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Software Design – Dilbert Cartoon

Posted on August 31, 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’m afraid I’ve seen this approach in far too many healthcare organizations. This is particularly true in health data analytics. Let me know if you can relate to this cyclical discussion. I do think it’s getting better though as more people have experience in the process. It’s just been a very long road.

Population Health Survey

Posted on August 28, 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 the themes we’ve been writing a lot about recently is incorporating more social and behavioral health data into the EHR and healthcare. I think we’re at the start of a trend around using data in healthcare that is not going to stop. While we currently have more access to data than ever, it feels more like getting beat down by a wave on the beach than it does surfing a wave that provides an amazing thrill and speed. I guess I’m saying that we haven’t learned to harness the power of the wave data yet.

Much of the work we’re doing with healthcare data is around population health. I was intrigued by the findings of a population health survey done by Xerox. Here are some of the insights they shared with me:

What is population health? Definition components were ranked in the following order:

  1. Facilitates care across the health continuum
  2. Supports providing the highest quality of care at the lowest cost
  3. Uses actionable insight for patient care based on a variety of data
  4. Targets a specific population of individuals
  5. Enables patient engagement

Is population health management necessary?

100 percent of polled providers agree that population health management is necessary as the U.S. shifts to value-based care. 81 percent indicated they “strongly agree” with the statement, while the remaining 19 percent indicated they “somewhat agree” with the statement.

What is driving population health? Driving factors were ranked in the following order:

  1. Improved health outcomes
  2. Improved patient relationships and experiences
  3. Cost containment
  4. Increased revenue opportunity
  5. Brand and competition with others in market

What challenges exist in population health management? Challenges were ranked in the following order:

  1. Data management and integration capabilities
  2. Lack of financial incentives, too much risk
  3. Poor care coordination across care providers
  4. Creating actionable intelligence from available data
  5. Lack of provider expertise or knowledge
  6. Low patient engagement

When will population health management be a reality?

81 percent of polled providers believe their organizations will deliver fully scaled population health management programs within 5 years, which includes 16 percent who indicated they already are.

What this survey tells me is that we’re still trying to figure out population health. Plus, people have a really broad definition of what’s considered population health. Does that mean the word no longer has much meaning?

The final stat might be the most telling. Almost everyone believed that their organization would be able to deliver a fully scaled population health management program. Maybe there’s some arrogance bias in who participated in the survey, but I’m quite sure that we’ll have a lot more stragglers in the population health world than 18%. It’s taken us how many years to get 60% EHR adoption? I won’t be surprised if population health takes us even longer.

All of that said, the best organizations are going to leverage healthcare data to improve population health. That’s a powerful concept which isn’t going away ever.

EMR Vendors Slow To Integrate Telemedicine Options

Posted on August 27, 2015 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Despite the massive growth in demand for virtual medical services, major EMR vendors are still proving slow to support such options, seemingly ceding the market to more agile telemedicine startups.

Independent telemedicine vendors targeting consumers are growing like weeds. Players like Doctor on Demand, NowClinic, American Well and HealthTap are becoming household names, touted not only in healthcare blogs but on morning TV talk shows. These services, which typically hire physicians as consultants, offer little continuity of care but provide a level of easy access unheard of in other settings.

Part of what’s fueling this growth is that health insurers are finally starting to pay for virtual medical visits. For example, Medicare and nearly every state Medicaid plan also cover at least some telemedicine services. Meanwhile, 29 states require that private payers cover telehealth the same as in-person services.

Hospitals and health systems are also getting on board the telemedicine train. For example, Stanford Healthcare recently rolled out a mobile health app, connected to Apple HealthKit and its Epic EMR, which allows patients to participate in virtual medical appointments through its ClickWell Care clinic. Given how popular virtual doctor visits have become, I’m betting that most next-gen apps created by large providers will offer this option.

EMR vendors, for their part, are adding telemedicine support to their platforms, but they’re not doing much to publicize it. Take Epic, whose EpicCare Ambulatory EMR can be hooked up to a telemedicine module. The EpicCare page on its site mentions that telemedicine functionality is available, but certainly does little to convince buyers to select it. In fact, Epic has offered such options for years, but I never knew that, and lately I spend more time tracking telemedicine than I do any other HIT trend.

As I noted in my latest broadcast on Periscope (follow @ziegerhealth), EMR vendors are arguably the best-positioned tech vendors to offer telemedicine services. After all, EMRs are already integrated into a hospital or clinic’s infrastructure and workflow. And this would make storage and clinical classification of the consults easier, making the content of the videos more valuable. (Admittedly, developing a classification scheme — much less standards — probably isn’t trivial, but that’s a subject for another article.)

