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

Operational CIO vs Strategic CIO

Posted on May 30, 2017 I Written By

John Lynn is the Founder of the 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 and 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’ve been thinking and writing about the difference between an operational CIO and a strategic CIO for quite a while. There are far too many operational CIOs in healthcare who just want to make sure that the computers are replaced, the internet is fast and that they have good uptime. I believe CIOs that take this approach are making a mistake because they’re turning themselves into a commodity as opposed to a strategic part of their organization.

If you’re not sure of the difference, David Chou shared this great graphic which illustrates the difference between an operational healthcare CIO vs a strategic healthcare CIO.

Do you think it matters if you’re an operational CIO or a strategic CIO? I look forward to your thoughts in the comments.

Epic EHR Switching Video from Mary Washington Healthcare (MWHC)

Posted on May 26, 2017 I Written By

John Lynn is the Founder of the 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 and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

We’re back with another Fun Friday video (and a bonus story) to prepare you for the weekend. This week’s Fun Friday video comes from Mary Washington Healthcare (MWHC) doing a parody of a Hamilton song, “Right Hand Man,” as part of their switch to Epic. The production quality is really quite amazing and I love the choice of Hamilton. Check it out:

Now for a fun little story. I showed one of these EHR go-live videos to the Healthcare IT and EHR course I taught in Dubai. The majority of attendees were from Saudia Arabia with a few from Kuwait and UAE.

Well, the attendees loved the video. I asked them how well creating a video like this would go over in their hospitals. They all laughed and shook their heads. Certainly, the cultures are quite different. However, I did find it interesting that just as many people in the middle east were taking selfies as the US. Maybe the human desire isn’t all that different.

I don’t expect any of my students in the workshop to do anything like the above video. However, the concept of bringing your team together in an effort like what it takes to create this video is a powerful idea that could be applied regardless of culture.

Measuring Population Health ROI Is Still Tricky

Posted on May 24, 2017 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or

Over the past few years, health systems have made massive investments in population health management technology. Given the forces driving the investments are still present – or even closer at hand – there’s every reason to believe that they will continue.

That being said, health leaders are beginning to ask more questions about what they’re getting in return.  While systems may have subjected the initial investments to less scrutiny than usual, having accepted that they were critically necessary, many of these organizations are now trying to figure out what kind of return on investment they can expect to realize. In the process, some are finding out that even deciding what to measure is still somewhat tricky.

Many healthcare organizations started out with a sense that while investment returns on pop health management tech would take a while, they were in the knowable future. For example, according to a KPMG survey conducted in early 2015, 20 percent of respondents believed that returns on their investment in population health IT would materialize in one to two years, 36 percent expected to see ROI in three to four years and 29 percent were looking at a five+ year horizon.

At the time, though, many of the execs answering the survey questions were just getting started with pop health. Thirty-eight percent said their population health management capabilities were elementary-stage, 23 percent said they were in their infancy and 15 percent said such capabilities were non-existent, KPMG reported.

Since then, health systems and hospitals have found that measuring – much less realizing – returns generated by these investments can be complicated and uncertain. According to Dennis Weaver, MD, a senior consultant with the Advisory Board, one mistake many organizations make is evaluating ROI based solely on whether they’re doing well in their managed care contracts.

“They are trying to pay for all of the investment – the technology, care managers, operational changes, medical homes—all with the accountable payment bucket,” said Weaver, who spoke with Healthcare Informatics.

Other factors to consider

Dr. Weaver argues that healthcare organizations should take at least two other factors into account when evaluating pop health ROI, specifically reduction of leakage and unwarranted care variation. For example, cutting down on leakage – having patients go out of network – offers a 7 to 10 times greater revenue opportunity than meeting accountable care goals. Meanwhile, by reducing unwarranted variations in care and improving outcomes, organizations can see a 5 percent to 10 percent margin improvement, Weaver told the publication.

Of course, no one approach will hold true for every organization.  Bobbie Brown, senior vice president with HealthCatalyst, suggests taking a big-picture approach and drilling down into how specific technologies net out financially.

