Today we look back to 1988 to see if we are still making the same mistakes from 1988.
Today in health, it we're going to take a look at the past. In order to determine, are we still making the same mistakes we have made so many years ago? My name is bill Russell. I'm a former CIO for a 16 hospital system and creator of this week health set of channels, dedicated to keeping health it staff, current and engaged. We want to thank our show sponsors who are investing in developing the next generation of health leaders.
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And we thank you in advance for your generosity. All right. Had a couple days off, long weekend, we all have a long weekend. Hopefully, hopefully you had a long weekend. And, , we were just going through stuff. We're going through stuff in the house, doing the little, , cleaning and whatnot and came across this magazine. $2 time magazine.
Why this mouse is smiling. It's a time. , from April towards. 25th, 1988. And it's a story of, , Michael Eisner's turnaround of the magic kingdom. Is the reason I bought it. I was a huge, , I did, , in my investments class in college, I, I researched Disney. And I feel like this was my best stock pick ever. I researched Disney, Michael Eisner had been appointed. , there were some turnaround things going on and essentially I did a presentation on Disney to the investment.
Club and to my class and recommended that Disney was going to be a great stock for many years because Michael Eisner was going to turn it around. And if nothing else, they had real estate that was worth well more than what their stock was valued at. And, , got an a in that and whatnot. And so I was a huge Disney fan.
I'm not going to read that story, although it is a fascinating story. Again, April 25th, 1988 at bet. When you tote tuned in this morning, You didn't think we were going to go this far back. But, , just after the story, there's a page called technology. And there's two stories here. I'm going to read a little bit from both of them, because I think we can learn by looking back.
And determining, are we still making some of this same mistakes? So here's an interesting one. Reach out and see someone. Picture phones. I've been just around the corner for 30 years now. They're finally starting to appear in the U S homes and offices. Since last fall Mitsubishi electric of America has sold 64,000 of its new visitable units.
A $400 device that looks like a TV with a four and a half inch screen. But also has a built-in camera lens and a cord that plugs into a telephone Jack. Callers who pose in front of the visitor and push the button marked, send Ken swap black and white snapshots of each other. Over the phone lines provided, of course that the people they're talking to half the machines as well, some visit tells.
Have been sold to law enforcement agencies, which find them handy for checking mugshots. But most have been snapped up by grandparents, traveling executives and other folks who do not see as much of their loved ones as they would like. And that's the first article. Let me hone in on one thing here.
Because we're still making this mistake. In fact, I talked to a CIO. And I talked to a CEO of a company. , and I heard this story play out and, , I'm going to come back to it because I talked about it a couple of weeks ago. But, , listen to this. , Provided, they are talking to someone who has the machine as well. This is a proprietary.
, visible telephone kind of thing. You needed to have the same device on both sides. The world has changed to software. Software is everything. The hardware is nothing. Yes, it needs to meet specs, but the hardware is nothing. Any software manufactured today. That is tying or any hardware manufacturer today that is proprietary, that is tying their use of their software to the hardware is a problem. They are not living in this century.
Everything is software agility is software being able to adapt as software, being able to apply artificial intelligence to it is software based. And I come back to this example over and over again. When I hear of companies that have tied their hardware and their software together, specifically nurse sitting specifically in room cameras. I'm hearing these in-room camera systems being tied to the software. Ask this one question when they sell you the cameras, ask this one question, can I take the video feed and feed other software applications? If the answer is no run run as far away from that company, as you possibly can there, their hardware software is proprietary. You do not want to start installing hardware that can only talk to one system.
In , your rooms. This is what we've been doing for decades. This is the reason when I became CIO at St. Joe's we had 900 applications in 1800 instances of those applications. , because so much of the hardware was tied to specific software and we had all this just junk. Because healthcare thinks we're different and we're not different.
And the reason we're slow is cause we're, we're tied down by so much legacy equipment and legacy hardware. And this is happening today. You will walk by their booth at the next conference. You're going to say, boy, that's advanced. And ask them. Is the camera separate from the software. And if it's not separate from the software that is not advanced, you've just traveled back to 1988 and the visit telephone.
And you're considering buying that your job as the technologist is to make sure that your doctors and your nurses don't fall in love with that software, because if they do fall in love with that software, they're going to be ripping it out and replacing it in five years. And that's your fault. Okay. I just want to be real clear on that. That's your fault.
Let me give you the next story. It's really interesting. , the next major battle rat, a new breed of chips challenges. 25 years of computer design Silicon valley has, , well, anyway, it's some fluffy language here. And it talks about the fact that Motorola is coming out with the 8,800 chip 88. A thousand chip, 88 0 0 80 8,000 ship. I don't remember this ship, but essentially what it's known for is it's a risk-based processor.
And we're going from these bloated, , instruction sets to, , reduced instruction, set computing. And this thing is the hottest thing since sliced bread. Again, keep in mind this articles. , April 25th, 1988. And let me give you the last couple of paragraphs. At first, the industry was reluctant to switch to risk.
