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Telemedicine Becoming Popular, But Seldom Profitable

Posted on October 18, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

New research suggests that while most physicians are supportive of telemedicine, others have grave reservations about providing this type of care, and that more than half of organizations aren’t making money delivering telemedicine services.

In an effort to learn more about attitudes toward telemedicine, Reaction Data surveyed 386 physicians, physician leaders, IT leaders and nurse leaders as well as differences in adoption levels between different types of organizations.,

Some of the top benefits of telemedicine cited by respondents included that it helped providers to meet demand for simpler and more cost-effective care delivery (28%), allowed them to treat more patients (23%) and that it was easing demands on staff (19%). Interestingly, just 10% said that telemedicine was proving to be a viable source of revenue, and elsewhere in the survey, 14% reported that telemedicine was revenue-negative.

The majority of physicians (68%) reported that they were in favor of telemedicine, while another 15% took a neutral position. Only 17% didn’t support widespread telemedicine use.

Their responses varied more, however, when it came to how much of care could be effectively delivered via telemedicine.

Thirty-two percent felt that 0 to 20% of care could be delivered this way; 33% of physician respondents felt that 30 to 40% care could be delivered digitally; 19% of respondents said 50 to 60% of care could be provided via telemedicine; 14% felt that 70 to 80% of care could be provided digitally. Just 2% felt that 90 to 100% of care could be delivered via this channel.

When it came to actually delivering the care themselves — rather than a hypothetical situation — respondents seemed less flexible. For example, 33% said that they would never contract with an outsourced telemedicine company to provide patient consults.

On the other hand, 50% said they’d considered moonlighting as a telemedicine consultant, 7% said they’d already done so frequently, 8% said they delivered such consults occasionally 2% said that was all they did for a living.

Regardless, many healthcare organizations are adopting this approach on a corporate level. Sixty-one percent of hospitals in a health system said they adopted telemedicine: 40% of standalone hospitals had done so; 58% practices owned by a health system has that this technology. Only 17% of physician-owned practices had done so, which could reflect cultural issues, costs or technology adoption concerns.

Physicians that were delivering telemedicine services most often used them to reach patients in rural areas (24%), provide follow-up care (24%) and manage specific patient populations (23%).

Among organizations that haven’t adopted telemedicine, many are scarcely getting their feet wet. While one in three providers are evaluating telemedicine options currently, 20% are two years or more away from adoption and 26% said they would never move in this direction.

Meanwhile, roughly one-third of physician-owned practices reported that they would never adopt telemedicine. One responding physician called it “inherent malpractice,” and another called it a “blatant attempt to circumvent the physical examination.” It seems unlikely that these clinicians will change their views on this topic.

Getting Buy-in For Your Second (Or More) EMR Purchase

Posted on August 15, 2017 I Written By

The following is a guest blog post by Michael Shearer is VP of Marketing for SelectHub.

Remember when you rolled out your first EMR?  Many of your doctors were uncertain, frustrated or angry, insurers were rejecting claims left and right and revenue fell as providers struggled to use the new system. Ah, those were lovely days.

Thankfully, in time everyone finally adapted. Through a combination of one-on-one coaching, group training, peer-to-peer mentoring and daily practice, clinicians got used to the system. Your patient volumes returned to normal. Some, though probably not all, of them got comfortable with the EMR, and a few even developed an interest in the technology itself.

Unfortunately, over time you’ve realized that your existing EMR isn’t cutting it. Maybe you want a system with an integrated practice management system. Perhaps your vendor isn’t giving you enough support or plans to jack up prices for future upgrades.  It could be that after working with it for a year or two, your EMR still doesn’t do what you wanted it to do. Whatever your reasons, it’s time to move on and find a system that fits better.

Given how painful the previous rollout was, buying a new EMR could be pretty disruptive and could easily stir up resentments and fears that had previously been laid to rest. But if you handle the process well, you might find that getting EMR buy-in is easier the second (or more) time around. Below are some strategies for getting clinicians on board.

Learn from your mistakes

Before you begin searching for an EMR, make sure that you’ve learned from your past mistakes. Consider taking the following steps:

  • Conduct thorough research on how clinicians (and staff if relevant) see your existing system. This could include a survey posing questions such as:
    • How usable is the EMR?
    • What impact does the EMR have on patient care, and why?
    • Does the EMR meet the needs of their specialty?
    • What features does the existing EMR lack?
    • Are EMR templates helping with documentation?
    • What are the great features of your existing EHR?
  • Compile a list of technical problems you’ve experienced with the system
  • Evaluate your relationship with the EMR vendor, and make note of any problems you’ve experienced
  • Consider whether your purchasing model (perpetual license vs. online subscription) is a good fit

Put clinicians in charge

When you bought your first EMR, you may have been on uncharted ground. You weren’t sure what you wanted to buy or how much to spend, and clinicians were at a loss as well.  Perhaps in the absence of detailed clinical feedback, you moved ahead on your own in an effort to keep the buying process moving.

