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On the 1st Day of #HITChristmas … Joy Rios from ChirpyBird and HIT Like a Girl Podcast

Posted on December 13, 2018 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 day as I was thinking about the holiday season, I was inspired by some people who had sent us 12 gifts to celebrate the 12 days of Christmas. I’ve always loved the 12 days of Christmas ever since someone secret santa’d our family with big boxes of 12 gifts. I’ll never forget that really nice red backpack I got that Christmas.

Inspired by that memory, I decided to celebrate the 12 Days of Christmas here at Healthcare Scene by featuring 12 amazing people in healthcare IT. I just tweeted out a request for interesting healthcare IT people, companies, initiatives, etc that deserved a Christmas gift. So, for the next 12 days, we’ll be featuring a different one each day for our #HITChristmas. We hope you enjoy this spectrum of the broad Healthcare IT Community. We have some amazing people.

On the 1st Day of #HITChristmas we’re excited to feature, Joy Rios from ChirpyBird and HIT Like a Girl Podcast.

Tell us about yourself and ChirpyBird.

I’ve been working in healthIT since 2010, first with the EHR Incentive Program and later with PQRS. Now I work mainly in the Merit-based Incentive Payment System (MIPS) domain of CMS’ Quality Payment Program. Over the years, as I have learned about each of these programs, I’ve made a real effort to share my findings in the hopes of setting healthcare professionals up for success as they transition to value-based care. I’ve created several online and in-person training programs to help others navigate MIPS. I’ve also written 3 books, outlining the changes to each year’s rules for quality reporting.

Chirpy Bird Health IT Consulting is an extension of this effort. Our mission is to accelerate the adoption of value-based care through MIPS consulting. You can read more about us here: www.chirpybirdllc.com

People often ask where we got our business name. It’s a mix of the founding partners first names, Joy and Robin, so it made us think of a happy, or chirpy bird.

What are the good and the bad parts of the MACRA/MIPS government programs?  

The good: 
I think that there’s an opportunity to drive massive, bold changes in healthcare. For example, MACRA, along with the quality reporting programs that came before it, have contributed to the mass adoption of EHR technology nationwide, and is currently using its forces to push for interoperability.

In 2019 and going forward, MIPS has been modified to better address behavioral health issues, and specifically the opioid epidemic. I’m very excited to see what impacts can be made through a national focused effort to address the healthcare industry’s part in the opioid crisis.

The bad: 
Change on the scale of the value-based-care magnitude is going to take time. The transition should be looked at like a marathon, not a sprint. And unfortunately, we are a country with a hyper-focus on short-term gains.

As we transition to a more connected digital healthcare arena, we are at risk of doing more harm than good if the time isn’t taken to consider patient safety or quality during technology implementations.

A methodical approach, with a goal for continuous improvement rather than perfection will go a long way.

Where do you think all of these government regulations are heading?  Will they continue on their current course or do you expect big changes in the future?

If I could use my crystal ball, I’d predict that the MIPS program will be around at least through 2025, and in that time the number of private insurers will continue to dwindle, likely not to a single payer model, but it may potentially come close. Value-based care is here to stay as the fee-for-service model cannot be sustained.

The biggest changes will be in interoperability, tracking outcomes, as well as in patient engagement and experience.

You also do the HIT Like a Girl Podcast. Tell us about that and your goals for the podcast.

I have been incredibly inspired by the contributions and accomplishments of women in healthcare and yet when I got to health conferences, I just don’t see as much of their work displayed or their voices heard on stage.

If I could outline the HIT Like a Girl podcast ingredients, there’s a little “being the change you want to see in the world” mixed in with “empowered women empower women,” and a touch of “start before you’re ready.”

We want to highlight the role women play in the many areas within healthcare, learn from them, and share their experiences with our listeners. We strongly feel that knowing that there are ladies out there pushing their personal and professional boundaries allows others to follow their lead.

Our goal is to amplify their efforts and accomplishments to change the narrative and recognize more openly what women are bringing to the table in the health IT arena.

If you’ve missed an episode, check out www.HITlikeaGirlpod.com.