What’s more, rather than relying on the rudimentary information supplied by patient self-reports, clinicians could rely on full-bodied medical data stored in that EMR. I could even see next-gen video visit technology which exposes medical data to patients and allows patients to discuss it live with doctors.

But that’s not how things are evolving. Instead, it seems that providers are largely outsourcing telemedicine services, a respectable but far less robust way to get things done. I don’t know if this will end up being the default way they deliver virtual visits, but unless EMR vendors step up, they’ll certainly have to work harder to get a toehold in this market.

I don’t know why so few EMR companies are rolling out their own virtual visit options. To me, it seems like a no-brainer, particularly for smaller ambulatory vendors which still need to differentiate themselves. But if I were an investor in a lagging EMR venture, you can bet your bottom dollar I’d want to know the answer.

EMRs Must Support Hospital Outcomes Reporting

Posted on August 25, 2015 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Should a hospital be paid if it doesn’t make its outcomes statistics public? Pediatric heart surgeon Dr. Jeffrey Jacobs says “no.” Jacobs, who chairs the Society of Thoracic Surgeons National Database workforce, recently told CNN that he believes reimbursement should be tied to whether a hospital shares data transparently. “We believe in the right of patients and families to know these outcomes,” said Jacobs, who is with the Johns Hopkins All Children’s Heart Institute in St. Petersburg, FL.

Jacobs’ views might be on the extreme side of the industry spectrum, but they’re growing more common. In today’s healthcare industry, which pushes patients to be smart shoppers, hospitals are coming under increasing pressure to share some form of outcomes data with the public.

I’ve argued elsewhere that in most cases, most hospital report cards and ratings are unlikely to help your average consumer, as they don’t offer much context how the data was compiled and why those criteria mattered. But this problem should be righting itself. Given that most hospitals have spent millions on EMR technology, you’d think that they’d finally be ready to produce say, risk-adjusted mortality, error rates and readmissions data patients can actually use.

Today, EMRs are focused on collecting and managing clinical data, not providing context on that data, but this can be changed. Hospitals can leverage EMRs to create fair, risk-adjusted outcomes reports, at least if they have modules that filter for key data points and connect them with non-EMR-based criteria such as a physician’s experience and training.

While this kind of functionality isn’t at the top of hospitals’ must-buy list, they’re likely to end up demanding that EMRs offer such options in the future. I foresee a time when outcomes reporting will be a standard feature of EMRs, even if that means mashing up clinical data with outside sources. EMRs will need to interpret and process information sources ranging from credentialing databases and claims to physician CVs alongside acuity modifiers.

I know that what I’m suggesting isn’t trivial. Mixing non-clinical data with clinical records would require not only new EMR technology, but systems for classifying non-clinical data in a machine-readable and parseable format. Creating a classification scheme for this outside data is no joke, and at first there will probably be intermittent scandals when EMR-generated outcomes reports don’t tell the real story.

Still, in a world that increasingly demands quality data from providers, it’s hard to argue that you can share data with everyone but the patients you’re treating. Patients deserve decision support too.

It’s more than time for hospitals to stop hiding behind arguments that interpreting outcomes data is too hard for consumers and start providing accurate outcomes data. With a multi-million-dollar tool under their roof designed to record every time a doctor sneezes, analyzing their performance doesn’t take magic powers, though it may shake things up among the medical staff.  Bottom line, there’s less excuse than ever not to be transparent with outcomes. And if that takes adding new functionality to EMRs, well, it’s time to do that.

NYC Hospitals Face Massive Problems With Epic Install

Posted on August 24, 2015 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 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. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

A municipal hospital system’s Epic EMR install has gone dramatically south over the past two years, with four top officials being forced out and a budget which has more than doubled.

In early 2013, New York City-based Health and Hospitals Corp. announced that it had signed a $302 million EMR contract with Epic. The system said that it planned to implement the Epic EMR at 11 HHC hospitals, four long term care facilities, six diagnostic treatment centers and more than 70 community-based clinics.

The 15-year contract, which was set to be covered by federal funding, was supposed to cover everything from soup to nuts, including software and database licenses, professional services, testing and technical training, software maintenance, and database support and upgrades.

Fast forward to the present, and the project has plunged into crisis. The budget has expanded to $764 million, and HHC’s CTO, CIO, the CIO’s interim deputy and the project’s head of training have been given the axe amidst charges of improper billing. Seven consultants — earning between $150 and $185 an hour — have also been kicked off of the payroll.

With HHC missing so many top leaders, the system has brought in a consulting firm to stabilize the Epic effort. Washington, DC-based Clinovations, which brought in an interim CMIO, CIO and other top managers to HHC, now has a $4 million, 15-month contract to provide project management.

