This Week Health

We continue on in our series of Top of Mind issues for Healthcare CIOs as we end 2021 and enter 2022. Today we look at automation.

What is driving automation in Healthcare?

  1. Competition for Labor in IT
  2. Need to move up the Stack.
  3. Labor shortage and burnout in the clinical world.
  4. The advancement of the technology.
  5. Computer Vision
  6. Machine Learning
  7. AI
  8. Healthcare Finances

In this episode we look at three areas.

  1. IT Automation
  2. Administrative Automation
  3. Clinical Automation

This is big and only going to get bigger in 2022. I hope you enjoy.

#automation #healthcare #cio #cto #cmio #AI #HealthIT #DigitalHealth

Transcript
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Today in health.

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It, the story is top of mind things for healthcare CEOs.

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And this is a top five list based on my recent interviews today.

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Number four automation.

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My name is bill Russell.

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I'm a former CIO for a 16 hospital system.

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And creator of this week in health, it a channel dedicated to keeping

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health it staff current and engaged.

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If you were listening to the series, you know, we have four new shows, four shows,

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or I'm sorry, four channels for next year.

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If you haven't already hit this week, health.com/shows.

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And subscribed to all four of the new channels.

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We would love for you to do that.

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If you haven't been listening, go back to Monday, catch up on the

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five top of mind issues for CEOs.

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And let me tell you quickly about the four channels that we have this week.

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Health news.

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His way to stay current this week health conference, we are going to have keynote

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interviews and emerging products.

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This week health community is where we hear from you about interesting

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solutions to problems facing healthcare.

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From people who are solving them.

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For example, I have guests hosts for next year.

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And we have people like Craig, Richard Advil, and a angelic Russell data

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scientist who are going to host their own shows with their own networks.

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10 to 20 minute episodes.

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So I'm looking forward to that.

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That's a new new venture for us.

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And we also have this week health.

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Academy.

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And this is where you go or send people to learn about the intersection

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of technology and healthcare.

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You can sign up again at this week.

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health.com/shows.

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All right.

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Top five.

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Top of mind issues for CIO is based on the interviews that I did at the health

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conference, the chime fall forum and at the healthcare to healthcare event.

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And.

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Just phone conversations and the various zoom calls that I do

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with CEO's throughout the week.

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Number one was labor staffing.

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three, all things, digital, digital innovation, and all the cool things

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they're doing in digital today.

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We're going to talk about automation.

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And tomorrow, Friday, we're going to talk about care venues.

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So let's start automation.

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Let's start with what is driving automation?

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Number one is that competition for labor in it?

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All right.

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So we have an it labor challenge right now.

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Number two, the need to move up the stack.

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We want our staff to be working on higher level problems, and

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we're trying to offload some of those mundane, repetitive tasks.

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And I'm still talking about it in this case, but that could also be

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applied to the clinical setting.

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Number three thing, that's driving automation, labor, shortages, and

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burnout in the clinical world.

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So we're looking at clinical automation as well.

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A number for the advancement of technology, right?

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Computer, vision, machine learning, AI is driving it.

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And if I had to think about it,

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And this isn't really on my list, but was probably a financial pressure.

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That's pushing automation as well.

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More with less.

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All right.

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So let's take a look at three areas that are seeing automation.

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Number one, it automation to administrative automation

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within healthcare and number three, clinical automation.

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All right.

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Let's start with the area.

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We're all familiar with it.

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Automation.

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This is a new it's been around for quite some time.

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Most are using VMware and Microsoft in this capacity.

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And it's had some automation capabilities built into them for awhile.

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You know, but things like a puppet get lab red hat and chef

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are also prevalent in this space.

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We've done it on site.

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But where we see this more often as in the cloud and the cloud infrastructure plays

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that are out there, it's built in, spin up a cluster for load balancing, click done.

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So it's pretty cool that way.

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And now we're applying it to our in-house.

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Data centers as well.

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We're even doing it in a multi-cloud environment and doing it across clouds.

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Very very interesting concepts.

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Let's see.

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Here are the concepts.

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The concepts are like infrastructures code, task, orchestration,

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and event driven workflow.

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These are things that are entering the vernacular.

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If you will.

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If it hasn't entered yours, here's a quick primer on them.

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So infrastructure is code.

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I just, I discussed this on the show with with several CTOs over the past year.

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Imagine knowing that in the event of a ransomware event, You could execute code

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that can rebuild the infrastructure in minutes instead of days or even weeks.

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Right?

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The code holds the key to rebuilding servers and the proper

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configurations and the software.

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Yes, you have to manage it like code with release schedules and

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repositories, but in the end, this is an amazingly powerful tool.

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And we talked to one CTO that talked about the fact that they could spin up

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their entire epic environment in minutes.

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With a click of a button.

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And that again.

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An incredibly powerful tool, especially in the Dr.

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The disaster recovery business continuity world.

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Task orchestration is just what it sounds like within many it

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organizations, there are hundreds of repetitive tasks being done every day.

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With the crunch on labor, imagine being able to automate a bunch

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of someone or even a team's job.

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So that you can free them up for some of the work that's going on done.