What would you like to see happen to better help women in healthcare IT?

It’s pretty simple. We believe that it’s time to end the age of the male heavy panel or “manel,” as it is often called and that women in healthcare should be recognized for their efforts, expertise, and contributions.

There is no shortage of smart women working in health IT.

Personally, I’d like to see more women in leadership roles of large corporations.

You are one of the nicest people in the world.  Is it hard to be that nice?

LOL. Thanks for this complement. I’m a pretty positive person – my name is Joy, after all – and in general, I find that being nice takes little effort. When I smile while on the phone, I truly believe that the person on the other end can tell. Taking a kind posture has definitely helped me have more open and meaningful interactions with people and it’s quite possibly led to more opportunity.

In the sense that “it takes one to know one,” I am very grateful to work not only with smart people, but also kind ones.

What can the healthcare IT community do for you?

Great question! If you work with doctors or other MIPS eligible clinicians, talk to them about the electronic exchange of health information among their provider networks and with their patients. Encourage them to get the technical capabilities such as a Direct address (aka HISP address) in place and are using 2015 Edition certified EHR technology for the 2019 performance year .On a practical level, these are the building blocks needed to be in place for interoperability to be achieved.

Be sure to follow all of the 12 Day of #HITChristmas.

Will Chatbots Be Embedded In Health IT Infrastructure Within Five Years?

Posted on December 10, 2018 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 www.ziegerhealthcare.com.

Brace yourself: The chatbots are coming. In fact, healthcare chatbots could become an important part of healthcare organizations’ IT infrastructure, according to research released by a market analyst firm. I have my doubts but do read on and see what you think.

Jupiter Research is predicting that AI-powered chatbots will become the initial point of contact with healthcare providers for many consumers. As far as I know, this approach is not widespread in the US at present, though there are many vendors developing tools that they could deploy and we’ve seen some success from companies like SimplifiMed and big tech companies like Microsoft that are enabling chatbots as well.

However, Jupiter sees things changing rapidly over the next five years. It predicts that the number of chatbot interactions will shoot up at an average annual growth rate of 167%, from an estimated 21 million per year in 2018 to 2.8 billion per year in 2023.  By that point, healthcare will represent 10% of all chatbot interactions across major verticals, Jupiter says.

According to the market research firm, there are a number of reasons chatbot use in healthcare will grow so rapidly, including consumers’ growing comfort level with using chatbots to discuss their care. Jupiter also expects to see healthcare providers routinely use chatbots for customer experience management, though again, I’ve seen little evidence that this is happening just yet.

The massive growth in patient-chatbot interactions will also be fueled by a rise in the sophistication of conversational AI platforms, a leap so dramatic that consumers will handle a growing percentage of their healthcare business entirely via chatbot, the firm says. This, in turn, will free up medical staff time, saving countries’ healthcare systems around $3.7 billion by 2023.  This would prove to be a relatively modest savings for the giant US healthcare system, but it could be quite meaningful for a smaller country.

As healthcare organizations adopt chatbot platforms, their chief goal will be to see that information collected by chatbots is transferred to EHRs and other important applications, the report says. To make this happen, these organizations will have to make sure to integrate chatbot platforms with both clinical and line-of-business applications. (Vendors like PatientSphere already offer independent platforms designed to address such issues.)

All very interesting, no? Definitely. I share Jupiter’s optimistic view of the chatbot’s role in healthcare delivery and customer service and have little doubt that even today’s relatively primitive bots are capable of handling many routine transactions.

That being said, I’m thinking it will be more like 10 years before chatbots are used widely by providers. If what I’ve seen is any indication, it will probably take that long before conversational AI can truly hold a conversation. If we hope to use AI-based chatbots routinely at the front end of important processes, they’ll just have to be smarter.

What If You Live Tweeted an EHR Go Live?

Posted on December 3, 2018 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.

Have you ever wondered what an EHR go live is like? Ok, those of you who have been through one probably don’t want to relive that experience and may even have a little PTSD from the experience. However, as an EHR addict myself, I couldn’t resist watching the Golden Valley Memorial Healthcare (GVMH) in Clinton, MO live tweet their MEDITECH Expanse go live on the @gvmhe Twitter account.