This time around, though, clinicians will have plenty to say, and you should take their input very seriously. If they’re like their peers, their critiques of the existing EMR may include that:

  • It made documentation harder and/or more time-consuming
  • It wasn’t intuitive to use
  • It got in the way of their relationship with patients
  • It forced them to change their workflow
  • It didn’t present information effectively

These are just a few examples of the problems clinicians have had with their first EMR – you’ll probably hear a lot more. Ignoring these concerns could doom your next EMR rollout.

To avoid such problems, put clinicians in charge of the EMR purchasing process. By this point, they probably know what features they want, how documentation should work, what breaks their workflow, what supports their process and how the system should present patient data.

This will only work if you take your hands off of the wheel and let them drive the EMR selection process. Giving them a chance for token input but buying whatever administrators choose can only breed hostility and distrust.

Look to the future

When EMRs first showed up in medical practice, no one was sure what impact they’d have on patient care. Administrators knew that digitizing medical records would help them produce cleaner claims and shoot down denials, but few if any could explain why that would help their providers offer better care. In some cases, these first-line systems did nothing whatsoever for clinicians while weighing them down with extra work.

Over time, however, providers have begun using pooled EMR data to make good things happen, such as improving the health of entire populations, identifying how genetics can dictate responses to medication and predicting whether a patient is likely to develop a specific health condition. These are goals that will inspire most clinicians. While they may not care what happens in the business office, they care what happens to patients.

These days, in fact, using EMR data to improve care has become almost mandatory. Even if they didn’t bother before, practices are now buying systems better designed to help providers deliver care and improve outcomes. If your clinicians are still unhappy about their first experience, they may have trouble believing this. But make sure that they do.

The truth is, there will always be someone who doesn’t like technology, or refuses to take part in the buying process, and it’s unlikely you’ll win them over. But if your EMR actually enhances their ability to provide care, most will be happy to use it, and even evangelize the system to their colleagues. That’s the kind of buy-in you can expect if you deliver a system that meets their needs.

Michael Shearer is VP of Marketing for SelectHub, which offers selection tools for EMRs and practice management systems.

 

Should EMR Vendors Care If Patients Get Their Records?

Posted on August 11, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Not long ago, Epic CEO Judy Faulkner and former Vice President Joe Biden reportedly butted heads over whether patients need and can understand their full medical records. The alleged conversation took place at a private meeting for Cancer Moonshot, a program with which Biden has been associated since his son died of cancer.

According to a piece in Becker’s Health IT & CIO Review, Faulkner asked Biden why patients actually needed their full medical records. “Why do you want your medical records? They’re a thousand pages of which you understand 10,” she is said to have told Biden.

Epic responded to the widely-reported conversation with a statement arguing that Faulkner had been quoted out of context, and that the vendor supported patients’ rights to having their entire record. Given that Becker’s had the story third-hand (it drew on a Politico column which itself was based on the remarks of someone who had been present at the meeting) I have little difficulty believing that something was lost in translation.

Still, I am left wondering whether this piece had touched on something important nonetheless. It raises the question of whether EMR vendor CEOs have the attitude towards patient medical record access Faulkner is portrayed as having.

Yes, I suspect virtually every EMR vendor CEO agrees in principle that patients are entitled to access their complete records. Of course, the law recognizes this right as well. However, do they, personally, feel strongly about providing such access? Is making patient access to records easy a priority for them? My guess is “no” and “no.”

The truth is, EMR vendors — like every other business — deliver what their customers want. Their customers, providers, may talk a good game when it comes to patient record access, but only a few seem to have made improving access a central part of their culture. In my experience, at least, most do what medical records laws require and little else. It’s hard to imagine that vendors spend any energy trying to change customers’ records practices for the better.

Besides, both vendors and providers are used to thinking about medical record data as a proprietary asset. Even if they see the necessity of sharing this information, it probably rubs at least some the wrong way to ladle it out at minimal cost to patients.

Given all this background, it’s easy to understand why health IT editors jumped on the story. While she may have been misrepresented this time, it’s not hard to imagine the famously blunt Faulkner confronting Biden, especially if she thought he didn’t have a leg to stand on.

Even if she never spoke the words in question, or her comments were taken out of context, I have the feeling that at least some of her peers would’ve spoken them unashamedly, and if so, people need to call them out. If we’re going to achieve the ambitious goals we’ve set for value-based care, every player needs to be on board with empowering patients.