She recommends that health organizations start the investment analysis with broad strategic questions like “Does this investment help us grow?” and “Are we balancing risk and reward?” She also proposes that health leaders create a matrix which compares the cost/benefit ratio for individual components of the planned pop health program, such as remote monitoring and care management. Sometimes, putting things into a matrix makes it clear which approaches are likely to pay off, she notes.

Over time, it seems likely that healthcare leaders will probably come to a consensus on what elements to measure when sizing up their pop health investments, as with virtually every other major HIT expense. But in the interim, it seems that figuring out where to look for ROI is going to take more work.

Vendor Involvement in Online Communities – Caution but Proceed Forward

Posted on May 22, 2017 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 speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

At the Healthcare Marketing and Physician Strategies Summit #HMPS17 (May 8-10 in Austin TX), I presented alongside Dan Dunlop @dandunlop President of Jennings and Cindy Price Gavin @cindypricegavin, Founding Executive Director of Let’s Win! Sharing Science Solutions for Pancreatic Cancer. The three of us will discuss Online Communities

The same week on the #hcldr tweetchat we asked the community for opinions on vendor involvement in online healthcare communities:

  • Should healthcare vendors join online communities or stay clear?
  • Should online communities like #hcldr #lcsm #LupusChat or #bcsm be accepting of sponsorships or would they lose too much credibility?

These questions generated a lot of discussion and a variety of viewpoints were shared.

In general, most people were favorable to vendors participating in online communities – as long as they didn’t try to push their products/services while interacting with community members.

One particularly interesting viewpoint was shared by Ken Gordon @quickmuse:

Ken’s point is well made: people want to connect with people, not faceless company avatars. In an online community, members want to interact with other members and get useful information. So if a company wants to participate, one easy path to success is to allow individuals from the company be the participant not the company account itself. The company “wins” twofold with this approach. First, employees will feel valued and trusted since the company is allowing them to express themselves online. Second, the company will gain goodwill be seen by the association to active members who are contributing to the conversation.

There are plenty of great examples from both the #hcldr and #HITsm communities. Just look at @TextraHealth, @OchoTex, @burtrosen, @MandiBPro, @drnic1 and @techguy – each represents the company they work for/at AND contributes to the community as unique individuals. They are all trusted individuals and by extension we look upon the organizations they represent more favorably.

One of the most important factors to vendor involvement in an online healthcare community is disclosure. This was brought up several times when #hcldr discussed the second question:

Many recommended that community leaders establish clear guidelines for how sponsorship money would to be used and to publish what vendors could expect/not expect in return for their $$$.

Other practical advice for community administrators and hosts included:

Personally, I believe vendors SHOULD get involved in online healthcare communities – even if just to listen to what their target audiences are saying. They could learn so much just by seeing what topics are being discussed and the frustrations people are experiencing. Product marketers and developers would have a field day with all the information being shared online.

One word of caution though – when vendors do decide to participate, they need to realize that many in the community will be very skeptical at the start. Online communities are typically outgrowths of individual passions and interests. As such, corporations can be viewed by many as “invaders” into a private space. So caution…but please proceed forward.

Real-Time Health Systems (RTHS) and Experiential Wayfinding

Posted on May 19, 2017 I Written By

The following is a guest blog post by Jody Shaffer from Jibestream.

You have probably heard about Real-Time Health Systems (RTHS). This is a game-changing trend among healthcare providers where the delivery of healthcare is transforming to a more aware and patient-centric system. Providers are leveraging technology to get pertinent information to decision makers as quickly as possible empowering them to make more informed decisions in real-time. Facilities that are amenable to change will remain strong in competitive markets, while those who are reluctant to adapt will fall behind.

As we entered this new era in healthcare, providers are faced with a series of challenges. Smart medical devices are transforming the healthcare dynamic as medical data and information is produced and multiplying at an exponential rate, yet it’s use has not been keeping pace. This data overload has created a significant obstacle for healthcare providers to overcome. There is also intense pressure to create a consumer and patient experience that is dynamic, accessible and engaging.

So the question is, how can healthcare providers quickly process and interpret copious amounts of data into a digestible format for immediate patient consumption while internalizing and translating the same data into operational intelligence?

