What we Have Learned from Running MedFuse.io – Telehealth and Social Distancing for Healthcare Written by Patrick on March 26, 2020


Brief Note on the Video Quality & Freezing

I broadcasted from home today where the internet is not quite as blazing fast as my office and used a 2.4Ghz WiFi rather than my 5Ghz so that appears to have turned what is normally a video into a pure, “podcast.” So what you will see on the video after the five or ten minute mark is basically my frozen face on the screen looking to the right.  However – hopefully the voice portion of the video is still, “listenable.”

We are undertaking more R&D on how to run a virtual conference and a part of this effort has been running daily streams under different conditions in order to learn what the minimum specifications for running a talk from one’s home computer should be. Running a virtual conference includes working with a wide variety of systems simultaneously – folks using whatever computer they may have available, and so we have been going through this ourselves in order to understand what kinds of snafu’s happen along the way.

If you have been following along closely, you may have noticed that yesterday’s blog post video tutorial about streaming from a Raspberry Pi did not work out extremely well and in fact got chopped up.  We had originally recorded around 2 hours of video, but the final video length we ended up with was only 90 minutes!  So – we’re doing a re-do on Saturday.

The output of all of this will be a, “minimum specification document,” as well as a, “setup FAQ document” for all of our speakers and sponsors.

Telehealth and Social Distancing for Healthcare

Over the past two years, I have organized a conference called MedFuse.io which concentrates on the intersection between digital and connected healthcare data and medical (or healthcare) devices.  In today’s video I give a discussion on what were some of the high-level meta-analysis findings from that conference.  Throughout the process of running that conference I had the privilege of talking with doctors, pharmacists, long-term care practitioners from organizations like Fairview-Ebenezer, associations like LeadingAge, as well as medical device and technology experts from Mayo Clinic, Boston Scientific, Medtronic, Abbot and many different startups in the space.

I may make more video blog posts on this topic in the future, since it is such a huge area, but I wanted to start out with just a brief meta-analysis post showing some key findings, in the interests of keeping things short.  This is an incredibly complex area and one post would not do it justice.

Meta Analysis Findings

I’m going to write about some basic meta-analysis findings below, but I welcome anyone to check out kconfs.confrnz.com to see actual examples and presentations from the real experts at our previous shows.

Care Services Perspective

The “Care Services Perspective,” comes from those who are concerned with long-term care and aging in place.  This is a massive area of healthcare overall because people who require long term care, whether elderly or otherwise, typically make up for the bulk majority of healthcare utilization.  Care services have found an interest in connected medical devices and healthcare devices as well as Telehealth because there is a unique geographic aspect to this area of practice.  The two main points that I gleaned, as a non-expert, talking to experts in the space were:

  • It’s All About the Labor
    • You may have heard of the, “silver tsunami,” within the healthcare space.  You more than likely have heard of the concept we’re dealing with right now referred to as, “flattening the curve.”  Essentially, there’s just not enough expertise in the world to deal with the amount of people who require healthcare.  This was a problem even prior to the current COVID19 crisis and may remain a problem afterward, even if we are able to find a vaccine.  Granted, the problem will not be as acute if we can contain and remediate the virus – but the fact remains that there is just not enough healthcare labor, it takes a lot of specialization and schooling to train people, and so a lot of what happens is about making the best of the resources you have.  In some cases, such as with public healthcare, there’s just not enough budget and may never be enough budget for long-term care – so you get things like Dose Health which is a pharmaceutical tracker used in the public sector to improve adherence, designed and made in Minnesota, in fact – by a friend of mine.
  • Technology is Difficult to Adopt
    • While we may be quick to jump to specific solutions, healthcare facilities and long term care facilities have been burned in the past by having technology shoved in their laps and then later not being able to find value for what they paid.  There’s a perception in the technology and engineering world that since tech has improved so many things, it obviously may immediately create improvements in the healthcare space.  Well it turns out that this has not been perceived as true from these facilities.  So – what these organizations have typically done is to find more, “no brainer” upgrades such as just upgrades in WiFi connectivity, hoping that future IoMT solutions may be built which can tail onto an already ready-to-go infrastructure.  The advice for aspiring IoMT entrepreneurs and investors is to not look at long term care providers as, “distributors,” for your product but rather figure out how to take away risk from them to increase adoption of a particular solution.