Bringing Zen To Healthcare:  Transformation Through The N of 1

Posted on July 21, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

The following essay wasn’t easy to understand. I had trouble taking it in at first. But the beauty of these ideas began to shine through for me when I took time to absorb them. Maybe you will struggle with them a bit yourself.

In his essay, the author argues that if providers focus on “N of 1” it could change healthcare permanently. I think he might be right, or at least makes a good case.  It’s a complex argument but worth following to the end. Trust me, the journey is worth taking.

The mysterious @CancerGeek

Before I share his ideas, I’ll start with an introduction to @CancerGeek, the essay’s author. Other than providing a photo as part of his Twitter home page, he’s chosen to be invisible. Despite doing a bunch of skillful GoogleFu, I couldn’t track him down.

@CancerGeek posted a cloud of interests on the Twitter page, including a reference to being global product manager PET-CT; says he develops hospital and cancer centers in the US and China; and describes himself as an associate editor with DesignPatient-MD.

In the essay, he says that he did clinical rotations from 1998 to 1999 while at the University of Wisconsin-Madison Carbone Comprehensive Cancer Center, working with Dr. Minesh Mehta.

He wears a bow tie.

And that’s all I’ve got. He could be anybody or nobody. All we have is his voice. John assures me he’s a real person that works at a company that everyone knows. He’s just chosen to remain relatively anonymous in his social profiles to separate his social profiles from his day job.

The N of 1 concept

Though we don’t know who @CancerGeek is, or why he is hiding, his ideas matter. Let’s take a closer look at the mysterious author’s N of 1, and decide for ourselves what it means. (To play along, you might want to search Twitter for the #Nof1 hashtag.)

To set the stage, @CancerGeek describes a conversation with Dr. Mehta, a radiation oncologist who served as chair of the department where @CancerGeek got his training. During this encounter, he had an insight which helped to make him who he would be — perhaps a moment of satori.

As the story goes, someone called Dr. Mehta to help set up a patient in radiation oncology, needing help but worried about disturbing the important doctor.

Apparently, when Dr. Mehta arrived, he calmly helped the patient, cheerfully introducing himself to their family and addressing all of their questions despite the fact that others were waiting.

When Dr. Mehta asked @CancerGeek why everyone around him was tense, our author told him that they were worried because patients were waiting, they were behind schedule and they knew that he was busy. In response, Dr. Mehta shared the following words:

No matter what else is going on, the world stops once you enter a room and are face to face with a patient and their family. You can only care for one patient at a time. That patient, in that room, at that moment is the only patient that matters. That is the secret to healthcare.

Apparently, this advice changed @CancerGeek on the spot. From that moment on, he would work to focus exclusively on the patient and tune out all distractions.

His ideas crystallized further when he read an article in the New England Journal of Medicine that gave a name to his approach to medicine. The article introduced him to the concept of N of 1.  All of the pieces began to began to fit together.

The NEJM article was singing his song. It said that no matter what physicians do, nothing else counts when they’re with the patient. Without the patient, it said, little else matters.

Yes, the author conceded, big projects and big processes matter still matter. Creating care models, developing clinical pathways and clinical service lines, building cancer centers, running hospitals, and offering outpatient imaging, radiology and pathology services are still worthwhile. But to practice well, the author said, dedicate yourself to caring for patients at the N of 1. Our author’s fate was sealed.

Why is N of 1 important to healthcare?

Having told his story, @CancerGeek shifts to the present. He begins by noting that at present, the healthcare industry is focused on delivering care at the “we” level. He describes this concept this way:

“The “We” level means that when you go to see a physician today, that the medical care they recommend to you is based on people similar to you…care based on research of populations on the 100,000+ (foot) level.”

But this approach is going to be scrapped over the next 8 to 10 years, @CancerGeek argues. (Actually, he predicts that the process will take exactly eight years.)

Over time, he sees care moving gradually from the managing groups to delivering personalized care through one-to-one interactions. He believes the process will proceed as follows:

  • First, sciences like genomics, proteomics, radionomics, functional imaging and immunotherapies will push the industry into delivering care at a 10,000-foot population level.
  • Next, as ecosystems are built out that support seamless sharing of digital footprints, care will move down to the 1,000-foot level.
  • Eventually, the system will alight at patient level. On that day, the transition will be complete. Healthcare will no longer be driven by hospitals, healthcare systems or insurance companies. Its sole focus will be on people and communities — and what the patient will become over time.

When this era arrives, doctors will know patients far more deeply, he says.