The answer lies in evolving to a paradigm that is situationally aware and patient-centric in both operations and management. Not only is this pivotal in successfully achieving a RTHS, it ensures that healthcare providers connect, communicate and collaborate more effectively than they have in the past.

When looking to achieve a Real-Time Healthcare System, there are four primary phases that need to be addressed:

Phase 1 – Collecting data

Phase 2 – Processing data

Phase 3 – Translating data into intelligence

Phase 4 – Utilizing/sharing data

The final two phases are essential for healthcare providers to excel in this changing market dynamic and meet increasing patient expectations.

To yield valuable intelligence, data needs to be presented with situational context. Raw data is in itself useful for analytics, but can only be leveraged to create spatial awareness when augmented with location-based data.

Consumers have grown accustomed to the convenience of real-time access to information from mobile devices and apps, and healthcare is no exception. Through a combination of location-aware technologies, hospitals can eliminate some of patient’s biggest frustrations fostering a more positive patient experience across the continuum of care.

Mobile apps, digital maps and interactive kiosks leverage connected technologies to help create a more familiar and engaging environment promoting an effortless and seamless patient experience.

Experiential wayfinding, made available through these technologies, form the foundation for enhancing patient experience, which is paramount to the success of a healthcare organization. Experiential wayfinding reduces the complexity of indoor spaces by anticipating where people are going and what they are looking for. It can be used to direct visitors to a facility and identify parking availability nearest their desired location. Once there, it can be used to guide visitors to destination(s) within a facility using turn-by turn directions making it easy and less stressful to get where they need to go.

An integrated platform can also enable proactive interactions engaging patients before, during, and after hospital visits. The use of mobile messaging to deliver contextual content based on a patient’s location and profile help create a more pleasant and efficient patient experience. Prior to a visitor’s departure to a hospital, the facility’s mobile apps can share information such as appointment delays or traffic delays to take into account on the way there. Mobile messaging also enables facilities to communicate with visitors by sending appointment reminders, context-aware messages, preparation guidelines, post-care instructions, and more. Another application of this can save patients the frustration of intolerable wait-times when a hospital is stretched beyond capacity by sending notifications to offer a change of appointment or alternate appointment location.

Location awareness and spatial context benefit both patients and healthcare providers alike. For clinicians and healthcare teams, this translates to accelerated productivity facilitated through visibility, the streamlining of processes resulting in the elimination of inefficiencies, minimizing staff interruptions, and a balance between resources and demand.

When managed properly, a RTHS enables healthcare providers to improve patient satisfaction and outcomes by leveraging the vast amount of data made available through connected computers, technologies and medical equipment across hospitals, clinics, and patient homes.

By merging the location dimension into healthcare systems, providers are able to bring order to complex data. Through geoenrichment and data visualization, providers can improve patient experiences and outcomes, uncover previously unseen data patterns, realize workflow efficiencies through connected technologies and enrich business insights leading to better more actionable decisions.

Behind the Scenes: Preparing for a RTHS Transition

  • Digitization of Space (converting CAD/DWG map files to SVG)
    Before data can be presented in the context of a map, healthcare providers need to digitize their space. This provides a scalable platform for plotting data to support multiple use cases.
  • Connect core systems and data
    Leveraging technology that offers interoperability allows for seamless integration of core systems and data
  • Connect assets and people
    Create situational awareness by connecting to assets and people
  • Connect maps to data with Indoor Positioning Systems (IPS)
    Look for a solution that offer a technology agnostic architecture to calibrate maps Indoor Positioning
  • Implementation
    Make all this available by extending solution to patient and nonpatient hospital workflows

About Jody Shaffer
Jody Shaffer is an experienced marketer with more than 13 years in the software industry. Jody currently leads the marketing department at Jibestream, an award-winning company specializing in indoor mapping and location intelligence solutions. The company’s platform provides developers with the tools to build custom map-enabled applications unlocking the full potential of the Internet of Things (IoT). Jibestream’s platform can be found implemented in hospitals and health care facilities across north America.

Healthcare Analytics are the Problem. Applied AI is the Solution.

Posted on May 17, 2017 I Written By

The following is a guest blog post by Gurjeet Singh, Executive Chairman and Co-founder of Ayasdi.

