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Is Your Current Analytics Infrastructure Keeping You From Success in Healthcare Analytics?

Posted on February 17, 2017 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.

The following is a paid blog post sponsored by Intel.

Healthcare analytics is all the talk in healthcare right now.  It’s really no surprise since many have invested millions and even billions of dollars in digitizing their health data.  Now they want to extract value from that data.  No doubt, the promise of healthcare analytics is powerful.  I like to break this promise out into two categories: Patient Analysis and Patient Influence.

Patient Analysis

On the one side of healthcare analytics is analyzing your patient population to pull reports on patients who need extra attention.  In some cases, these patients are the most at risk portions of your population with easy to identify disease states.  In other cases, they’re the most expensive portion of your population.  Both of these are extremely powerful analytics as your healthcare organization works to improve patient care and lower costs.

An even higher level of patient analysis is using healthcare analytics to identify patients who don’t seem to be at risk, but whose health is in danger.  These predictive analytics are much more difficult to create because by their very nature they’re imperfect.  However, this is where the next generation of patient analysis is going very quickly.

Patient Influence

On the other side of healthcare analytics is using patient data to influence patients.  Patient influence analytics can tell you simple things like what type of communication modality is preferred by a patient.  This can be used on an individual level to understand whether you should send an email, text, or make a phone call or it can be used on the macro level to drive the type of technologies you buy and content you create.

Higher level patient influence analytics take it one step further as they analyze a patient’s unique preferences and what influences the patient’s healthcare decision making.  This often includes pulling in outside consumer data that helps you understand and build a relationship with the patient.  This analytic might tell you that the patient is a huge sports fan and which is their favorite team.  It might also tell you that this person has a type A personality.  Together these analytics can inform you on the most appropriate ways and methods to interact and influence the patient.

What’s Holding Healthcare Analytics Back?

Both of these healthcare analytics approaches have tremendous promise, but many of them are being held back by a healthcare organization’s current analytics infrastructure.

The first problem many organizations have is where they are storing their data.  I’d describe their data as being stored in virtual prisons.  We need to unlock this data and free it so that it can be used in healthcare analytics.  If you can’t get at the data within your own organization, how can we even start talking about all the health data being stored outside the four walls of your organization?  Plus, we need to invest in the right storage that can support the growth of this data.  If you don’t solve these data access and storage pieces, you’ll miss out on a lot of the benefits of healthcare analytics.

Second, do you trust your data?  Most hospital CIOs I talk to usually respond, “Mostly.”  If you can’t trust your data, you can’t trust your analytics.  A fundamental building block of successful analytics is building trust in your data.  This starts by implementing effective workflows that capture the data properly on the front end.

Next, do you have the processing power required to process all these analytics and data?  Healthcare analytics in many healthcare organizations reminds me of the old days when graphic designers and video producers would have to wait hours for graphics programs to load or videos to render.  Eventually we learned not to skimp on processing power for these tasks.  We need to learn this same lesson with healthcare analytics.  Certainly cloud makes this easier, but far too often we under fund the processing power needed for these projects.

Finally, all the processing power in the world won’t help if you don’t have your most important piece of analytics infrastructure: people.  No doubt, finding experienced people in healthcare data analytics is a challenge.  It is the hardest thing to do on this list since it is very competitive and very expensive.  The good news is that if you solve the other problems above, then you become an attractive place for these experts to work.

In your search for a healthcare analytics expert, you can likely find a data expert.  You can find a clinical expert.  You can find an EHR expert.  Finding someone who can work across all three is the Holy Grail and nearly impossible to find.  This is why in most organizations healthcare analytics is a team sport.  Make sure that as you build your infrastructure of healthcare analytics people, you make sure they are solid team players.

It’s time we start getting more value out of our EHR and health IT systems.  Analytics is one of those tools that will get us there.  Just be sure that your current infrastructure isn’t holding you back from achieving those goals.