He predicts that by leveraging all of the data available in the digital world, physicians will know the truth of their experiences, including the food they eat, the air they breathe, how much sleep they get, where they work, how they commute to and from work and whether they care for a family member or friend, doctors will finally be able to offer truly personalized care. They’ll focus on the N of 1, the single patient they’re encountering at that moment.

The death of what we know

But we’re still left with questions about the heart of this idea. What, truly, is the N of 1? Perhaps it is the sound of one hand clapping. Or maybe it springs from an often-cited Zen proverb: “When walking, walk. When eating, eat.” Do what you’re doing right now – focus and stay in the present moment. This is treating patients at the N of 1 level, it seems to me.

Like Zen, the N of 1 concept may sound mystical, but it’s entirely practical. As he points out, patients truly want to be treated at the N of 1 – they don’t care about the paint on the walls or Press Ganey scores, they care about being treated as individuals. And providers need to make this happen.

But to meet this challenge, healthcare as we know it must die, he says. I’ll leave you with his conclusion:

“Within the next eight years, healthcare as we know it will end. The new healthcare will begin. Healthcare delivered at the N of 1.”  And those who seek will find.

The EMR Vendor’s Dilemma

Posted on June 6, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Yesterday, I had a great conversation with an executive at one of the leading EMR vendors. During our conversation, she stressed that her company was focused on the future – not on shoring up its existing infrastructure, but rather, rebuilding its code into something “transformational.”

In describing her company’s next steps, she touched on many familiar bases, including population health, patient registries and mobile- first deployment to support clinicians. She told me that after several years of development, she felt her company was truly ready to take on operational challenges like delivering value-based care and conducting disease surveillance.

All that being said – with all due respect to the gracious exec with whom I spoke – I wouldn’t want to be a vendor trying to be transformed at the moment. As I see it, vendors who want to keep up with current EMR trends are stuck between a rock and a hard place.

On the one hand, such vendors need to support providers’ evolving health IT needs, which are changing rapidly as new models of care delivery are emerging. Not only do they need to provide the powerhouse infrastructure necessary to handle and route massive floods of data, they also need to help their customers reach and engage consumers in new ways.

To do so, however, they need to shoot at moving targets, or they won’t meet provider demand. Providers may not be sure what shape certain processes will take, but they still expect EMR vendors to keep up with their needs nonetheless. And that can certainly be tricky these days.

For example, while everybody is talking about population health management, as far as I know we still haven’t adopted a widely-accepted model for adopting it. Sure, people are arriving at many of the same conclusions about pop health, but their approach to rolling it out varies widely.  And that makes things very tough for vendors to create pop health technology.

And what about patient engagement solutions? At present, the tools providers use to engage patients with their care are all over the map, from portals to mobile apps to back-end systems using predictive analytics. Synchronizing and storing the data generated by these solutions is challenging enough. Figuring out what configuration of options actually produces results is even harder, and nobody, including the savviest EMR vendors, can be sure what the consensus model will be in the future.

Look, I’m aware that virtually all software vendors face this problem. It’s difficult as heck to decide when to lead the industry you serve and when to let the industry lead you. Straddling these two approaches successfully is what separates the men from the boys — or the girls from the women — and dictates who the winners and losers are in any technology market.

But arguably, health IT vendors face a particularly difficult challenge when it comes to keeping up with the times. There’s certainly few industries are in a greater state of flux, and that’s not likely to change anytime soon.

It will take some very fancy footwork to dance gracefully with providers. Within a few years, we’ll look back and know vendors adapted just enough.

Clinical Insights from Social Media Data: Amplifying Patient Voice with Symplur

Posted on May 31, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

What data from social media can help healthcare organizations?

One of the biggest challenges of online and social data is the sheer volume of unstructured data. Can your physician read all your tweets and postings? Hopefully not. Physicians have data and work overload, a daily report of steps taken from activity trackers or online social media use hurts their ability to treat patients. HealthIT solutions can help process this data and find patterns and changes.

I had a conversation with Audun Utengen about actionable insights into healthcare from his company, Symplur. At Datapalooza he participated in a panel and mentioned the rich amount of patient data that can be found on twitter (shocked gasp followed by a furrowed brow). Symplur signals tracks online engagement.  You can find healthcare insights from conversations really quickly. They provide tools that help healthcare providers get patient insights where they are naturally interacting. There is value in meeting patients where they are, and patients are discussing their healthcare online.

Originally, the assumption was that patients would not say things online. Sensitive topics do not naturally show up in social media use- fewer people are discussing gonorrhea online than receive treatment for gonorrhea. Providers assumed that things which are protected patient information would not show up on twitter. They were wrong. As most social media users know- it’s shocking what people will post online. Not every aspect of health is on twitter but patients want to engage online.  They go to twitter because they want their voices to be heard. They want things to change. They can’t be ignored on twitter. They want their voices to be heard by people in decision-making positions.