The combination of electronic medical records, financial data, clinical data, and advanced analytics promised to revolutionize healthcare.

It hasn’t happened.

The common excuse is that healthcare wasn’t really prepared for the enormity and complexity of the data challenge and that, over time, with the next EMR implementation, that healthcare will be positioned to reap the benefits. Unfortunately, the next generation of EMR, or the one after that, isn’t going to solve the problem.

They problem is on the analytics side.

Healthcare analytics are still driven by a question-first approach. The start of our analytics journey still begins with the question.  The challenge is which question? The more data we have at our disposal, the more potential questions there are and the lower the likelihood that we will ask the one that generates new value for the patient, the provider, or the payer. Even when we are successful in asking the right question, we have engaged in a confirmatory process – we have confirmed something we already knew.

Some will suggest that predictive analytics solves the problem, but it too is hypothesis driven – just in a different way. With predictive analytics, the set of variables selected, the choice of algorithms are, in effect, guesses as to what will produce the best outcome.

Ultimately, both approaches are flawed.

We need a new approach that surfaces trends we humans haven’t even considered, and that delivers a host of meaningful insights to clinicians before they even ask any questions. We need technology solutions that combine the best qualities of human intelligence (artificial intelligence) with the best computing capabilities that exceed human ability (machine learning).  When these technologies are operationalized systematically across an enterprise, it’s called Applied AI.  Applied AI is here to replace healthcare analytics, and we all stand to benefit.

Five Keys to Applied AI

Applied AI has already begun driving care improvement, cost-reduction, and improved clinical and financial decision-making across the healthcare enterprise – and the entire healthcare continuum. Applied AI is not a concept, but a series of intelligent applications that target discrete healthcare problems from clinical variation to population health. These intelligent applications have a collection of capabilities that make them intelligent – of which all need to be present. Let’s look at those capabilities:

DiscoveryIntelligent applications need to support both unsupervised and semi-supervised discovery. These capabilities are quite rare but serve as the foundation for our efforts to move past hypothesis driven inquiry. In practical terms, this means that an intelligent application considers all the data and all the possibilities within that data to detect the patterns, groups or anomalies that elude traditional approaches. Using their own systems of records, including EMRs, financial data, patient-generated data, and socio-economic data, healthcare organizations can automatically discover groups of patients that share unique combinations of characteristics. These groups can then be used to tailor and personalize diagnostics and care paths, for example. Alternatively, healthcare organizations may also discover unique patterns or outliers within their claims data to aid in member retention or preventing fraud or waste. This type of holistic discovery is unique to AI and improves prediction and makes operational insights possible.

Predictions Intelligent applications must also be able to predict the future with high accuracy. Holistic discovery enables even better predictive models through the unbiased creation of groups or the identification of patterns. Superior prediction gives healthcare organizations foresight into the future needs, costs, disease burden, and risks of patients. For example, intelligent applications can determine the groups of patients projected to have the highest escalation of costs over time, as well as other outcomes such as the conditions likely to appear for each group, and an individual’s predicted change in utilization. Predictions can be made across multiple targets and are multi-faceted, considering all factors whether they’re health- or non-healthcare-related occurring outside of the healthcare system.

JustificationAn intelligent solution must justify its predictions, discoveries, and actions in a transparent way so human operators feel confident to act upon its recommendations. For example, a healthcare app may reveal differentiating characteristics of patient risk trajectories, what factors make them high or low-risk, and descriptions of individual factors that lead to variation in cost and quality. Justification is key because without a thorough understanding of the “why” behind predictions, organizations are unable to adopt AI into day-to-day decision-making.

Action An intelligent system that is not effectively operationalized will become less intelligent over time. Actionable information that guides and augments human decision-making is what makes AI a part of daily operations. For these systems to deliver optimal value they need humans in the loop providing feedback and governance. Whether it be a recommended care path or a detailed risk profile, intelligent applications allow organizations to collaborate on the best actions tailored for each patient population, or to physicians or organizations. Across the care continuum, within health systems and health plans, this allows them to better assess individuals and the best course of care, and more confidently prescribe care and programs for each individual.