If this topic interests you and you’ll be at HIMSS 2017, join us at the Intel Health Booth #2661 on Tuesday, 2/21 from 2:00-2:45 PM where we’ll be holding a special meetup to discuss Getting Ready for Precision Health.  This meetup will also be available virtually via Periscope on the @IntelHealth Twitter account.

Many Providers Still Struggle With Basic Data Sharing

Posted on February 15, 2017 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.

One might assume that by this point, virtually every provider with a shred of IT in place is doing some form of patient data exchange. After all, many studies tout the number of healthcare data send and receive transactions a given vendor network or HIE has seen, and it sure sounds like a lot. But if a new survey is any indication, such assumptions are wrong.

According a study by Black Book Research, which surveyed 3,391 current hospital EMR users, 41% of responding medical record administrators find it hard to exchange patient health records with other providers, especially if the physicians involved aren’t on their EMR platform. Worse, 25% said they still can’t use any patient information that comes in from outside sources.

The problem isn’t a lack of interest in data sharing. In fact, Black Book found that 81% of network physicians hoped that their key health system partners’ EMR would provide interoperability among the providers in the system. Moreover, the respondents say they’re looking forward to working on initiatives that depend on shared patient data, such as value-based payment, population health and precision medicine.

The problem, as we all know, is that most hospitals are at an impasse and can’t find ways to make interoperability happen. According to the survey, 70% of hospitals that responded weren’t using information outside of their EMR.  Respondents told Black Book that they aren’t connecting clinicians because external provider data won’t integrate with their EMR’s workflow.

Even if the data flows are connected, that may not be enough. Researchers found that 22% of surveyed medical record administrators felt that transferred patient information wasn’t presented in a useful format. Meanwhile, 21% of hospital-based physicians contended that shared data couldn’t be trusted as accurate when it was transmitted between different systems.

Meanwhile, the survey found, technology issues may be a key breaking point for independent physicians, many of whom fear that they can’t make it on their own anymore.  Black Book found that 63% of independent docs are now mulling a merger with a big healthcare delivery system to both boost their tech capabilities and improve their revenue cycle results. Once they have the funds from an acquisition, they’re cleaning house; the survey found that EMR replacement activities climbed 52% in 2017 for acquired physician practices.

Time for a comment here. I wish I agreed with medical practice leaders that being acquired by a major health system would solve all of their technical problems. But I don’t, really. While being acquired may give them an early leg up, allowing them to dump their arguably flawed EMR, I’d wager that they won’t have the attention of senior IT people for long.

My sense is that hospital and health system leaders are focused externally rather than internally. Most of the big threats and opportunities – like ACO integration – are coming at leaders from the outside.

True, if a practice is a valuable ally, but independent of the health system, CIOs and VPs may spend lots of time and money to link arms with them technically. But once they get in house, it’s more of a “get in line” situation from what I’ve seen.  Readers, what is your experience?

Hospital EMR and EHR Milestone – 1 Million Pageviews

Posted on February 13, 2017 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 just looking over the stats for Hospital EMR and EHR and noticed that were right at 1 million pageviews for this site. That’s a pretty amazing accomplishment for such a niche site. Especially since we’ve moved a lot of the traffic off of the site and onto our email list. Looks like this will make the 1111th blog post for Hospital EMR and EHR and it has 25,293 email subscribers (Subscribe Here) to the content we generate on this site. That’s a really amazing thing since we email those on the list 3-5 times per week. Hospital EMR and EHR has become a really important part of Healthcare Scene and we’re happy to contribute to the hospital healthcare IT industry at large.

On this milestone, we want to thank some of our recent sponsors that have made what we do possible. If you enjoy reading our content, please take a second to look through our sponsors to see if one of them can help make your life easier.

Stericycle Communication Solutions – Stericycle has been a long time sponsor of multiple Healthcare Scene blogs. Plus, they have written the Communication Solutions Series of blog posts which are an excellent read if you’re interested in strategies for healthcare engagement. They also have a free guide that addresses the question Patient or Consumer? This is a great company that’s really working to make the patient experience better.

