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2018 Health:Further Festival Format Delivers Interesting Takeaways and a Side of Fun

Posted on September 4, 2018 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

Health:Further delivered interesting takeaways from Walmart, Dell Medical School, Cerner, athenahealth & MEDITECH. The companies are bullish on data analytics, design-thinking and interoperability. Social Determinants of Health remains a challenge.

Last week, I had the chance to attend the 2018 Health:Further event (H:F) for the first time. I say event rather than conference because the latter would not do justice to the non-traditional format of the gathering in Nashville. Instead of the standard plenary+breakouts+exhibit-hall arrangement that is the norm for conferences, H:F used a music-festival approach with multiple stages in a giant exhibit hall. This was a perfect match to the unique venue – Nashville’s Music City Center.

There were four themed stages at H:F

  1. Summit of the Southeast #SOSE18 (hosted by the Tennessee chapter of HIMSS)
  2. Finances and Tokenomics (hosted by the Tennessee chapter of HFMA)
  3. Humanizing Health
  4. Clinicians and Consumers

The music-inspired multiple-stage approach allowed participants to easily and quickly move between talks. Each stage was curtained off with convenient entrances on each side of the seating area. The lack of walls and doors gave the event a dynamic and fluid feeling – with many members of the audience deciding to move to a different stage after listening to the opening statements of the session they were currently watching. Although it may have been disheartening for speakers to see people getting up to leave, in most cases there was an equal flow of people into the audience as were leaving.

Photo by AngelMD:

As a veteran conference attendee, I have no hesitation voting with my feet, but many others do not want to make a scene opening the heavy conference room doors. Most just stay put and check email while the speaker completes the presentation. Neither benefits in that situation and so the H:F organizers overcame this challenge by adopting the festival format.

Over the three days of the event, I had the opportunity to listen to thought-leaders from a number of high-profile companies including Walmart, HCA Healthcare, Dell Medical School, Mass Challenge, the Department of Health and Human Services, Cerner, MEDITECH, and athenahealth. From this outstanding lineup of speakers, several key interesting takeaways emerged.

Data analytics is yielding useful health insights

Marcus Osborne, Vice President of Health & Wellness Transformation at Walmart, spoke about the retail giant’s use of consumer purchasing to detect changes in people’s health. The company has done research on the buying patterns of its consumers and they have found that small changes in purchase behavior are strongly linked to changes in a person’s health. The data and linkage is so strong that it may be possible for Walmart to know about it before the person even has had a chance to go see their doctor!

I’m excited to see how retailers like Walmart, Amazon, Target, and others can impact health with this depth of data analysis.

Osborne also spoke about using data analytics to help drive down the cost of healthcare for it’s workforce by guiding people to higher efficacy treatments. Osborne used the term “appropriate care” when describing how data could be used to match employees with the best healthcare professional given that person’s unique health needs. The company estimates this could yield over $1Billion in savings.

Design will be a differentiator

Stacey Chang, Founder & Executive Director of the Design Institute for Health at UT Austin, challenged the audience to think seriously about the role of design in healthcare. He made the case that design-thinking and well-designed healthcare organizations (physically and from a process perspective) will be the winners as the system becomes more value-based and consumer driven.

Chang’s most thought-provoking takeaway was his statement: “To provoke change with technology – allowing humans to interact again”. That is, to truly affect change in healthcare, we need to work on technologies that bring people closer together and allow them to interact with each other, rather than with a computer screen.

Diversity leads to innovation

In one of several all-women panels, the topic of diversity and how different perspectives are needed to improve healthcare was discussed. One panelist spoke passionately about the need for healthcare to be more inclusive of everyone involved in care: patients, care-givers, clinicians, administrators, payors, employers, etc. Another panelist quickly added that diversity of industry and training was also needed – that healthcare would benefit from perspectives from outside the industry and from people with non-medical backgrounds like arts, philosophy and music.

EHR companies can get along (interoperability)

The most memorable (and lively) session at H:F happened on the Summit of the Southeast stage. The team at Tennessee HIMSS managed to get representatives from Cerner, athenahealth, MEDITECH and Medhost on a panel together to talk about interoperability. Right from the first question, we knew we were in for a fun ride:

Greg Meyer @Greg_Meyer93, Director and Distinguished Engineer at Cerner, created the most memorable moment on stage, hugging Evan Grossman who was representing athenahealth after Grossman emphatically stated that patients should “not be the mule that makes interoperability work”:

The panelists spoke at length about practical strategies to achieve interoperability – strategies that did not involve creating yet another standard, government regulations or financial incentives. The consensus of the panel was the EHR companies simply needed to get down to work and make their respective systems talk to one another because it’s the right thing to do.

No argument here.

SDOH remains a challenge

The final takeaway from H:F was that social determinants of health (SDOH) is slowly entering the consciousness of healthcare. More and more people are starting to realize and see that we cannot address health if we do not also address poverty, education, the lack of jobs, transit and food deserts. Unfortunately SDOH solutions are still in short supply. No one I spoke to had any solid ideas that would scale and everyone acknowledged this would continue to be a challenge over the next decade.

Special thanks to the Tennessee HIMSS organization for inviting me to the 2018 Health:Further event.

Tips on Implementing Text Analytics in Healthcare

Posted on July 6, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Most of us would agree that extracting clinical data from unstructured physician notes would be great. At present, few organizations have deployed such tools, nor have EMR vendors come to the rescue en masse, and the conventional wisdom holds that text analytics would be crazy expensive. I’ve always suspected that digging out and analyzing this data may be worth the trouble, however.

That’s why I really dug a recent article from HealthCatalyst’s Eric Just, which seemed to offer some worthwhile ideas on how to use text analytics effectively. Just, who is senior vice president of product development, made a good case for giving this approach a try. (Note: HealthCatalyst and partner Regenstrief Institute offer solutions in this area.)

The article includes an interesting case study explaining how healthcare text analytics performed head-to-head against traditional research methods.

It tells the story of a team of analysts in Indiana that set out to identify peripheral artery disease (PAD) patients across two health systems. At first gasp, things weren’t going well. When researchers looked at EMR and claims data, they found that failed to identify over 75% of patients with this condition, but text analytics improved their results dramatically.

Using ICD and CPT codes for PAD, and standard EMR data searches, team members had identified less than 10,000 patients with the disorder. However, once they developed a natural language processing tool designed to sift through text-based data, they discovered that there were at least 41,000 PAD patients in the population they were studying.

To get this kind of results, Just says, there are three key features a medical text analytics tool should have:

  • The medical text analytics software should tailor results to a given user’s needs. For example, he notes that if the user doesn’t have permission to view PHI, the analytics tool should display only nonprivate data.
  • Medical text analytics tools should integrate medical terminology to improve the scope of searches. For example, when a user does a search on the term “diabetes” the search tool should automatically be capable of displaying results for “NIDDM,” as this broadens the search to include more relevant content.
  • Text analytics algorithms should do more than just find relevant terms — they should provide context as well as content. For example, a search for patients with “pneumonia,” done with considering context, would also bring up phrases like “no history of pneumonia.” A better tool would be able to rule out phrases like “no history of pneumonia,” or “family history of pneumonia” from a search for patients who have been treated for this illness.

The piece goes into far more detail than I can summarize here, so I recommend you read it in full if you’re interested in leveraging text analytics for your organization.

But for what it’s worth, I came away from the piece with the sense that analyzing your clinical textual information is well worth the trouble — particularly if EMR vendors being to add such tools to their systems. After all, when it comes to improving outcomes, we need all the help we can get.