I loved this kind of transparency and documenting of a go live. Pretty cool to see the process. The only thing I wish they would have done is used a hashtag throughout and shared it with others that were tweeting about the go live. If they had, then it would have been easier to find great tweets like this one from their CMIO Bill Dailey, MD:

I won’t share the full go live stream since you can go and read it on the @gvmhe account. However, here were some tweets that stood out.


This is an exciting and nerve wracking part of any go-live.


I’m sure the team will look back on this picture fondly. Plus, they’ll probably note all the people who were too busy to get in on the picture.


One of the best and worst parts of a go-live. The countdown clock which shows you how long until the real work begins and how much time you have left to finish your preparations. It’s always ironic that there’s always more prep that could be done, but you have to go live anyway.


You have to have a little fun during the go live.


The stress is real. Is there an ICD-10 for EHR go lives?


It’s like New Year’s, but less champagne and kissing. I like the matching shirts though.


Another stressful clock


War room in action!


The inevitable issues of getting your vendors on the phone. I wonder how effective this tweet was in helping the vendor respond. Especially since the tweet above was the 2nd one.


The moment before go live.


15 minutes later!


Don’t forget the power of food during a go live.


Must be a pretty happy Christmas gift to have the go live done and with relatively few hiccups.


The reality of the first few days.


I wonder how they measured this, but pretty interesting to consider.


Monday with a full day of patients. Congrats GVMH!

I left off a number of things, so go and check out the full @gvmhe Twitter feed. Plus, you can follow along to see how the first few weeks on MEDITECH Expanse goes for them. I hope they keep tweeting once all the go live staff leave. That’s usually a challenging time as well.

Next Steps In Making Healthcare AI Practical

Posted on November 30, 2018 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 www.ziegerhealthcare.com.

In recent times, AI has joined blockchain on the list of technologies that just sort of crept into the health IT toolkit.

After all, blockchain was borne out of the development of bitcoin, and not so long ago the idea that it was good for anything else wasn’t out there. I doubt its creators ever contemplated using it for secure medical data exchange, though the notion seems obvious in retrospect.

And until fairly recently, artificial intelligence was largely a plaything for advanced computing researchers. I’m sure some AI researchers gave thought to cyborg doctors that could diagnose patients while beating them at chess and serving them lunch, but few practical applications existed.

Today, blockchain is at the core of countless health IT initiatives, many by vendors but an increasing number by providers as well. Healthcare AI projects, for their part, seem likely to represent the next wave of “new stuff” adoption. It’s at the stage blockchain was a year or two ago.

Before AI becomes more widely adopted in healthcare circles, though, the industry needs to tackle some practical issues with AI, and the list of “to-dos” keeps expanding. Only a few months ago, I wrote an item citing a few obstacles to healthcare AI deployment, which included:

  • The need to make sure clinicians understand how the AI draws its conclusions
  • Integrating AI applications with existing clinical workflow
  • Selecting, cleaning and normalizing healthcare data used to “train” the AI

Since then, other tough challenges to the use of healthcare AI have emerged as the healthcare leaders think things over, such as:

Agreeing on best practices

Sure, hospitals would be interested in rolling out machine learning if they could, say, decrease the length of hospital stays for pneumonia and save millions. The thing is, how would they get going? At present, there’s no real playbook as to how these kinds of applications should be conceptualized, developed and maintained. Until healthcare leaders reach a consensus position on how healthcare AI projects should generally work, such projects may be too risky and/or prohibitively expensive for providers to consider.

Identifying use cases

As an editor, I see a few interesting healthcare AI case studies trickle into my email inbox every week, which keeps me intrigued. The thing is, if I were a healthcare CIO this probably wouldn’t be enough information to help me decide whether it’s time to take up the healthcare AI torch. Until we’ve identified some solid use cases for healthcare AI, almost anything providers do with it is likely to be highly experimental. Yes, there are some organizations that can afford to research new tech but many just don’t have the staff or resources to invest. Until some well-documented standard use cases for healthcare AI emerge, they’re likely to hang back.