Patient’s online discussion have positive impacts on organizations. The key is to be proactive about patient engagement online. Stanford did a study looking about patients’ engagement at conferences. Typically, you will find 1 patient in the top 1 percent of influencers. While this number is low, conferences which have a higher percentage of patients active as top influencers have a greater reach. Want to increase your Healthcare voice and conference audience? Engage patient advocates online. Engaging patients is commercially valuable in amplification. Future patients get more insight as well.  Audun Utengen and I looked at the data from Datapalooza and found that 11 of the top 100 influencers were patients.  That is way ahead of the median number for all healthcare conferences- in 2016 the average number of top influencers that were patients at a conference was one.

“They did a great job giving patients a voice at the conference. I am impressed.”

-Audun Utengen, Co-Founder of Symplur

Healthcare Stakeholder breakdown of the top 100 influencers ranked by the Healthcare Social Graph Score.

Datapalooza had a higher than average reach and a unique blend of participants. Audun Utengen described some of the unique features of the conference:

“The social conversation from the conference was very dynamic. From the 9,366 tweets, 80% included at least one mention. Lot’s of connections were made and we witnessed the typical “flattening of healthcare” that social media is known for by breaking down the barriers between the stakeholder groups. Below is a network analysis graph showing the flattening and the conversational patterns between Twitter account and their healthcare stakeholder groupings.”

Conversations blend between different stakeholders in the healthcare conversation at Datapalooza

The ability for many stakeholders to access information and interact with each other in one place is one of the advantages of twitter. Using hashtags can help stakeholders learn about content about a specific topic quickly. One of the things Symplur is allows is the visualization of keywords surrounding conversations on twitter. When looking at the conversations from Datapalooza the topic of “patients” was very high. Unsurprisingly, “data” is the topic of focus. Patient, Health and Patients rounded out the top conversation topics.

Keyword Frequency Analysis Graph

Symplur Signals have been used for over 200 healthcare studies. They partner with academic research centers seeking more information from online conversations. Companies can also look at competitors in their area and see how they compare. Does a nearby provider have more positive mentions on social media?

Data from online interactions can also give insights into patient health. Social usage has unique implications for mental health. Frequently, online behavior change can predict mental health change. Pediatricians and Providers are in a position to see online behavior in their area and help families understand the implications. If bullying is a problem in your area providers can know their patients will have higher stress levels and provide resources and support. Certain behaviors and even emojis indicate a higher risk of depression. A suicide that will predictably happen based on social data will not show up in clinical records. Listening to what patients want us to hear will help provide greater support.

The sheer volume of social data can mask its usefulness. Online activity and data can be difficult to process for many clinicians. In a world of ever-increasing data and patients reporting everything from steps taken a day to now online behavior many providers have data overload. Data insight tools such as Symplur filter data into a format that allows physicians and systems to use it to improve patient outcomes.

Few Practices Rely Solely On EMR Analytics Tools To Wrangle Data

Posted on May 23, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

A new survey done by a trade group representing medical practices has concluded that only a minority of practices are getting full use of their EMR’s analytics tools.

The survey, which was reported on by Becker’s Hospital Review, was conducted by the Medical Group Management Association.  The MGMA’s survey called on about 900 of its members to ask how their practices used EMRs for analytics.

First, and most unexpectedly in today’s data-driven world, 11 percent of respondents said that they don’t analyze their EMR data at all.

Thirty-one percent of respondents told MGMA that they use all of their EMR’s analytical capabilities, and 22 percent of respondents said they used some of their EMR’s analytics capabilities.

Another 31 percent reported that they were using both their EMR’s analytics tools and tools from an external vendor. Meanwhile, 5 percent said they used only an external vendor for data analytics.

According to Derek Kosiorek, CPEHR, CPHIT, principal consultant with MGMA’s Health Care Consulting Group, the survey results aren’t as surprising as they may seem. In fact, few groups are likely to get  everything they need from EMR data, he notes.

“Many practices do not have the resources to mine the data and organize it in ways to create new insights from the clinical, administrative and financial information being captured daily,” said Kosiorek in a related blog post. “Even if your practice has the staff with the knowledge and time to create reports, the system often requires an add-on product sold by the vendor or an outside product or service to analyze the data.”

However, he predicts that this will change in the near future. Not only will EMR analytics help groups to tame their internal data, it will also aggregate data from varied community settings such as the emergency department, outpatient care and nursing homes, he suggests. He also expects to see analytics tools offer a perspective on care issues brought by regional data for similar patients.