, but the new crop of chips has made believers out of almost everybody son, a company, best known for its engineering, , computers. I got into the chip business last summer when it began licensing a risk processor to at and T Unisys and Xerox. I'm going to keep naming these companies. Cause none of them around today.
And if they are around, they're not producing, , computers or chips. Okay. , so let's go on from here, MIPS, which introduced its second generation of chips. Last month supplies, microprocessors to tandem prime and Silicon graphics. Hewlett Packard has built an entire line of computers around risk technology, most important and most important. IBM.
Is making a major commitment to risk. IBM vice-president Andrew Heller suggests that risk technology could produce startling advances in electronic speech recognition. Machine vision and artificial intelligence, all of which requires super fast microprocessors assessed Heller computers that can listen and talk back and recognize objects onsite.
Are not so far fetched risk will help make all of that a reality. And it's going to happen this century.
Gosh, where do, where to start? Let's start with the last paragraph, which is about IBM. And if you wonder where IBM comes into healthcare and says we are. We're essentially going to cure cancer. We're going to change how healthcare is, if you wonder where that started, if you wonder where that provato started.
Oh, gosh, you just go back to this issue. April 25th, 1988.
Where they essentially say risk technology could produce startling advances in electronic speech recognition, machine vision, and artificial intelligence. And, oh, by the way, we're going to see that this century, which we did not see this century, in fact, we're seeing it now, which would have been. 35 years. So he was off by, I don't know, 23 ish years for this to actually become a reality. , Why was he so off? On this. Because, yes, the hardware is the foundational element that we needed, but we are at scale now.
Cloud computing has taken us to scale. There's almost nothing we can't do that requires more computing, more computing, more storage, more processing. Just we can do it. We're at scale. Now that we're at scale, everything is software. I'm going to keep coming back to this. Everything is software. And we need to start thinking this way, software gives us agility. Software gives us the ability to change things.
, you know, the software defined data center, think of your data center, your architecture as software. Your people should be able to program things. They should be able to do things on their phone that used to require a computer. They should be able to automate things. Why should they be able to automate things? Because it's software and automation on software is a natural thing to occur.
It's no longer about the hardware.
If you are still talking about hardware, you are living a decade ago. If not two decades ago. Everything is software. Everything should be software. Your network should be software, software defined network, software defined data center, software defined PACS software. , defined, , interoperability suffered everything is software defined.
So in order to change that mindset, we need to be looking at the world as if it is software. Think about this. I run a very powerful computer on my desk. I could just, as in fact, when I travel, I travel with a computer that is probably, I don't know, a fifth, maybe even a 10th, as powerful as the one I have on my desk.
Again, that's legacy thinking because the computer I have that I travel with. Outside of the screen size is. , equally as adept. Why is it equally as adept? Because everything we're doing, we're doing in the cloud,
including the recording of this podcast is being transcribed in the cloud by AI. And none of that software is running on my machine. In fact, if I look at all these windows that are open on my machine, they are all portals into the cloud computing in some way, shape or form. Software. Everything is software. Make sure you ask the question. Do I control the data? Do I control the flow of data?
The flow of data is what feeds your software engine. And when you have proprietary devices in your healthcare system. That limits your ability to handle and control. The flow of information,
you need that information to flow seamlessly into your software. Have it be processed in an out, in the form of insights in the form of workflow, in the forms of automation. That is architecture. That is what we mean by architecture.
If you don't have an architect who understands the importance of software and data flow. You're likely focused on the wrong things. If you're talking about switches, routers, hubs, data centers, you name it, hardware. Hardware related assets, you're focused on the wrong things. It is so important to get this right.
Make sure we stop. Installing proprietary hardware. I know it's healthcare. I know there's a ton of it's still out there. You just have to ask the question. The information and the data that's coming into this, can it be utilized by other systems? Do we have access to all the data? Do we control how the data flows in and out of the, that hardware?
And they're gonna say, well, it's FDA approved and those kinds of things. Okay. That's fine. I want the data to flow out of that. And into my software architecture so that we can apply artificial intelligence machine learning to it so that we can utilize the tools that are available to us. Now through cloud computing.
To, , really make healthcare better for everyone.
Anyway, I thought I'd, , share with you. This is what happens when you give me a couple of days off. I go back to 1988. , but it was interesting. It's I think sometimes we look at the past. , the other thing I take from this article by the way, is things are moving a lot faster today than they did back then.
There a lot of the foundation wasn't in place. And once you get to scale, then things start to really happen. We did not have the computing power, even with this advent of risk computing to do the things that the IBM executive talked about back then, but we do now. We do because we're at scale with, with regard to all of the hardware, things that we've talked about, bandwidth.
, the compute storage processing. , you name it. We were at scale. And since we're at scale, we are doing some amazing things. With software do not let your data do not let those things get locked up and proprietary hardware. All right. That's all for today. If you know, someone that might benefit from our channel, please forward them a note. They can subscribe on our website this week out.com or wherever you listen to podcasts, apple, Google, overcast, Spotify, Stitcher.
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