Galen Healthcare Solutions – We’ve had the chance to work with Galen Healthcare Solutions across a number of different mediums including email, display ads, and sponsored content. You’ve probably read their Tackling EHR and EMR Transition series where they’ve shared a lot of great insights into how your organization should handle archiving old legacy data and also how you can migrate data from one EHR to a new EHR. Both of these topics are going to become increasingly important and Galen Healthcare Solutions have become real experts. Be sure to check out their Free Data Archive whitepaper and their Free EHR Migration whitepaper.

Medical Software Advice (A Gartner Company) – I’ve been working with Medical Software Advice for a very long time. They’ve provided a really great service to my readers around EHR selection. With 300+ EHR vendors out there, it can be hard to cut through the various options. Medical Software Advice has helped out hundreds of companies with their EHR selection including setting up EHR demos and getting EHR pricing. Check out their Top 5 EHR Software list.

4Med – 4Med is another partner that we’ve worked with for a very long time. They’ve consistently offered some great educational content (include CEUs) for the healthcare IT professional. Here are some of their upcoming courses that are great examples: HIPAA Compliance Officer, Patient Centered Medical Home Project Manager, and ACI MACRA-MIPA Project Manager. Each of those links gives you a discount off the regular registration price.

HIPAAOne – HIPAA compliance has always been essential to healthcare, but meaningful use and now MACRA have made the HIPAA Risk Assessment a priority for many organizations. What’s shocking to me is how many organizations haven’t done a proper HIPAA Risk assessment. HIPAA One has created a really great software solution to automate your HIPAA Risk Assessment. I like to call them the Tax Act or H&R Block software for HIPAA compliance. If you’ve got a stack of Excel spreadsheets managing your HIPAA Risk Assessment, take a second to look at how HIPAAOne can make your job easier. Also, they have a great 5 min HIPAA compliance quiz to assess some of key HIPAA compliance areas.

We’re also excited to announce our new Healthcare Scene media kit. It’s been amazing to see the evolution of what we’re able to offer healthcare IT vendors. We really want to develop deep relationships with our advertisers and not just take their money and run. We think that’s the best thing for both our readers and our advertisers. If you’re trying to get the word out to the hospital market, let us how we can help on our contact us page.

I couldn’t finish this post without saying a massive thank you to our readers. It’s hard to know exactly what kind of impact you’re having when you blog. However, every once in a while you get a glimpse into the benefit your blog posts are providing readers and that makes it all worthwhile. Thank you to each of you who read and support our work.

Now, on to the next million pageviews!

When Healthcare IT Isn’t Enough

Posted on February 10, 2017 I Written By

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

This week I’ve gone through close to 200 pitches from companies who want to meet with me at the HIMSS Annual conference. While I can’t say that this is a fun task (especially since I have to tell 95% of them no), it is an educational experience to see what 200 companies are sharing as we head into the biggest healthcare IT conference in the world.

If I were to summarize the pitches in general, I would describe them as incremental. I’ll admit that this is a pretty disappointing perspective since we all know that healthcare needs something transformational. Don’t get me wrong. I believe that regular incremental improvement is transformational, but I’d say that most of the pitches lacked ambition.

Along with this observation is the idea that in most cases technology isn’t enough. If it were enough, EHR software that’s in use in most of healthcare would have already transformed the industry. The longer I spend in this industry, the more I realize that technology is just a tool in the tool belt. The real transformation comes from something more than technology. Technology might be a catalyst or facilitator, but that’s all.

This is actually a theme that really began at last year’s HIMSS conference. The areas that excite me most are those that literally change behavior. This might be the patient’s behavior or it might be the clinician’s behavior. It might also be the payer, health system, or government’s behavior.

The challenge is that changing behavior is hard. Slapping an EMR system is easy compared to behavior change. Implementing a secure text message solution is easy compared to behavior change. Rolling out an enterprise data warehouse is easy compared to behavior change.