The healthcare AI discussion is clearly at a relatively early stage, and more obstacles are likely to show up as providers grapple with the technology. In the meantime, getting these handled is certainly enough of a challenge.

Less Than Half of Healthcare Users Trust Critical Organizational Data

Posted on November 29, 2018 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 www.ziegerhealthcare.com.

If you’re a healthcare CIO, you must hope that your users trust and feel they can leverage data to do their jobs better. However, some of your colleagues don’t seem to be so sure. A new study has concluded that less than half of users in responding healthcare organizations have a high degree of trust in their clinical, operational or financial data.

The study, which was conducted by Dimensional Insight, surveyed 85 chief information officers and other senior health IT leaders. It asked these leaders how they rated trust in the data leveraged by their various user communities, the percentage of user population they felt was self-service oriented and making data-driven decisions, and whether they planned to increase or decrease their investments in data trust and self-service analytics.

When rating the level of data trust on a 10-point scale, just 40% of respondents rated their trust in financial data at eight or above, followed by 40% of clinical data users and 36% of operational data users.

Perhaps, then, it follows that healthcare organizations responding to the survey had low levels of self-service data use. Clinical data users had a particularly low rate of self-service use, while financial users seemed fairly likely to be accessing and using data independently.

Given these low levels of trust and self-service data usage, it’s not surprising to find out that 76% of respondents said they plan to invest in increasing their investment in improving clinical data trust, 77% their investments in improving operational data trust and 70%  their investment in financial data trust.

Also, 78% said they plan to increase their spending on self-service analytics for clinical data and 73% expect to spend more on self-service analytics for operational data. Meanwhile, while 68% plan to increase spending on financial self-service analytics, 2% actually planned to decrease the spending in this area, suggesting that this category is perhaps a bit healthier.

In summing up, the report included recommendations on creating more trust in organizational data from George Dealy, Dimensional Insight’s vice president of healthcare applications. Dealy’s suggestions include making sure that subject matter experts help to design systems providing information critical to their decision-making process, especially when it comes to clinicians. He also points out that health IT leaders could benefit from keeping key users aware of what data exists and making it easy for them to access it.

Unfortunately, there are still far too many data silos protected by jealous guardians in one department or another. While subject matter experts can design the ideal data sharing platform for their needs, there’s still a lot of control issues to address before everyone gets what they need. In other words, increasing trust is well and good, but the real task is seeing to it that the data is rich and robust when users get it.

AI May Be Less Skilled At Analyzing Images From Outside Organizations

Posted on November 26, 2018 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 www.ziegerhealthcare.com.

Using AI technologies to analyze medical images is looking more and more promising by the day. However, new research suggests that when AI tools have to cope with images from multiple health systems, they have a harder time than when they stick to just one.

According to a new study published in PLOS Medicine, interest is growing in analyzing medical images using convolutional neural networks, a class of deep neural networks often dedicated to this purpose. To date, CNNs have made progress in analyzing X-rays to diagnose disease, but it’s not clear whether CNNs trained on X-rays from one hospital or system will work just as well in other hospitals and health systems.

To look into this issue, the authors trained pneumonia screening CNNs on 158,323 chest X-rays, including 112,120 X-rays from the NIH Clinical Center, 42,396 X-rays from Mount Sinai Hospital and 3,807 images from the Indiana University Network for Patient Care.

In their analysis, the researchers examined the effect of pooling data from sites with a different prevalence of pneumonia. One of their key findings was that when two training data sites had the same pneumonia prevalence, the CNNs performed consistently, but when a 10-fold different in pneumonia rates were introduced between sites, their performance diverged. In that instance, the CNN performed better on internal data than that supplied by an external organization.

The research team found that in 3 out of 5 natural comparisons, the CNNs’ performance on chest X-rays from outside hospitals was significantly lower than on held-out X-rays from the original hospital system. This may point to future problems when health systems try to use AI for imaging on partners’ data. This is not great to learn given the benefits AI-supported diagnosis might offer across, say, an ACO.