LearningIntelligent applications “learn” to improve predictions over time. As more and more data is analyzed, the technology learns from these complex data points to improve predictions over time. Whether it be claims, medical records, or socio-economic data, AI taps into these data points to generate more accurate, personalized predictions that continuously improve. Further, intelligent apps learn the impact of actions over time to support and continuously improve decision making.

Applied AI in action

A large hospital system decided it wanted to reduce clinical variation across its enterprise to improve outcomes for all patients. It implemented machine intelligence, including unsupervised machine learning techniques that run algorithms using the system’s own data—not benchmarks—to uncover actionable insights. The technology correlates and analyzes electronic medical record and financial data including treatments prescribed, procedures performed, drugs administered, length of stay, and costs per patient. The goal was to discover and refine clinical pathways that are optimized to drive higher quality of care and lower costs.

The machine intelligence solution identified a group of orthopedic surgeons who consistently had better outcomes among their knee replacement patients. These patients had shorter hospital stays and shorter time to ambulation than other total knee surgery replacements across the system. The solution also told clinicians why:  these doctors prescribed a unique, not widely used medication at an earlier postsurgical time than their peers. The medication reduced patients’ pain so they could get out of bed and walk around sooner – improving their outcomes and reducing costs.

Clinicians hadn’t previously known to look for variation based on what medication was given post-operatively. But machine intelligence identified a pod of doctors with better outcomes that were statistically significant. By comparing very large numbers of data points, the solution quickly uncovered why.  Now the hospital system has operationalized these best practices throughout their hospitals, lowering costs for knee replacement by more than 5 percent, and reducing pain for patients.

The last piece of the puzzle – AI applications

As healthcare organizations increasingly see the value of Applied AI, they may worry that more robust technology means greatly increased technical headcount to manage this strategy. But an important component of a successful Applied AI strategy is that it leverages the unique capabilities of both machines and humans. Hiring a dozen data scientists won’t make the most of the human intelligence within your organization. That’s because these new data scientists likely would not have the subject matter expertise needed to recognize and deploy the meaningful insights that surface. Meanwhile, the people who are the best suited to learn from the data, domain experts, usually do not have an interface to read data themselves. Subject matter experts typically only interact with data using rudimentary applications like PowerPoint or Excel.

So, the last key to a successful Applied AI strategy is to wrap the results of machine learning and artificial intelligence into business-facing applications. These applications can be customized for the types of insights they uncover, such as the optimal way to perform surgical procedures. It’s critical that the results of machine learning and machine intelligence actually make it to clinicians, instead of ending up siloed somewhere in the IT department. The successor technology to healthcare analytics must not only be more powerful and more precise, it must also be more user-friendly.

What’s Next

Healthcare analytics simply aren’t living up to their promise. We can wring our hands, we can wait, we can soldier on with insights that only marginally move the needle to improve outcomes and lower costs. Or we can combine artificial intelligence with powerful machine learning to turn enormous datasets into business insights that really matter. Then we can deliver those insights, via easy-to-use business applications, to the best clinician minds, to operationalize this machine intelligence approach across the enterprise. That’s Applied AI, and it’s a bright future.

About Gurjeet Singh
Gurjeet Singh is Ayasdi’s Executive Chairman and co-founder. As the Executive Chairman, he leads a technology movement that emphasizes the importance of extracting insight from data, not just storing and organizing it.

Gurjeet developed key mathematical and machine learning algorithms for Topological Data Analysis (TDA) and their applications during his tenure as graduate student in Stanford’s Mathematics Department where he was advised by Ayasdi co-founder Prof. Gunnar Carlsson.

Gurjeet is the author of numerous patents and has published in a variety of top mathematics and computer science journals. Before starting Ayasdi, he worked at Google and Texas Instruments. Gurjeet was named by Silicon Valley Business Journal as one of their 40 Under 40 in 2015.

Gurjeet holds a B.Tech. from Delhi University, and a Ph.D. in Computational Mathematics from Stanford University. He lives in Palo Alto with his wife and two children, and develops multi-legged robots in his spare time.