At HIMSS and throughout the year I’m most interested on those companies who understand not only the technology side of things, but the behavior side of things as well.

If you’re interested in healthcare transformation and what it requires, join us at the Digital Transformation Meetup at HIMSS17. It’s happening Tuesday, 2/21 from 11:30-12:30 at the Dell EMC Booth #3161. More details on this meetup and other HIMSS17 meetups can be found here.

Suggestions and Tips for Hospital IT Professionals at #HIMSS17

Posted on February 8, 2017 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.

Hard to believe that the 2017 HIMSS Annual Conference is less than a week and a half away. For someone who eats, breathes, and sleeps Health IT, HIMSS is like winning the golden ticket to visit Willy Wonka’s chocolate factory. However, for a lot of hospital IT professionals, it might be their first time attending HIMSS and it can be quite overwhelming. 40,000-50,000 attendees and approximately 1300 exhibitors should be overwhelming.

While I’m certainly not a HIMSS veteran like many people, I’ve learned a number of important tips and tricks that will help you get the most out of HIMSS. Hopefully some of these will help you have a better HIMSS experience.

Standard Conference Answers – Instead of listing these individually, I’ll list them all in one since they’re true for any conference and their reasons should be now apparent. Wear comfortable shoes. Drink lots of water. Plan for good meals. Bring a battery pack or charge whenever possible. Expect bad internet. Have fun.

CHIME-HIMSS CIO Forum – As a hospital IT professional, the CHIME-HIMSS CIO Forum on Saturday and Sunday before HIMSS is excellent. They put together a great program of speakers, but more importantly you get the chance to network with 1000 or so of people like you. Don’t miss it if you come from the hospital IT world.

People – This one is obvious once you think about it, but is often missed by attendees. The people you hang out with at a conference will make all the difference. If you hang out with smart, well connected people, you’ll meet a bunch of other smart, well connected people and you’ll have a great experience. If you feel you don’t know anyone good to hang out with, hit social media and start interacting with people you find interesting. Friendships will develop quickly if you put in a little effort. Who you spend time with can transform your HIMSS experience for good or bad.

Plan for Serendipity – Everyone likes to suggest that the key to HIMSS is to have a plan. Considering the volume of sessions and exhibitors, a plan is good. However, don’t forget to plan in time for serendipitous interactions. Maybe that’s putting a party on your schedule that will broaden your horizon. Maybe that’s putting some down time on your schedule to sit at a table and connect with some random strangers. Maybe that’s some time trolling the exhibit hall to meet new people and companies that will provide you new perspectives. My favorite experience at HIMSS16 was a random dinner that came together after meeting someone at an impromptu meetup.

Don’t Be a Wallflower, Engage with Others – It’s easy to go to a conference and spend your entire time listening to sessions and exhibitor presentations and pitches. While this is valuable, you’ll have a deeper, more engaging experience at HIMSS17 if you engage with the people around you. Yes, I’m suggesting you go beyond just the usual casual platitudes of where you work and where you’re from. If this scares you or you don’t know how to get started, join us at a #HIMSS17 meetup where everyone is there to do just that. Education is valuable, but engagement is priceless.

Those are a few of my tips for #HIMSS17. What tips would you add to the list?

An Approach For Privacy – Protecting Big Data

Posted on February 6, 2017 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.

There’s little doubt that the healthcare industry is zeroing in on some important discoveries as providers and researchers mine collections of clinical and research data. Big data does come with some risks, however, with some observers fearing that aggregated and shared information may breach patient privacy. However, at least one study suggests that patients can be protected without interrupting data collection.

In what it calls a first, a new study appearing in the Journal of the American Medical Informatics Association has demonstrated that protecting the privacy of patients can be done without too much fuss, even when the patient data is pulled into big data stores used for research.

According to the study, a single patient anonymization algorithm can offer a standard level of privacy protection across multiple institutions, even when they are sharing clinical data back and forth. Researchers say that larger clinical datasets can protect patient anonymity without generalizing or suppressing data in a manner which would undermine its use.