Doctor and Acute Caretaker Perspective

Some doctors, caretakers, nurses and even dentists find IoMT very interesting – others find it a completely useless distraction – it all depends upon where you are on the care cycle and how it helps you, if at all.

The key take aways are: simplicity, usability and seamless integration.  Acute care-taking is very much a, “real time job,” – it requires observation, moment to moment decision making, a vast array of knowledge and tool application from multiple real-time experts, and record keeping.  Speed and accuracy is often not only a question of efficiency but also a question of saving lives or reducing problems.

Requirements from the acute caretaker perspective who are interested in IoMT, can possibly be best summed up by saying, “It’s about usability, simplicity and seamless integration and use of tools and screens.  We don’t even want to feel like we’re using technology.”

This means that a key design team from an IoMT perspective should most likely include a lot of user experience and user interaction expertise and feedback – which is hard to get because these acute caretakers are always busy – and today busier than ever before.

Taxonomy Perspective

Organizations like the University of Minnesota, Medical Alley and researchers from Mayo, as well as program managers from Google Health or Medtronic or large enterprises need a form of, “intelligence,” to understand what’s going on.  The key take away here, which I had several excellent discussions along with Dan Mooradian of the University of Minnesota Technological Leadership Institute was that having a sort of, “break down,” of where IoMT goes and how it fits in to the big picture can be helpful.

The breakdown which was discussed at one of the sessions involved, basically, “Pre-Condition, Procedure, and Outpatient.”  Another way of saying, “Pre-Condition” could be, “Preventative Medicine.”  The thought here is that IoMT practitioners need to think about where along the line of care they lie, and how their data might help other parts of the line of care, in a feedback loop if possible.  So even if your device or innovation lies within a highly non-regulated space, perhaps something as far afield as using a smart speaker to provide better care and feedback – there should be some thinking about how all of these pieces can be integrated together over the coming decades.

Key take away: the closer to the center, the closer to, “Procedure,” the more regulated, dangerous and expensive a particular solution becomes – this goes for both the device and physical manifestation of the the IoMT solution as well as the data and modeling behind it.

Patient Care Perspective

For patient care, the example I would like to give is directly from Heather Mortensen, one of our wonderful speakers.  Basically, there were a couple key take-aways from her talk.  This is another topic that definitely requires an entire blog post in it of itself, but in the interests of brevity, there are two key take-aways:

  • Patients find themselves simultaneously working with and working against the healthcare system.
  • Open Looped systems have the opportunity to become closed loop systems with feedback.

Heather gave an example of a glucose monitor for diabetes.  Previous iterations of this monitor were entirely, “open loop,” using proprietary protocols and had little opportunity for data and condition share on a distributed scale.  They were, “on premise” devices and as such the feedback and care taking associated with these devices was slow.  Contrast that with bluetooth connected glucose monitor – which gives the ability to feed data back into, “whatever” system and apply various levels of either signal processing or expert evaluation.  Connected glucose monitors give the capability to create feedback loops, closed loop systems rather than open looped systems – which opens up the ability to improve care and improve one’s own healthcare outcomes together with a healthcare provider.

Image Credit: Heather Mortensen

Image Credit: Heather Mortensen

 

Summary – Relation to Telehealth and Social Distancing

When you hear the word, “telehealth,” now – which will come up a lot – keep in mind that there’s a lot more than meets the eye.  Today we may think of it as something that will allow people to maintain social distance – as a purely preventative measure – however there are great opportunities for usage and improvement going forward.

That’s pretty much a broad 10,000 foot overview of what I wanted to say on the topic – other than delving into more specific examples:

1) It’s not as simple as it sounds to deliver.

2) There’s a whole, “pipeline” of applications and

3) Feedback loops are important to improve patient care.

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