The Epic launch date for the first two hospitals in the network was originally set for November 2014 but has been moved up to April 2016, according to the New York PostHHC leaders say that the full Epic launch should take place in 2018 if all now goes as planned. The final price tag for the system could end up being as high as $1.4 billion, the newspaper reports.

So how did the massive Epic install effort go astray? According to an audit by the city’s Technology Development Corp., the project has been horribly mismanaged. “At one point, there were 14 project managers — but there was no leadership,” the audit report said.

The HHC consultants didn’t help much either, according to an employee who spoke to the Post. The employee said that the consultants racked up travel, hotels and other expenses to train their own employees before they began training HHC staff.

HHC is now telling the public that things will be much better going forward. Spokeswoman Ana Marengo said that the chain has adopted a new oversight and governance structure that will prevent the implementation from falling apart again.”We terminated consultants, appointed new leadership, and adopted new timekeeping tools that will help strengthen the management of this project,” Marengo told the newspaper.

What I’d like to know is just what items in the budget expanded so much that a $300-odd million all-in contract turned into a $1B+ debacle. While nobody in the Post articles has suggested that Epic is at fault in any of this, it seems to me that it’s worth investigating whether the vendor managed to jack up its fees beyond the scope of the initial agreement. For example, if HHC was forced to pay for more Epic support than it had originally expected it wouldn’t come cheap. Then again, maybe the extra costs mostly come from paying for people with Epic experience. Epic has driven up the price of these people by not opening up the Epic certification opportunities.

On the surface, though, this appears to be a high-profile example of a very challenging IT project that went bad in a hurry. And the fact that city politics are part of the mix can’t have been helpful. What happened to HHC could conceivably happen to private health systems, but the massive budget overrun and billing questions have government stamped all over them. Regardless, for New York City patients’ sake I hope HHC gets the implementation right from here on in.

What’s Information Governance and Why Does It Matter in Healthcare?

Posted on August 19, 2015 I Written By

Erin Head is the Director of Health Information Management (HIM) for an acute care hospital in Titusville, FL. She is a renowned speaker on a variety of healthcare and social media topics and currently serves as CCHIIM Commissioner for AHIMA. She is heavily involved in many HIM and HIT initiatives such as information governance, health data analytics, and ICD-10 advocacy. She is active on social media on Twitter @ErinHead_HIM and LinkedIn. Subscribe to Erin's latest HIM Scene posts here.

I recently spent some time explaining Information Governance (IG) and its importance to one of our executive leaders. She asked me to explain IG in 3 sentences or less to help her understand. Well, that was actually pretty difficult. It is complicated to summarize such a large, all encompassing framework that is IG but I believe I made the case effectively: “Information Governance is the umbrella that houses every transaction of information (not just medical records) within the organization and covers many different departments and tasks. It is much more than data governance. IG covers everything from monitoring the generation of data, protecting the information, controlling access to information, capturing revenue, governing the content and quality of the information, promoting population health, making decisions from data, and sharing the information internally and externally.”

Perhaps my explanation was less concise than she was looking for but IG is just that complex. I was happy to have the floor and to be able to discuss this topic with someone who can help me make an impact within the organization with a little education and guidance. I did not wait to be asked about IG. This topic is something of importance to me as an HIM professional and it’s also important to the successful operation of healthcare therefore I look for ways to insert the topic into everyday conversation at my organization. I welcome the opportunity to discuss IG.

This concept of governing information is not new; especially not to HIM professionals. Healthcare IG is becoming the new brand for the tasks we have done in HIM for decades. As more and more health information has become automated, IG has emerged as the necessary solution to the growing presence of raw data and increased electronic accessibility. I agree that governing health information and data in an electronic world is different from the paper-based records of the past but the foundation and concepts are the same. Managing information in the form of thousands of pieces of data takes technology and data analytics skills that HIM professionals are adapting and learning every day. We must take the new technology and the wealth of data and use it for the good of healthcare.

IG is really not so daunting when you start to apply it to everyday organizational workflows. It’s what HIM professionals know best. AHIMA has adapted ARMA’s generally accepted recordkeeping principles and has written a collaborative white paper to help us better understand what IG is in today’s data-driven healthcare environment. This is great for educating the HIM workforce and creating talking points for discussing IG within our organizations. If senior leaders and other healthcare professionals don’t understand IG and why an organization needs a structured approach, it is up to HIM professionals to start the conversation to introduce everyone to the principles of information governance and how HIM can lead the cause.

25% of EHR Budget Goes to EHR Training…At Least for the DoD EHR

Posted on August 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.