To conduct the study, researchers set a privacy adversary out to beat the system. This adversary, who had collected patient diagnoses from a single unspecified clinic visit, was asked to match them to a record in a de-identified research dataset known to include the patient. To conduct the study, researchers used data from Vanderbilt University Medical Center, Northwestern Memorial Hospital in Chicago and Marshfield Clinic.

The researchers knew that according to prior studies, the more data associated with each de-identified record, and the more complex and diverse the patient’s problems, the more likely it was that their information would stick out from the crowd. And that would typically force managers to generalize or suppress data to protect patient anonymity.

In this case, the team hoped to find out how much generalization and suppression would be necessary to protect identities found within the three institutions’ data, and after, whether the protected data would ultimately be of any use to future researchers.

The team processed relatively small datasets from each institution representing patients in a multi-site genotype-disease association study; larger datasets to represent patients in the three institutions’ bank of de-identified DNA samples; and large sets which stood in for each’s EMR population.

Using the algorithm they developed, the team found that most of the data’s value was preserved despite the occasional need for generalization and suppression. On average, 12.8% of diagnosis codes needed generalization; the medium-sized biobank models saw only 4% of codes needing generalization; and among the large databases representing EMR populations, only 0.4% needed generalization and no codes required suppression.

More work like this is clearly needed as the demand for large-scale clinical, genomic and transactional datasets grows. But in the meantime, this seems to be good news for budding big data research efforts.

Boston Children’s Benefits From the Carequality and CommonWell Agreement

Posted on February 3, 2017 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.

Recently two of the bigger players working on health data interoperability – Carequality and the CommonWell Health Alliance – agreed to share data with each other. The two, which were fierce competitors, agreed that CommonWell would share data with any Carequality participant, and that Carequality users would be able to use the CommonWell record locator service.

That is all well and good, but at first I wasn’t sure if it would pan out. Being the cranky skeptic that I am, I assumed it would take quite a while for the two to get their act together, and that we’d hear little more of their agreement for a year or two.

But apparently, I was wrong. In fact, a story by Scott Mace of HealthLeaders suggests that Boston Children’s Hospital and its physicians are likely to benefit right away. According to the story, the hospital and its affiliated Pediatric Physicians Organization at Children’s Hospital (PPOC) will be able to swap data nicely despite their using different EMRs.

According to Mace, Boston Children’s runs a Cerner EMR, as well as an Epic installation to manage its revenue cycle. Meanwhile, PPOC is going live with Epic across its 80 practices and 400 providers. On the surface, the mix doesn’t sound too promising.

To add even more challenges to the mix, Boston Children’s also expects an exponential jump in the number of patients it will be caring for via its Medicaid ACO, the article notes.

Without some form of data sharing compatibility, the hospital and practice would have faced huge challenges, but now it has an option. Boston Children’s is joining CommonWell, and PPOC is joining Carequality, solving a problem the two have struggled with for a long time, Mace writes.

Previously, the story notes, the hospital tried unsuccessfully to work with a local HIE, the Mass Health Information HIway. According to hospital CIO Dan Nigrin, MD, who spoke with Mace, providers using Mass Health were usually asked to push patient data to their peers via Direct protocol, rather than pull data from other providers when they needed it.

Under the new regime, however, providers will have much more extensive access to data. Also, the two entities will face fewer data-sharing hassles, such as establishing point-to-point or bilateral exchange agreements with other providers, PPOC CIO Nael Hafez told HealthLeaders.

Even this step upwards does not perfect interoperability make. According to Micky Tripathi, president and CEO of the Massachusetts eHealth Collaborative, providers leveraging the CommonWell/Carequality data will probably customize their experience. He contends that even those who are big fans of the joint network may add, for example, additional record locator services such as one provided by Surescripts. But it does seem that Boston Children’s and PPOC are, well, pretty psyched to get started with data sharing as is.