Enhance Your Conference Experience with Social Media

Posted on May 15, 2017 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 speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

The Healthcare Marketing and Physician Strategies Summit #HMPS17 has come to a close and I am reminded again of the power that social media has to enhance the whole conference experience. Pre-mobile, as an attendee, you could count on making 10-20 contacts during a conference…more if you really “worked the room” at the social events. Today it is entirely possible to meet 50+ new people at a conference by leveraging social media before and during the event.

At #HMPS17 I saw many examples of how social media has changed the attendee dynamics at conferences. I watched a group of 5 Instagram users meetup at the hotel restaurant (I’m pretty sure some food pics were taken!). I also saw two different groups of Facebook friends head out for a night on the town together. Of course, the #hcldr community had a meetup in the hotel lobby that attracted 8 people – 5 of whom came to the hotel just for the meetup (Thanks for driving 2hrs from Houston @JoeBabaian!)

During the conference itself I ran into at least 20 other people that knew from social media. All of these were first-time meetings (or what I call meeting old friends for the first time). This degree of networking would have been very difficult in the era before social media. You would have had to attend the same conference consistently for a number of years in order for people to get to know you. I would encourage fellow marketers and salespeople to get active on social media. There simply is no better accelerator for business relationships.

Since #HMPS17 spanned a Tuesday, I had the rare opportunity to organize a group session for the weekly #hcldr chat. Four of us gathered together and participated in the tweetchat while physically sitting beside each other. If you’ve never done this or seen it, it does look very strange. People are staring at their devices, madly typing and barely talking. Then all of a sudden someone will make a comment out loud about a tweet they have read and everyone chimes in with a verbal comment. Usually these side conversations last 1-2 minutes and then people go back to their devices. A few minutes later it happens again.

Through the one we held at #HMPS17 I now have two new friends: Alexis Todd and Tori Benick of UltraLinq. It was truly wonderful to see how much they enjoyed their first tweetchat. Dan Dunlop @dandunlop (who was the other in-person participant) commented to me how especially energizing it is to hear new perspectives and to see how excited newcomers get when they discover how educational a tweetchat can be.

If you are in healthcare marketing or involved with sales to healthcare organizations, I would really encourage you to join the conversations happening on social media. It doesn’t matter the social platform you choose – just pick one and dive in. Not only will you take your healthcare conference experience up a notch, but you as well as your organization will benefit through the connections you make.

See you on Twitter.

Predicting Readmissions, Longitudinal Record, and Physicians’ Time

Posted on May 12, 2017 I Written By

John Lynn is the Founder of the 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 and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Here’s a quick look around the Twittersphere and a few topics that stood out to me that I think might be of interest to you.

I’ve been following algorithms like this for a while and they’re really starting to come into their own. This type of predictive technology or predictive analytics if you prefer is going to really change how we manage patients in a hospital. If done right, it can help us become proactive instead of reactive. This will require us to change a lot of processes though.

Is a longitudinal health record possible in any format? I’m beginning to think that it’s a pipe dream that will never happen. At least not with our current documentation requirements.

I find time studies like these very interesting. However, the thing I hate about them is that we don’t have a time study from before implementing EHR software so we could compare how a physician used their time before EHR and after. No doubt over 50% of their time being spent on documentation and not face-to-face with the patient feels bad. However, how far off was this from where we were in the paper world?

Looking at the chart, prescription refills can be faster in an EHR. Secure messages can be faster with an EHR since you’re not playing phone tag which was the process before secure messages. Telephone encounters were likely the same. That leaves just the progress notes as the one thing that could be more time consuming in an EHR than the paper chart. How much more is the real question. Paper chart progress notes weren’t all that fast either. That’s why stacks of paper charts that weren’t completed were always sitting on physicians’ desks.

I guess the core question I would ask is, “Are EHRs the reason doctors hate medicine, or are the ongoing regulations and requirements that have been heaped on doctors the real problem?” My guess is that all this documentation overheard that’s being required of doctors was a problem in the paper world, but has been exacerbated in the EHR world. What do you think?