On the other hand, it’s worth noting that the CNNs were able to determine which organization originally created the images at an extremely high rate of accuracy and calibrate its diagnostic predictions accurately. In other words, it sounds as though over time, CNNs might be able to adjust to different sets of data on the fly. (The researchers didn’t dig into how this might affect their computing performance.)

Of course, it’s possible that we’ll develop a method for normalizing imaging data that works in the age of AI, in which case the need to adjust for different data attributes may not be needed.  However, we’re at the very early stages of training AIs for image sharing, so it’s anyone’s guess as to what form that normalization will take.

Sharing Records with Patients is the Right Thing to Do – OpenNotes

Posted on November 21, 2018 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’ve been a big fan of the OpenNotes effort for a long time. While I’ve heard every excuse in the business for why patients shouldn’t have access to their chart, all of those reasons have fallen flat. Much of that is thanks to the good work of the people at OpenNotes.

If your organization has not embraced opening up your chart notes to patients, what’s holding you back? The case for opening your notes to patients is clear.

If you want a more humorous look at this, check out this video featuring e-Patient Dave and clip’s from Seinfeld.

I’m not sure how I missed this video when it first came out, but it’s timeless. Plus, there’s no one better to share this message than e-Patient Dave whose life was literally saved because he demanded access to his chart.

No doubt, a lot of things have changed in the 20 years since the above episode aired. One of those things is patients desire to access their chart and technology’s ability to deliver the chart to the patient at basically no cost.

If your organization hasn’t embraced OpenNotes, I encourage you all to do so now. They can answer all your questions and address all your doubts. Join the Movement and improve the care you provide patients.

Apple Health, Opioid Challenge, Safety Risk Heat Maps, and athenahealth Acquisition

Posted on November 20, 2018 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.

We’re back again with a quick roll around Twitter in a round up of some of the interesting tweets we’ve seen shared. This was quite a diverse set of tweets, so I think there will be something of interest for everyone in this Twitter Round Up.


This tweet is a little annoying for me. I know Matthew has the best of intentions, but there’s no way I’d call and ask my provider or hospital to take part in this. I’m an Android user. This type of access does nothing for me. Apple users seem to forget that. Plus, it’s worth mentioning that there are more Android users out there than Apple users. It’s great that Apple is doing this, but it’s not the game changing thing that so many make it out to be.


Numbers like this always take me back. I just have to keep reminding myself that the opioid crisis wasn’t created over night and it won’t be fixed over night either.


Love this type of collaboration and creativity. One of the big things missing in healthcare is getting doctors off the reimbursement treadmill so they can take part in these types of creative activities. Also, a heat map of patient safety risk is pretty interesting to consider.


No doubt, we’ll hear a lot more about this acquisition in the future. As soon as Jonathan Bush was out as CEO, this company and people’s perception of this company changed. He was the heart and soul of the company and it’s going to be much different going forward. As far as the hospital piece of this tweet. I’ll be really interested to see if private equity is brave enough to continue Jonathan Bush’s ambitious hospital EHR strategy. I won’t be surprised if they pull the plug on it, but time will tell.

What’s the Future of Open Source EHR, Vista?

Posted on November 19, 2018 I Written By

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

I was going through some old draft posts (as I mentioned yesterday) and found a post that was started by Nate DiNiro which said “Will the VA and DoD help tip the scales on VistA adoption with OSEHRA?” Granted, this post was first started back in 2011. It’s amazing how much has changed since then.

We all know about the DoD’s selection of Cerner and Leidos to replace their EHR. In a more surprising move was the VA’s decision to sole-source their EHR selection of Cerner based on the idea that it was essential they go with Cerner after the DoD selected Cerner. Certainly a topic for another blog post.

We’ve certainly heard many complaints from those in the VA community that are going to have a really hard time giving up Vista which was basically tailored for many of their unique needs. However, there seems to be nothing stopping that ship now.