Now, back to me as Queen Grump again. I have to admit that Mace paints a pretty attractive picture here, and I wish Boston Children’s and PPOC much success. But my guess is that there will still be plenty of difficult issues to work out before they have even the basic interoperability they’re after. Regardless, some hope of data sharing is better than none at all. Let’s just hope this new data sharing agreement between CommonWell and Carequality lives up to its billing.

Health IT Preserves Idaho Hospital’s Independence

Posted on February 1, 2017 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.

Most of the time, when I write about hospital IT adoption, I end up explaining why a well-capitalized organization is going into the red to implement its EMR. But I recently found a story in RevCycle Intelligence in which a struggling hospital actually seems to have benefitted financially from investing in IT infrastructure. According to the story, a 14-bed critical access hospital in Idaho recently managed to stave off a forced merger or even closure by rolling out an updated EMR and current revenue cycle management technology.

Only a few years ago, Arco, Idaho-based Lost Rivers Medical Center was facing serious financial hurdles, and its technology was very outdated. In particular, it was using an EMR from 1993, which was proving so inflexible that the claims stayed in accounts receivable for an average of 108 days. “We didn’t have wifi,” CEO Brad Huerta told the site. “We didn’t have fiber. We literally had copper wires for our phone system…we had an EMR in a technical sense, but nobody was using it. It was a proverbial paperweight.”

Not only was the cost of paying for upgrades daunting, the hospital’s location was as well. Arco is a “frontier” location, making it hard to recruit IT staffers to implement and maintain infrastructure, staff and servers, the story notes. Though “fiercely independent,” as Huerta put it, it was getting hard for Lost Rivers to succeed without merging with a larger organization.

That being said, Huerta and his team decided to stick it out. They feared diluting their impact, or losing the ability to offer services like trauma care and tele-pharmacy, if they were to merge with a bigger organization.

Instead of conceding defeat, Huerta decided to focus on improving the hospital’s revenue cycle performance, which would call for installing an up-to-date EMR and more advanced medical billing tools. After the hospital finished putting in fiber in its area, Lost Rivers invested in athenahealth’s cloud-based EMR and medical billing tools.

Once the hospital put its new systems in place, it was able to turn things around on the revenue cycle front. Total cash flow climbed rapidly, and days in accounts receivable fell from 108 to 52 days.

According to Huerta, part of the reason the hospital was able to make such significant improvements was that the new systems improved workflow. In the past, he told RevCycle Intelligence, providers and staff often failed to code services correctly or bill patients appropriately, which led to financial losses.

Now, doctors chart on laptops, tablets or even phones while at the patients’ bedside. Not only did this improve coding accuracy, it cut down on the amount of time doctors spend in administrative work, giving them time to generate revenue by seeing additional patients.

What’s more, the new system has given Lost Rivers access to some of the advantages of merging with other facilities without having to actually do so. According to the story, the system now connects the critical access hospital with larger health systems, as the athenahealth system captures rule changes made by the other organization and effectively shares the improvements with Lost Rivers. This means the coding proposed by the system gradually gets more accurate, without forcing Lost Rivers to spend big bucks on coding training, Huertas said.

While the story doesn’t say so specifically, I’m sure that Lost Rivers is spending a lot on its spiffy new EMR and billing tech, which must have been painful at least at first. But it’s always good to see the gamble pay off.

UCSF Partners With Intel On Deep Learning Analytics For Health

Posted on January 30, 2017 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.

UC San Francisco’s Center for Digital Health Innovation has agreed to work with Intel to deploy and validate a deep learning analytics platform. The new platform is designed to help clinicians make better treatment decisions, predict patient outcomes and respond quickly in acute situations.

The Center’s existing projects include CareWeb, a team-based collaborative care platform built on Salesforce.com social and mobile communications tech; Tidepool, which is building infrastructure for next-gen smart diabetes management apps; Health eHeart, a clinical trials platform using social media, mobile and realtime sensors to change heart disease treatment; and Trinity, which offers “precision team care” by integrating patient data with evidence and multi-disciplinary data.

