS wants to adopt a standard, Congress must approve it.

This change creates two potential adoption paths. Along the first, and most obvious, HHS develops a mandatory, national patient ID through Medicare, or the Meaningful Use program, etc., and asks congress’ approval. This would be a long, hard, uphill fight.

The second is voluntary adoption. For example, NIST could develop a voluntary, industry standard. Until now, Paul’s rider stopped this approach.

NIST’s a Consensus Building Not a Rulemaking Agency

NIST’s potential ID role is well within its non regulatory, consensus standards development mandate. It could lead a patient ID building effort with EHR stakeholders. Given the high cost of current patient matching techniques, stakeholders may well welcome a uniform, voluntary standard. That would not solve all interoperability problems, but it would go a long way toward that end.

Congress has loosened its grip on a patient ID, now its up to ONC, NIST, etc., to use this new freedom.

Assessment Released of Health Information Exchanges (Part 2 of 2)

Posted on January 7, 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://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The previous installment of this article talked about the survivability of HIEs, drawing on a report released under ONC auspices. This installment delves into some other interesting aspects of information exchange.

Data Ownership and Privacy Raise Their Heads
Whenever data is a topic, policy issues around ownership and privacy cannot be dismissed. The HIE report does not address them directly, but they peek out from behind questions of how all this stuff gets stored.

Two essential strategies allow data sharing. In the simpler strategy, the HIE vacuums up data from all the providers who join. In a more subtle and supple strategy, known as a federated system, the HIE leaves the data at the providers and just provides connectivity. For instance, the HIE report explains that some HIEs store enough data to identify patients and list the providers who have data on them (this uses a master patient index, which solves the common problem of matching a patient). Once a patient is matched, the HIE retrieves relevant data from each provider.

The advantage of the vacuum suction strategy is that, once an HIE has all the data in one place, it can efficiently run analytics across a humongous data set and deliver the highly desirable analytics and planning that make the HIE attractive to clients. But this strategy brings significant risk as well.

Programmers and administrators in the computer field have long understood the classic problem of copying data: if you keep two or more copies of data, they can get out of sync. The HIE report recognizes this weakness, indicating that HIEs storing patient data can get outdated (p. 12). According to the report, “Stakeholders reported it is very damaging to the reputation of state efforts when provider queries return insufficient results, leading users to conclude the system is not useful.” (p. 17) In fact, some HIEs don’t even know when a patient has died (p. 20).

Another classic problem of copying data is that it forces the HIE to maintain a huge repository, along with enough server power and bandwidth to handle requests. This in turn raises costs and drives away potential clients. Success in such cases can be self-defeating: if you really do offer convenient query facilities and strong analytic power, demands will increase dramatically. Larger facilities, which (as I’ve said) are more attractive to HIEs, will also use data in more highly developed and sophisticated ways, which will lead to more requests banging on the HIE’s door. It’s no whim that Amazon Web Services, the leading cloud offering in the computer field, imposes limits on data transferred, as well as other uses of the system.

Thus the appeal of federated systems. However, they are technically more complex. More significantly, their success or failure rests on standardization more than a vacuum suction strategy. If you have a hundred different providers using a couple dozen different and incompatible EHRs, it’s easier to provide one-way channels that vacuum up EHR data than to upgrade all the EHRs to engage in fine-grained communication. Indeed, incomplete standards were identified as a burden on HIEs (p. 19). Furthermore, data isn’t clean: it’s entered inconsistently by different providers, or in different fields (p. 20). This could be solved by translation facilities.

What intrigues me about the federated approach is that the very possibility of its use puts providers on the defensive over their control of patient data. If an HIE gets a federated system to work, there is little reason to leave data at the provider instead of putting it under the control of the patient. Now that Apple’s HealthKit and similar initiatives put patient health records back on the health care agenda, patient advocates can start pushing for a form of HIE that gives patients back their data.

What Direction for Direct Project?
The Direct project was one of the proudest achievements of the health IT reforms unleashed by the HITECH act. It was open source software developed in a transparent manner, available to all, and designed to use email so even the least technically able health care provider could participate in the program. But Direct may soon become obsolete.

It’s still best for providers without consistent Internet access, but almost anyone with an always-on Internet connection could do better. The HIE report says that in some places, “Direct use is low because providers must access the secure messaging system through a web portal instead of through their EHRs.” (p. 11)

A recent article uncovered the impedances put up by EHR vendors to prevent Direct from working. The HIE report bolstered this assessment (pp. 19-20). As for DirectTrust (also covered by the article’s reporter), even though it was meant to solve connectivity problems, it could turn into yet another silo because it requires providers to sign up and not all do so.

Ideally, health information exchange would disappear quietly into a learning health care system. The ONC-sponsored report shows how far we are from this vision. At the same time, it points to a few ways forward: more engagement with providers (pp. 14, 25), more services that add value to patient care, tighter standards. With some of these advances, the health care field may find the proper architecture and funding model for data exchange.

Assessment Released of Health Information Exchanges (Part 1 of 2)

Posted on January 6, 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://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.

Like my Boston-area neighbors who perennially agonize over the performance of the Red Sox, healthcare advocates spend inordinate amounts of time worrying about Health Information Exchanges (HIEs). Will the current round of exchanges work after most previous attempts failed? What results can be achieved from the 564 million dollars provided by the Office of the National Coordinator since 2009? Has the effort invested by the government and companies in the Direct project paid off, and why haven’t some providers signed up yet?

I too was consumed by such thoughts when reading a reported contracted by the ONC and released in December, “HIE Program Four Years Later: Key Findings on Grantees’ Experiences from a Six-State Review. Although I found their complicated rating system a bit arbitrary, I found several insights in the 42-page report and recommend it to readers. I won’t try to summarize it here, but will use some of the findings to illuminate–and perhaps harp on–issues that come up repeatedly in the HIE space.
Read more..

The Inside of a CT Scanner

Posted on January 5, 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.

This picture is just awesome. As I’m at CES 2015 this week I’ll be looking at the latest digital health companies. However, we often forget some of the amazing technologies like a CT scanner that we have in healthcare. Healthcare is awesome!