Given these events, it brings up an interesting question about the future of Vista as the VA replaces their version of Vista with Cerner. The good news for those healthcare organizations on Vista is that it’s now open source. So, the software can persist as long as there is a community of developers behind it. The core question is how much of Vista’s ongoing development came from the VA versus the community.

The two players I’ve seen using the open source Vista EHR platform are MedSphere and WorldVista. I’ll admit that I haven’t seen too much news from either of them lately, but they both seem to be humming along.

I took a look at the ONC’s latest Health IT Dashboard stats for hospitals. In 2017 (their latest data), it reported 11 “providers with certified technology” for Medsphere and 1 for WorldVistA. Of course, this is just those who have taken part in the meaningful use government program. It’s reasonable to assume that some open source EHR customers probably didn’t want to take part in meaningful use. Plus, these numbers don’t include international Vista installs which obviously can’t take part in meaningful use.

Given these numbers and the VA pulling Vista out, I have a feeling it’s going to be a hard road ahead for Vista.

I’ll never forget when it was first announced that the VA was open sourcing Vista and that anyone that wanted a free EHR could have it. What was amazing is that the HIM manager I was working with found an article talking about this announcement and brought it to me. She wondered why we were paying for an EHR if Vista was available for free. It gave me a chance to explain to her that “free software” doesn’t mean it’s free to implement and manage. Not to mention the fact that this was a small ambulatory clinic that was likely not a good fit for the hospital focused Vista software.

What have you heard or seen with Vista? Has more been happening with the open source versions of Vista that I just haven’t seen? As a big open source user myself (my blogs run on pretty much all open source software), I’d love to see an open source EHR succeed. Unfortunately, it just hasn’t seen near the adoption it needs to really create that momentum yet.

Interoperability Problems Undercut Conclusions of CHIME Most Wired Survey

Posted on November 13, 2018 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 www.ziegerhealthcare.com.

Most of you have probably already seen the topline results from CHIME’s  “Healthcare’s Most Wired: National Trends 2018” study, which was released last month.

Some of the more interesting numbers coming out of the survey, at least for me, included the following:

  • Just 60% of responding physicians could access a hospital network’s virtual patient visit technology from outside its network, which kinda defeats the purpose of decentralizing care delivery.
  • The number of clinical alerts sent from a surveillance system integrated with an EHR topped out at 58% (alerts to critical care units), with 35% of respondents reporting that they had no surveillance system in place. This seems like quite a lost opportunity.
  • Virtually all (94%) participating organizations said that their organization’s EHR could consume discrete data, and 64% said they could incorporate CCDs and CCRs from physician-office EHRs as discrete data.

What really stands out for me, though, is that if CHIME’s overall analysis is correct, many aspects of our data analytics and patient engagement progress still hang in the balance.

Perhaps by design, the hospital industry comes out looking like it’s doing well in most of the technology strategy areas that it has questions about in the survey, but leaves out some important areas of weakness.

Specifically, in the introduction to its survey report, the group lists “integration and interoperability” as one of two groups of foundational technologies that must be in place before population health management/value-based care,  patient engagement and telehealth programs can proceed.

If that’s true, and it probably is, it throws up a red flag, which is probably why the report glossed over the fact that overall interoperability between hospitals is still very much in question. (If nothing else, it’s high time the hospitals adjust their interoperability expectations.) While it did cite numbers regarding what can be done with CCDs, it didn’t address the much bigger problems the industry faces in sharing data more fluidly.

Look, I don’t mean to be too literal here. Even if CHIME didn’t say so specifically, hospitals and health systems can make some progress on population health, patient engagement, and telehealth strategies even if they’re forced to stick to using their own internal data. Failing to establish fluid health data sharing between facility A and facility B may lead to less-than-ideal results, but it doesn’t stop either of them from marching towards goals like PHM or value-based care individually.

On the other hand, there certainly is an extent to which a lack of interoperability drags down the quality of our results. Perhaps the data sets we have are good enough even if they’re incomplete, but I think we’ve already got a pretty good sense that no amount of CCD exchange will get the results we ultimately hope to see. In other words, I’m suggesting that we take the CHIME survey’s data points in context.