In all of the news surrounding Leidos and Cerner winning the DoD EHR bid, I was really struck by this one piece from Healthcare IT News:

Training. As is often the case in massive software implementations, training eats up a lot of the costs and, in the DoD’s case, “over 25 percent of the contract goes to training users and clinicians,” Miller said.

Think about how much training you can get for $1+ billion. I get that training is not cheap. I also get that the DoD EHR implementation is a massive project, but that’s a lot of money for training. Do you think that most EHR implementations spend 1/4 of their budget on training?

Hopefully people will chime in with their answer to that question in the comments. My experience is that hospitals probably should budget 1/4 of their budget for training, but most don’t get anywhere near that amount. Plus, the EHR training budget often starts much larger and then when the budget overruns start to happen, EHR training is one of the first places they go to cut the budget.

How much EHR training is enough in your experience? Should it be 25% of the budget? I’m not sure how much is needed, but I do know that most organizations don’t purchase enough. Sounds like the DoD might be the exception.

What’s the Glue Holding EHR Migration and Conversion Projects Together? – Optimize Healthcare Integration Series

Posted on August 13, 2015 I Written By

The following is a guest blog post by Stephane Vigot, President of Caristix, a leading provider of healthcare integration products and services. This post is part of the Optimize Healthcare Integration series.
Stephane Vigot - Caristix
Are you considering migrating from an older EHR to a newer EHR or are you in the process of that conversion? If so, you are well aware of the complexity of this process. There are a lot of reasons that drive the EHR conversion decision, but the primary reason that organizations undertake EHR conversion is simply to improve patient care and safety by providing clinicians and caregivers with the right information at the right time.

It’s easy to think that this is all about the technology. EHR conversion is far more than an IT project. It is a central business issue that needs to be strategically sponsored and backed by upper level management. In our previous post, we addressed the issue of aligning integration goals for business and technology.  In a project of this magnitude, aligning business and technology goals becomes critical. Implementation takes hard work, time, and is very expensive. Effectively dealing with scope, budget & time creep, and change management matched to the stated business goals is the key to success. The complex planning needed is just one part of the story but the actual execution can be extremely problematic.

Since the primary reason for undertaking EHR conversion is to improve patient care and safety, clinical workflow is top-of-mind and coupled to data exchange and flow through your systems. On the IT side, your analysts define the project requirements and your developers build the interfaces based on those requirements. But the team that plays the most critical role is your quality team. Think of them as your project’s glue.

QA has layers of responsibilities. They are the ones that hold the requirements as the project blueprint and make sure that those requirements, driven by the pre-identified business needs, are being met. They also make sure that all defined processes are being followed. Where processes are not followed, QA defines the resulting risks that must be accommodated for in the system. A subset of responsibility for QA is in the final gate-keeping of a project, the testing and validation processes that address the functionality and metrics of a project.

Analysts work to build the interfaces and provide QA with expected workflows. If those workflows are not correctly defined, QA steps in to clarify them and the expected data exchange, and builds test cases to best represent that evolving knowledge. Identifying workflow is often done blindly with little or no existing information. Once the interface is built, those test cases become the basis for testing. QA also plays an important role in maintenance and in contributing to the library of artifacts that contribute to guaranteeing interoperability over time.

Though it is difficult to estimate the actual costs of interfacing due to the variance implicit in such projects, functional and integrated testing is often up to 3x more time consuming than development. It’s important to note that this most likely represents defects in the process. Normally, in traditional software development those numbers are inversed with QA taking about 1/3 of development time. It’s quite common that requirements are not complete by the time the project lands in QA’s lap. New requirements are continually discovered during testing. These are usually considered to be bugs but should have been identified before the development phase started. Another major reason for the lengthy time needed is that all testing is commonly done manually. A 25 minute fix may require hours of testing when done manually.

In technology projects, risk is always present. QA teams continuously work to confine and evaluate risk based on a predefined process and to report those issues. The question continually being asked is: what are the odds that X will be a problem? And how important is that impact if there is a problem? Here the devil is in the details. QA is constantly dancing with that devil. Risk is not an all or nothing kind of thing. If one were to try and eliminate all risk, projects would never be completed. QA adds order and definition to projects but there are always blind alleyways and unknown consequences that cannot be anticipated even with the most well defined requirements. Dealing with the unknown unknowns is a constant for QA teams. The question becomes how much risk can be tolerated to create the cleanest and most efficient exchange of date on an ongoing basis.