At this point I’m going to jump in and pick up the mic. While I haven’t seen anyone from MGMA comment on this, I think this data – and Kosiorek’s comments in particular – underscore the tension between population health models and day-to-day medical practice. Specifically, they remind us that doctors and regional health systems naturally have different perspectives on why and how they use data.

On the one hand there’s medical practices which, from what I’ve seen, are of necessity practical. These providers want first and foremost to make individual patients feel good and if sick get better. If that can be done safely and effectively I doubt most care about how they do it. Sure, doctors are aware of pop health issues, but those aren’t and can’t be their priority in most cases.

Then, you have hospitals, health systems and ACOs, which are already at the forefront of population health management. For them, having a consistent and comprehensive set of tools for analyzing clinical data across their network is becoming job one. That’s far removed from focusing on day-to-day patient care.

It’s all well and good to measure whether physicians use EMR analytics tools or not. The real issue is whether large health organizations and practices can develop compatible analytics goals.

The Sexiest Data in Health IT: Datapalooza 2017

Posted on May 15, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

The data at this conference was the Best Data. The Biggest Data. No one has better data than this conference.

The sexiest data in all of healthIT was highlighted in Washington DC at Datapalooza April 27-28, 2017.  One of the main themes was how to deal with social determinants of health and the value of that data.  Sachin H. Jain, MD of Caremore Health reminded us that “If a patient doesn’t have food at home waiting for them they won’t get better” social data needs to be in the equation. Some of the chatter on the subject of healthcare reform has been criticism that providing mandatory coverage hasn’t always been paired with knowledge of the area. If a patient qualifies for Medicaid and has a lower paying job how can they afford to miss work and get care for their health issues?
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Rural areas also have access issues. Patient “Charles” works full time during the week and qualifies for Medicaid. He can’t afford to miss a lot of work but needs a half a day to get treatments which affect his ability to work. There is no public transportation in his town to the hospital in a city an hour and a half away. Charles can’t afford the gas or unpaid time off work for his treatment.

Urban patient “Haley” returns to her local ER department more than once a week with Asthma attacks.  Her treatments are failing because she lives in an apartment with mold in the walls. As Craig Kartchner from the Intermountain Healthcare team responded to the #datapalooza  hashtag online- These can be the most difficult things to change.

The 2016 report to Congress addresses the difficulty of the intersection between social factors and providing quality healthcare in terms of Social Determinants of Health:

“If beneficiaries with social risk factors have worse health outcomes because the providers they see provide low quality care, value based purchasing could be a powerful tool to drive improvements in care and reduce health disparities. However, if beneficiaries with social risk factors have worse health outcomes because of elements beyond the quality of care provided, such as the social risk factors themselves, value based payment models could do just the opposite. If providers have limited ability to influence health outcomes for beneficiaries with social risk factors, they may become reluctant to care for beneficiaries with social risk factors, out of fear of incurring penalties due to factors they have limited ability to influence.”

Innovaccer just launched a free tool to help care teams track and monitor Medicare advantage plans. I went to their website and looked at my county and found data about the strengths in Salt Lake where I’m located. They included:

  • Low prevalence of smoking
  • Low Unemployed Percentage
  • Low prevalence of physically inactive adults

Challenges for my area?

  • Low graduation rate
  • High average of daily Air pollution
  • High income inequality
  • High Violent crime rate per 100,000 population

Salt Lake actually has some really bad inversion problems during the winter months and some days the particulate matter in the air creates problems for respiratory problems. During the 2016-2017 winter there were 18 days of red air quality and 28 days of yellow air quality. A smart solution for addressing social determinants of health that negatively impact patients in this area could be addressing decreasing air pollution through increased public transportation. Healthcare systems will see an increase in cost of care during those times and long term population health challenges can emerge. You can look at your county after you enter your email address on their site. This kind of social data visualization can give high level insights into the social factors your population faces.

One of the themes of HealthDataPalooza was how to use system change to navigate the intersection between taking care of patients and not finding way to exclude groups. During his panel discussion of predictive analytics, Craig Monson the medical director for analytics and reporting discussed how “data analytics is the shiny new toy of healthcare.”    In addition to winning the unofficial datapalooza award for the most quotes and one liners – Craig presented the Clinical Risk Prediction Initiative (CRISPI).  This is a multi variable logistic regression model with data from the Atrius health data warehouse. His questions for systems to remember in their data analysis selection are “Who is the population you are serving? What is the outcome you need? What is the intervention you should implement?”

Warning- Craig reminds us that in a world of increasing sexy artificial intelligence coding a lot of the value analysis can be done with regression. Based on that statement alone I think he can be trusted. I still need to see his data.