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Plus the added benefit that we have to talk about is giving

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them more rewarding work.

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It's a significant retention when.

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And then finally event driven workflow utilizes things like API APIs.

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That are built into much of modern infrastructure to create sophisticated

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workflows based on triggers.

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Let's see.

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I imagine if your container, I love this actually, now that I

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think about this, imagine if your container could detect an attack.

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And trigger a process that destroyed the container and rebuilt it and move

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the workloads over to the new container.

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Leaving the attacker, always having to adjust and refactor.

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You know what they're going to do.

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They're going to go somewhere else.

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They're going to go somewhere else.

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That's a lot easier.

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It's pretty cool.

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Right?

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So event driven workflow.

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So there's where those were the three.

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Primary things I would think about in this area.

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Infrastructure is code TAC.

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Task orchestration and event driven workflow.

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Like I said, this is just a primer.

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Not going into big detail.

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All right.

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Let's talk about administrative automation.

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Robotic process automation is the word.

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It's the terminology that gets used in this area.

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All right.

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The application of this is really as broad as the imagination

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here are the core components.

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The computer watches, the screen listens to the conversation, or just

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plain old watches for events to happen.

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In any number of administrative or clinical settings, and then it fires off

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events, more code that makes something happen without human intervention.

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And without human error.

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At least once the process has been baked correctly.

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You know, the old adage does apply here.

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Nothing can mess things up quite as quickly or broadly

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as a computer with bad code.

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But if you bake it right.

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You just relieved a burden of the clinician or the clinical team with a

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process that may have taken days and may now be done in seconds and the

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results passed on so that the next step in the process can fire off.

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You know, this level of automation is being used extensively in billing

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and administrative processes.

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But it can really be applied to any administrative process in the hospital.

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Take a high level event, like a patient schedules, an appointment.

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Perhaps, there are things that need to happen before that appointment

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around insurance check or information request back to the patient.

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And many applications try to build that into the software,

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but that was fairly rigid.

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RPA sits alongside the applications and connects them in, in, in the best cases.

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It connects them with API APIs, but in other cases with some

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rudimentary processes to fire off additional processes, right?

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So because it sits outside, it can be refactored many

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times for different workflows.

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Taken at the end of the process, the appointment is finished and

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the claim needs to be created and submitted for payment.

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It turns out that there are a ton of repetitive tasks.

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That get done in the process and RPA is a natural fit.

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To offload a lot of that burden.

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With really high accuracy.

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Rates, if not higher accuracy rates than than humans doing it.

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Finally, let me talk about clinical automation for a second.

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I recently interviewed the CEO for artist site, which is a startup

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with a focus on clinical automation.

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Here's what I learned.

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The data in the EHR is not as clean as we would like.

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And it's not always as real time as we would like in a clinical setting.

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So they set out to solve the front end problem, which is

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getting a set of clean data.

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To act on and the simple solution is inexpensive camera in each room.

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What can you do with a steady stream of data?

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From a clinical room, whatever the various rooms in the hospital happened to be.

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Well, you can look for fall risk, hand washing.

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You can look at a pressure wound, patients being turned or moved,

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and then you can send alerts to a nurse to move the patient.

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Right.

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But the reality is the sky's the limit because the backend

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software can be trained to look for anything and fire off a process,

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as simple as an alert to the nurse.

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Or even more sophisticated with the use of API APIs and modern systems.

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But, clearly the first thing that pops into your head is wait, how do clinicians

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feel about being watched all the time?

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And I'm glad you asked that question.

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They aren't being watched all the time.

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The code is trained to black out the identifying components

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of the clinician, and just look for what is trained to look for.

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So when you actually see the screen of what the computer is,

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seeing it, blacks out those people.

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So you don't really know who they are.

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You might say, wait, I can probably correlate the data and the video feed

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and figure out who was in the room.

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You would, if the video feed actually existed, the system processes the

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feed through AI and then forgets it.

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Destroys the video feed and no longer needs it.

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So it no longer exists quickly after the information is processed, it's gone

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and the AI engine has done its work.

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It is identified the things it needs to identify pretty interesting, right.

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I was talking to one CIO.

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Who's using this solution.

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And their legal team came back and said, Hey, we need the

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video feed from this room.

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And I said, well, it doesn't exist.

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And they said, oh, well, it has to exist.

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There's a camera in the room.

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So there's this underlying assumption that if there's a camera in the

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room, there's a video feed somewhere.

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So you have to educate people on what's actually happening.

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But at the end of the day, the CIO was able to look at the legal team and say,

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The video feed does not exist.

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It does not exist anywhere.

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It is gone.

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It's not processed in that way.

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It's not stored in that way.

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So that's interesting.

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It addresses that.

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That that concern that big, brother's going to be looking over the shoulder

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while adding an awful lot of value.

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And even value to the clinicians in terms of alerts and those kinds of things.

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And then, yeah, the obvious things like, Hey rooms empty, it needs to be clean.

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You can get a quick feed into that room to see if the work has been

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done and those kinds of things.

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So awful.

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Lot of value being created in that space.

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Well, that's the world of automation.

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So stay up to date on this one.

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That's all for today.

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