These projects seem to be a good fit with Intel’s healthcare efforts, which are aimed at helping providers succeed at distributed care communication across desktop and mobile platforms.

As the two note in their joint press release, creating a deep learning platform for healthcare is extremely challenging, given that the relevant data is complex and stored in multiple incompatible systems. Intel and USCF say the next-generation platform will address these issues, allowing them to integrate not only data collected during clinical care but also inputs from genomic sequencing, monitors, sensors and wearables.

To support all of this activity obviously calls for a lot of computing power. The partners will run deep learning use cases in a distributed fashion based on a CPU-based cluster designed to crunch through very large datasets handily. Intel is rolling out the computing environment on its Xeon processor-based platform, which support data management and the algorithm development lifecycle.

As the deployment moves forward, Intel leaders plan to study how deep learning analytics and machine-driven workflows can optimize clinical care and patient outcomes, and leverage what they learn when they create new platforms for the healthcare industry. Both partners believe that this model will scale for future use case needs, such as larger convolutional neural network models, artificial networks patterned after living organizations and very large multidimensional datasets.

Once implemented, the platform will allow users to conduct advanced analytics on all of this disparate data, using machine learning and deep learning algorithms. And if all performs as expected, clinicians should be able to draw on these advanced capabilities on the fly.

This looks like a productive collaboration. If nothing else, it appears that in this case the technology platform UCSF and Intel are developing may be productized and made available to other providers, which could be very valuable. After all, while individual health systems (such as Geisinger) have the resources to kick off big data analytics projects on their own, it’s possible a standardized platform could make such technology available to smaller players. Let’s see how this goes.

An Effective Strategy for Long-term Epic Training

Posted on January 27, 2017 I Written By

The following is a guest blog post by Chris Cooley, Training Advisor at Pivot Point Consulting, a Vaco Company.

Ensuring that you have enough staff to cover day-to-day, new-hire, remedial, and monthly EHR update training is not an easy task. At the most recent Epic User Group Meetings and Spring Councils, sessions dedicated to building steady training teams were among the best attended. To be sure, Epic training is a hot topic in healthcare organizations—particularly as it relates to new hires. Here are some best-practice suggestions to help establish a long-term and successful Epic training program.

The Necessary Evils

eLearning
Many organizations are opting for eLearning in lieu of classroom training to reach multiple groups. The difficulty with this approach is the inability to truly know if the participant grasped the material. Most participants can pass a quick post-exam without completely understanding or retaining the information.

Timing is also an issue. Even a two-day lapse between an eLearning session and practicing the learned material can pose the risk of an 80 percent information loss, requiring retraining or additional support during the first shift following training. That said, when used correctly, eLearning can be quite effective when used in conjunction with traditional classroom training and immediate practice.

For those familiar with Epic, an interactive eLearning session that speaks to the specifics of your organization can easily be implemented in lieu of classroom training. When using eLearning, make sure to follow adult learning principles. Keep courses short, interactive, and challenging to keep end users engaged. To help participants retain information, include built-in exercises to prevent advancing without completing an action.

Classroom Training
In a preceptor-led training model, about four to eight hours of classroom training should be sufficient. Stick to the basics of navigation, terminology, and one or two main workflows to get comfortable working in the system.

For physicians, schedule a one-on-one follow-up with the trainer to set up preference lists and customizations within the same week. Avoid doing this day one or two, as the physician will need to be familiar with the existing orders and sets before customizing further.

Beyond the Classroom

Routine Training Integration
Standard training and orientation programs offer great opportunities to incorporate Epic-specific training elements where applicable. Nurses, for example, have a day or more of skill validation when starting a new position. For every skill they perform, an Epic training opportunity exists. Have participants find the order in Epic, perform the skill, then document the appropriate procedure and follow up. Collaborate with the education department and affected department leaders to add Epic workflows into routine training outlets.

Preceptorship
Learning happens best when on the floor, in the department, or repeatedly completing a task. Assign new hires a preceptor who is well versed in Epic and department workflows. Have them log in and perform the work while the preceptor guides them through their duties. After two to three days of side-by-side work, your new employee should be off and running.