CRISPI analyzed the relative utility of certain types of data, and didn’t have a large jump in utility when adding Social Determinant Data. This data was one of the most popular data sets during Datapalooza discussions but the reality of making actionable insights into system improvement? Craig’s analysis said it was lacking. Does this mean social determinant data isn’t significant or that it needs to be handled with a combination of traditional modeling and other methods?  Craig’s assertion seemed to fly in the face of the hot new trend of Social Determinants of Health data from the surface.

Do we have too much data or the wrong use of the data? Most of the companies investing into this space used data sources outside the traditional definition to help create solutions with social determinate of health and Patient outcomes. They differed in how they analyzed social determinant data. Traditional data sources for the social determinants of health are well defined within the public health research.  The conditions in which you work and live impact your health.

Datapalooza had some of the greatest minds in data analytics and speakers addressed gaps in data usefulness. Knowing that a certain large county wide population has a problem with air quality might not be enough to improve patient outcomes. There is need for analysis of traditional data sources in this realm and how they can get meaningful impact for patients and communities. Healthcare innovators need to look at different data sources.  Nick Dawson, Executive director of Johns-Hopkins Sibley Innovation Hub responded to the conversation about food at home with the data about Washington DC.  “DC like many cities has open public data on food scarcity. But it’s not part of a clinical record. The two datasets never touch.” Data about food scarcity can help hospital systems collaborate with SNAP and Government as well as local food programs. Dawson leads an innovation lab at Johns Hopkins Sibley where managers, directors, VPs and C Suite leaders are responsible for working with 4 innovation projects each year.

Audun Utengen, the Co Founder of Symplur said “There’s so much gold in the social media data if you choose to see it.” Social data available online helps providers meet patients where they are and collect valuable data.  Social media data is another source to collect data about patient preferences and interactions for reaching healthcare populations providers are trying to serve. With so much data available sorting through relevant and helpful data provides a new challenge for healthcare systems and providers.

New Data sources can be paired with a consultative model for improving the intersection of accountable care and lack of access due to social factors. We have more sophisticated analytic tools than ever for providing high value care in the intersection between provider responsibility and social collaboration. This proactive collaboration needs to occur on local and national levels.  “It’s the social determinants of health and the behavioral aspects that we need to fund and will change healthcare” we were reminded. Finding local community programs that have success and helping develop a strategy for approaching Social Determinants of Health is on the mind of healthIT professionals.

A number of companies examine data from sources such as social media and internet usage or behavioral data to design improvements for social determinants of health outcomes.   They seek to bridge the gaps mentioned by Dawson. Data sets exist that could help build programs for social determinants of health.  Mandi Bishop started Lifely Insights centered around building custom community plans with behavioral insights into social determinant data. Health in all Policies is a government initiative supporting increased structure and guidelines in these areas. They support local and State initiatives with a focus on prevention.

I’m looking forward to seeing how the data landscape evolves this year. Government Challenges such as the Healthy Behavior Data Challenge launched at Datapalooza will help fund great improvements. All the data people will get together and determine meaningful data sets for building programs addressing the social determinants of health. They will have visualization tools with Tableau. They will find ways to get food to patients at home so those patients will get better. Programs will find a way to get care to rural patients with financial difficulty and build safe housing.

From a healthcare delivery perspective the idea of collaborating about data models can help improve community health and decrease provider and payer cost. The social determinants of health can cost healthcare organizations more money than data modeling and proactive community collaboration.

Great regressions, saving money and improving outcomes?

That is Datapalooza.

Using AI To Streamline EMR Workflow For Clinicians

Posted on May 10, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Understandably, most of the discussion around AI use in healthcare focuses on data analytics for population health management and predictive analytics. Given the massive scale of the data we’re collecting, that’s no surprise.

In fact, one could argue that using AI technologies has gone from an interesting idea to an increasingly established parto the health IT mix. After all, few human beings can truly understand what’s revealed by terabytes of data on their own, even using well-designed dashboards, filters, scripting and what have you. I believe it takes a self-educating AI “persona,” if you will, to glean advanced insights from the eternity of information we have today.

That being said, I believe there’s other compelling uses for AI-fueled technologies for healthcare organizations. If we use even a relatively simple form of interpretive intelligence, we can improve health IT workflows for clinicians.

As clinicians have pointed out over and over, most of what they do with EMRs is repetitive monkey work, varied only by the need to customize small but vital elements of the medical record. Tasks related to that work – such as sending copies of a CT scan to a referring doctor – usually have to be done in another application. (And that’s if they’re lucky. They might be forced to hunt down and mail a DVD disc loaded with the image.)