If QA is your glue, what are you doing to increase the quality of that glue, to turn that into super glue? What you can do is provide tools that offset the challenges your QA team faces. At the same time, these tools help contain project scope, time & budget creep, and maintain continual alignment with business goals. The right tools should help in the identification of requirements prior to interface development and throughout that process, identify the necessary workflows, and help in the QA process of building test cases. De-identification of PHI should be included so that production data can be used in testing. Tools should automate the testing and validation process and include the capability of running tests repetitively. In addition, these tools should provide easily shared traceability of the entire QA process by providing a central depository for all assets and documentation to provide continuity for the interoperability goals defined for the entire ecosystem.

What is your organization experiencing in your conversion projects? We’d love to hear your thoughts in the comments.

Caristix, a leading healthcare integration company, is the sponsor of the Optimize Healthcare Integration blog post series.  Check out this free online demo of Caristix Workgroup product which helps you test your interface and speed up HL7 interface development.

About Stéphane Vigot
Stéphane Vigot, President of Caristix, has over 20 years of experience in product management and business development leadership roles in technology and healthcare IT. Formerly with CareFusion and Cardinal Health, his experience spans from major enterprises to startups. Caristix is one of the few companies in the health IT ecosystem that is uniquely focused on integrating, connecting, and exchanging data between systems. He can be reached at stephane.vigot@caristix.com

Data is Good. Context is Better.

Posted on August 10, 2015 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin is a true believer in #HealthIT, social media and empowered patients. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He currently leads the marketing efforts for @PatientPrompt, a Stericycle product. Colin’s Twitter handle is: @Colin_Hung

Last week I was asked by a colleague to explain a line I used during a presentation: “giving patients access to health data isn’t enough, we need to provide patients with context to go along with it. In fact context may be more valuable than the data itself”. My colleague, new to healthcare, didn’t understand the difference between data and context.

My usual go-to for explaining data vs context is this Wired Magazine article where they re-imagined standard medical lab tests. The blood test in particular clearly illustrates the concepts of data and context. On the standard blood test, vitamin D levels are simply shown as a number: 22 ng/mL. For most people, including me, this number means very little. Is it too low? Is it too high? Is it just right? In the re-imagined test, not only is the number presented, but it is placed on a scale that shows the patient what it truly means:
Reimagined Blood Test - Vitamin D

A few days ago, however, I found a more easy-to-understand example.

I happened to catch the nightly news on one of Toronto’s local television stations, Citynews. What caught my attention was their weather forecast. Citynews has always presented the weather by showing a variety of weather data: temperatures, humidity readings and barometric pressures. I’m sure many of you will find the following graphic very familiar:

CityTV Weather Graphic 5 - Normal Forecast

In the past few years, Citynews included more advanced weather metrics like UV readings, pollen counts and air quality indices. The latter two metrics are helpful to allergy suffers and those with respiratory issues. When pollen counts are high and air quality is low, people who are sensitive know to take medication and/or minimize their time outdoors.

But therein lies the problem with weather data. Presenting just the numbers means that the viewer has to put that information into their own context. For example, a 100F temperature combined with 40% humidity means that being outside is going to be uncomfortably sticky and hot. But see what you have to do there? You have to take the two data elements and then put them into context based on your own experience. The data only becomes useful when you are able to apply the right context.

Last week, however, I noticed that Citynews had moved past providing weather data and began providing true context about the weather. Here is the graphic that caught my eye:

CityTV Weather Graphic 3 - Context

To create this graphic, Citynews combined multiple data elements including:

  • Temperature
  • Humidex
  • UV
  • Pollen
  • Air quality
  • Chance of showers
  • Winds

I was blown away (excuse the weather pun) by what the Citynews weather team had done. They put weather data into context and the result was truly valuable information for viewers. Instead a collection of numbers, Citynews had provided context.

Now admittedly weather data is a bit simpler than clinical data, but if a local weather station can put data into context why can’t we do the same in healthcare?

Of course, healthcare and HealthIT vendors need to solve the problem of patient access to data first. But I don’t believe simply dumping data into the hands of patients and care givers is enough to change health behavior. To truly improve the health of patients and to drive down costs, patients need more than just number and facts. Patients need context.

Step 1: Access

Step 2: Context

The Power of Medical Device Data Infographic

Posted on August 6, 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 the advantages of devices is that they’re really good at collecting vast amounts of data. One of the problems we have in healthcare is that our medical devices collect a lot more healthcare data than we actually use. It’s too bad since no doubt there is a lot more benefit we could receive from all the medical device data we’re collecting.

This point was really driven home when I saw the infographic below from Capsule which looked at The Power of Medical Device Data. Take a look and see what I mean and then ask yourself, how could we better use medical device data?
THE POWER OF MEDICAL DEVICE DATA to Healthcare