Draw preceptors from within the new employee’s department and remove them from their daily duties when onboarding new hires. Choose your preceptors wisely. Just because Jane Doe is the resident Epic expert on your floor doesn’t mean she’ll be the best preceptor. Look for someone who embodies your organization’s culture, is a cheerleader for Epic, and has the patience to answer the same question multiple times.

Other Considerations

Materials
Materials must be well written, well organized, and—most important—accessible. Often, materials are outdated, in print form only, or not easily found by the end user. The use and regular maintenance of Learning Home Dashboards can ensure the latest materials are organized, intuitive, and available.

Consider turning tip sheets into two-minute-or-less video snippets. More often than not, watching and then repeating a process is preferable to deciphering a tip sheet and/or screen shots—especially for physicians and millennials looking for the quickest answer.

Remedial Training
While new hires account for about 30-50 percent of a trainer’s time, some individuals or departments will always need a little extra help. For example, evaluating a workflow to offer a faster/easier process, retraining, or providing additional one-on-one time with the end user can account for another 20 percent of a trainer’s time.

Update Training
Each month, a new set of Epic updates must be showcased to employees. This can be accomplished via monthly training or eLearning. In my experience, the time to coordinate and deliver monthly update training accounts for about 10 percent of the trainer’s time.

Rounding
End users often struggle in silence. When my trainers are not actively training, or working on materials, they are rounding in the departments they support looking for opportunities to strengthen knowledge. In addition to rounding, trainers attend huddles and meetings, offer help, and bring vital intel about updated or ill-working workflows to the principal trainer’s attention.

Help Desk
Trainers will also spend a good deal of time working “tickets” to assist end users (and often analysts) in identifying and communicating problems and resolutions.

Learning Management System (LMS) Administration
Hundreds of small details go into ensuring that Epic training is meeting the needs of an organization.  Who is expected in training? When and where can training be held? Who has completed training and can be activated in the system? It is imperative to dedicate at least one full time LMS administrator or coordinator to these ongoing Epic needs. Depending on the organization’s size, this may require up to four full-time resources.

Effective Coverage 
The number of Epic trainers needed will vary according to the organization’s size and hiring volume. Depending on the application and the hiring schedule, your principal trainer may be able to handle all training without the support of additional resources. However, I recommend having at least one credentialed trainer available for backup—to cover vacations, assist in remedial training, etc. Consider cross-training to make trainers versatile in related apps. Maintain expertise amongst your trainers by limiting cross-training to three areas of focus.

The example below includes enough trainers to cover the needs of a two hospital system and surrounding clinics in the same geographical location.

CT1: SBO, HB/PB
CT2 ClinDoc, Stork, Orders
CT3 ClinDoc, Beaker, Orders
CT4 Ambulatory, HOD, Cadence
CT5 Ambulatory, HOD, Cadence
CT6 Radiant, Cupid
CT7 Beacon, Willow
CT8 ASAP, OpTime, ANA
CT9 HIM, GC
CT10 HIM, GC

 

PT1 GC, Cadence
PT2 Ambulatory, HOD
PT3 ClinDoc, Stork
PT4 Orders, ASAP, Beaker
PT5 OpTime, ANA
PT6 Radiant, Cupid
PT7 Beacon, Willow
PT8 HIM, HB, PB, SBO

 
Creating partnerships throughout your organization, along with a steady, recurring training schedule, is the key to running an efficient, low-budget training team. With exceptional, easily accessible training materials and operational preceptors, training can be efficient, low-cost, and have employees in their positions with minimal classroom time.

About Chris Cooley
Chris Cooley is a Subject Matter Expert for the LIVESite division of Pivot Point Consulting, a Vaco Company. Previously, she worked as a full-time training manager, with 14 EMR implementations under her belt. With a combined knowledge of adult learning principles, technical writing, project management and the healthcare world, Chris is known for her creative solutions.