2 Core Healthcare IT Principles

Posted on May 10, 2017 I Written By

John Lynn is the Founder of the 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 and 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 favorite bloggers I found when I first starting blogging about Healthcare IT was a hospital CIO named Will Weider who blogged on a site he called Candid CIO. At the time he was CIO of Ministry Health Care and he always offered exceptional insights from his perspective as a hospital CIO. A little over a month ago, Will decided to move on as CIO after 22 years. That was great news for me since it meant he’d probably have more time to blog. The good news is that he has been posting more.

In a recent post, Will offered two guiding principles that I thought were very applicable to any company working to take part in the hospital health IT space:

1. Embed everything in the EHR
2. Don’t hijack the physician workflow

Go and read Will’s post to get his insights, but I agree with both of these principles.

I would add one clarification to his first point. I think there is a space for an outside provider to work outside of the EHR. Think of someone like a care manager. EHR software doesn’t do care management well and so I think there’s a space for a third party care management platform. However, if you want the doctor to access it, then it has to be embedded in the EHR. It’s amazing how much of a barrier a second system is for a doctor.

Ironically, we’ve seen the opposite is also true for people like radiologists. If it’s not in their PACS interface, then it takes a nearly herculean effort for them to leave their PACS system to look something up in the EHR. That’s why I was excited to see some PACS interfaces at RSNA last year which had the EHR data integrated into the radiologists’ interface. The same is true for doctors working in an EHR.

Will’s second point is a really strong one. In his description of this principle, he even suggests that alerts should all but be done away within an EHR except for “the most critical safety situations. He’s right that alert blindness is real and I haven’t seen anyone nail the alerts so well that doctors aren’t happy to see the alerts. That’s the bar we should place on alerts that hijack the physician workflow. Will the doctor be happy you hijacked their workflow and gave them the alert? If the answer is no, then you probably shouldn’t send it.

Welcome back to the blogosphere Will! I look forward to many more posts from you in the future.

Google’s DeepMind Rolling Out Bitcoin-Like Health Record Tracking To Hospitals

Posted on May 8, 2017 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or

Blockchain technology is gradually becoming part of how we think about healthcare data. Even government entities like the ONC and FDA – typically not early adopters – are throwing their hat into the blockchain ring.

In fact, according to recent research by Deloitte, healthcare and life sciences companies are planning the most aggressive blockchain deployments of any industry. Thirty-five percent of Deloitte’s respondents told the consulting firm that they expected to put blockchain into production this year.

Many companies are tackling the practical uses of blockchain tech in healthcare. But to me, few are more interesting than Google’s DeepMind, a hot new AI firm based in the UK acquired by Google a few years ago.

DeepMind has already signed an agreement with a branch of Britain’s National Health Trust, under which it will access patient data in the development healthcare app named Streams. Now, it’s launching a new project in partnership with the NHS, in which it will use a new technology based on bitcoin to let hospitals, the NHS and over time, patients track what happens to personal health data.

The new technology, known as “Verifiable Data Audit,” will create a specialized digital ledger which automatically records every time someone touches patient data, according to British newspaper The Guardian.

In a blog entry, DeepMind co-founder Mustafa Suleyman notes that the system will track not only that the data was used, but also why. In addition, the ledger supporting the audit will be set to append-only, so once the system records an activity, that record can’t be erased.

The technology differs from existing blockchain models in some important ways, however. For one thing, unlike in other blockchain models, Verifiable Data Audit won’t rely on decentralized ledger verification of a broad set of participants. The developers have assumed that trusted institutions like hospitals can be relied on to verify ledger records.

Another way in which the new technology is different is that it doesn’t use a chain infrastructure. Instead, it’s using a mathematical function known as a Merkle tree. Every time the system adds an entry to the ledger, it generates a cryptographic hash summarizing not only that latest ledger entry, but also the previous ledger values.

DeepMind is also providing a dedicated online interface which participating hospitals can use to review the audit trail compiled by the system, in real-time. In the future, the company hopes to make automated queries which would “sound the alarm” if data appeared to be compromised.

Though DeepMind does expect to give patients direct oversight over how, where and why their data has been used, they don’t expect that to happen for some time, as it’s not yet clear how to secure such access. In the mean time, participating hospitals are getting a taste of the future, one in which patients will ultimate control access to their health data assets.