Then there’s documentation work which, though important enough, has to be done in a way to satisfy payers. I know some practice management systems that integrate with the office EMR auto-populate the patient record with coding and billing information, but my sense is that this type of automation wouldn’t scale within a health system given the data silos that still exist.

What if we used AI to make all of this easier for providers? I’m talking about using a predictive intelligence, integrated with the EMR, that personalizes the way data entry, documentation and follow-up needs are presented. The AI solution could automatically queue up or even execute some of the routine tasks on its own, leaving doctors to focus on the essence of their work. We all know Dr. Z doesn’t really want to chase down that imaging study and mail it to Albany. AI technology could also route patients to testing and scans in the most efficient manner, adjusted for acuity of course.

While AI development has been focused on enterprise issues for some time, it’s already moving beyond the back office into day-to-day care. In fact, always-ahead-of-the-curve Geisinger Health System is already doing a great deal to bring AI and predictive analytics to the bedside.

Geisinger, which has had a full-featured EMR in place since 1996, was struggling to aggregate and manage patient data, largely because its legacy analytics systems couldn’t handle the flood of new data types emerging today.

To address the problem, the system rolled out a unified data architecture which allowed it to integrate current data with its existing data analytics and management tools. This includes a program bringing together all sepsis-vulnerable patient information in one place as they travel through the hospital. The tool uses real-time data to track patients in septic shock, helping doctors to stick to protocols.

As for me, I’d like to see AI tools pushed further. Let’s use them to lessen the administrative burden on overworked physicians, eliminating needless chores and simplifying documentation workflow. And it’s more than time to use AI capabilities to create a personalized, efficient EMR workflow for every clinician.

Think I’m dreaming here? I hope not! Using AI to eliminate physician hassles could be a very big deal.

Paper Records Are Dead

Posted on March 14, 2017 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 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. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Here’s an argument that’s likely to upset some, but resonate with others. After kicking the idea around in my head, I’ve concluded that given broad cultural trends, that the healthcare industry as a whole has outgrown the use of paper records once and for all. I know that this notion is implicit in what health IT leaders do, but I wanted to state this directly nonetheless.

Let me start out by noting that I’m not coming down on the minority of practices (and the even smaller percentage of hospitals) which still run on old-fashioned paper charts. No solution is right for absolutely everyone, and particularly in the case of small, rural medical practices, paper charts may be just the ticket.

Also, there are obviously countless reasons why some physicians dislike or even hate current EMRs. I don’t have space to go into them here, but far too many, they’re hard to use, expensive, time-consuming monsters. I’m certainly not trying to suggest that doctors that have managed to cling to paper are just being contrary.

Still, for all but the most isolated and small providers, over the longer term there’s no viable argument left for shuffling paper around. Of course, the healthcare industry won’t realize most of the benefits of EMRs and digital health until they’re physician-friendly, and progress in that direction has been extremely slow, but if we can create platforms that physicians like, there will be no going back. In fact, for most their isn’t any going back even if they don’t become more physician firendly. If we’re going to address population-wide health concerns, coordinate care across communities and share health information effectively, going full-on digital is the only solution, for reasons that include the following:

  • Millennial and Gen Y patients won’t settle for less. These consumers are growing up in a world which has gone almost completely digital, and telling them that, for example they have to get in line to get copies of a paper record would not go down well with them.
  • Healthcare organizations will never be able to scale up services effectively, or engage with patients sufficiently, without using EMRs and digital health tools. If you doubt this, consider the financial services industry, which was sharing information with consumers decades before providers began to do so. If you can’t imagine a non-digital relationship with your bank at this point, or picture how banks could do their jobs without web-based information sharing, you’ve made my point for me.
  • Without digital healthcare, it may be impossible for hospitals, health systems, medical practices and other healthcare stakeholders to manage population health needs. Yes, public health organizations have conducted research on community health trends using paper charts, and done some effective interventions, but nothing on the scale of what providers hope (and need) to achieve. Paper records simply don’t support community-based behavioral change nearly as well.
  • Even small healthcare operations – like a two-doctor practice – will ultimately need to go digital to meet quality demands effectively. Though some have tried valiantly, largely by auditing paper charts, it’s unlikely that they’d ever build patient engagement, track trends and see that predictable needs are met (like diabetic eye exams) as effectively without EMRs and digital health data.

Of course, as noted above, the countervailing argument to all of this is the first few generations of EMRs have done more to burden clinicians than help them achieve their goals, sometimes by a very large margin. That seems to be largely because most have been designed — and sadly, continue to be designed — more to support billing processes than improve care. But if EMRs are redesigned to support patient care first and foremost, things will change drastically. Someday our grandchildren, carrying their lifetime medical history in a chip on their fingernail, will wonder how providers ever managed during our barbaric age.