AI for Nursing Jobs, Right Kind of Wrong Book - podcast episode cover

AI for Nursing Jobs, Right Kind of Wrong Book

Dec 11, 202315 min
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Episode description

Dr. Iman Abuzeid, Co-Founder and CEO at Incredible Health, discusses implementing AI for the nurse hiring platform. Amy C. Edmondson, Novartis Professor of Leadership and Management at the Harvard Business School, talks about her book Right Kind of Wrong: The Science of Failing Well.
Hosts: John Tucker and Mike Regan. Producer: Paul Brennan.

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Transcript

Speaker 1

You're listening to Bloomberg Business Week with Krol mess Here and Tim Stenebek on Bloomberg Radio.

Speaker 2

Mike, you know there's a nursing shortage in the US, and our next guest may have a solution. A doctor Emon Abbozaid is co founder and chief executive officer of Incredible Health, and she's joining us now from where are you, Austin? I'm looking at the background. That doesn't look like Austin, not that I've really that's the.

Speaker 1

Nicest soum background I think we've seen today. It's pretty bank.

Speaker 3

Thank you, Austin. It's pretty green, all right.

Speaker 2

So what is what is Incredible Health and how are you going to solve the nursing crisis in the US.

Speaker 3

So, Incredible Health is the fastest growing venture backed healthcare career marketplace hospitals and health systems. They use our software to hire nurses and permanent roles in less than twenty days. Our mission is to help healthcare professionals live better lives and to help them find and do their best work.

Speaker 2

Oh and wait for it, Michael, they use artificial intelligence, so, which means if this were a publicly traded stock, could be like through the roof right, yeah, right, So well how does AI? What's what's the intersection of what you do and artificial intelligence.

Speaker 3

So this week we announce the implementation of generative AI across our platform, which we're really excited to do and we're also the first in our industry, right in our part of the industry to do that. There's these features really aim to just expand opportunities for nurses and to help further streamline the hiring process too. I will say that even beyond the generative AI, we do use machine learning,

we also use algorithms to drive the value here. First first area I just want to share is just our resume wizard that allows nurses to instantly create resumes in a high quality resume and seconds in our mobile app. Thirty percent of nurses start the job search process without a resume for a variety of reasons, you know, including socioeconomic reasons like not having access to a computer laptop, or not simply not knowing what a high quality resume

is what's needed. And so thousands of nurses have already used this, and so that's thousands of nurses that are no longer left behind in the job search process.

Speaker 1

And doctor how are you utilizing the AI? Are you, you know, is it a chat GPT thing or using one of these big tech products that's already available. Did you develop your own? How are you accomplishing this?

Speaker 3

Yeah, so I have a fantastic product and engineering team and they're using a GPT technology from open Ai specifically. Another feature I wanted to mention is just our customized health system outreach to nurses. So this is this is an example of a feature where that health systems can use to send highly customized messaging to nurses. It highlights you know, hospital perks and benefits and ultimately helps hospitals

really differentiate themselves from the competition. And since we implemented that, the interview requests accepted from nurses has gone off by twenty percent, So.

Speaker 2

Why limit this just to nurses and everybody use it.

Speaker 3

So the nursing is one of the is the top shortage in healthcare when it comes to just labor shortages, it's also one of the top shortages in the country, and it's definitely one of the you know, top areas that are the health systems that we work with care about the most. So we're very focused on nurses and hospitals right now in the US, of course, you know, we have plans to expand beyond nurses and beyond hospitals before now that's for now, that's our.

Speaker 1

Focus radio radio people. Yeah, they're gonna the chat cheep PT is gonna you know.

Speaker 2

The funny thing is is this, like in my career, I've been doing this, like, oh my god, forty years. I have never once had to give anybody a resume.

Speaker 1

Really, I don't know. They hear your voice, John, and then it must be they hear that Barry White voice and they're they're instantly so. But doctor, I'd like to step back just a little bit and talk about this nursing shortage. What caused that? Is it a remnant of the pandemic where you know a lot of nurses sort of had to step back from their career. What's going on that's driving this big shortage of nurses in your opinion?

Speaker 3

Yeah, So, Look, it's a long term trend that's been going on for ten years and it's projected to continue for many decades to come. What's happening is that our demand from patients and from Americans on the healthcare system continues to increase because our population is aging, but we as a country have not done a great job of increasing the number of healthcare workers to meet that growing demand,

and so the shortage is increasingly becoming tougher and tougher. Now. COVID, of course, was a demand shock, but even after COVID, even now there's still a shortage. I think you all mentioned the Jobs report. When you look at the detail in there, the biggest increase in job gains in the US is in healthcare. So this does continue, and despite the job growth, we still don't have enough healthcare workers to fill those roles.

Speaker 2

How many hospitals are using your stuff right now to end your customer base?

Speaker 3

Yeah, So we work with over seven hundred and fifty hospitals across the country, including large health systems like Age and Kaiser, Permanente, large regional systems like Baylor, Scott and White, and many academic medical centers too, like Johns, Hopkins and Cedar Sinai. We also work with over eight hundred thousand nurses, so one in four nurses in the US uses incredible health to manage their careers.

Speaker 1

And I assume to the nurses pay or is it the hospital's paying, and the nurses get it for free. What are the economics of the Yeah, it's.

Speaker 3

One hundred percent free for nurses. They can use all our tools, all our features, you know, even beyond finding a job. We have continuing education and a community for them to ask for advice and salary estimators and so on. And it's the hospitals that pay.

Speaker 2

I'm curious how you started the business and the different funding rounds you had to go through. How easy or difficult was that? And walk me through the steps that brought you into an existence.

Speaker 3

Sure, we founded the company six years ago. We've raised almost one hundred million dollars for the company, and the company today is valued at one point sixty five billion. I myself, I'm an MD by background, I've been in healthcare. I've been in technology for the last ten years of my career. And ultimately myself and my co founder, my CTO Rome Portlock, who's a brilliant software engineer from MIT. You know, we really we knew that there was There

were constant complaints from members of our family. Actually, so doctors in my family were often complaining about understaffing nurses, and Rome's family were saying, hey, I'm experienced I'm qualified, I apply to ten places I don't even hear back. We started to really dig into it. We realized the tools, the processes of technology in healthcare hiring, A lot of it's not really changed in over twenty years. It's primarily job bars. You know, post a job and hope it

all works out. But that's really tough and that's not sufficient a in an industry that has major labor shortages.

Speaker 2

Do you have additional funding rounds coming up and the expansion You sort of touched on that before, But what's next?

Speaker 3

So what's next for us and just looking at twenty twenty four is continuing to invest in our product roadmap, more extensive use of generative AI as well, to continue to expand opportunities for healthcare workers, for nurses, and to make and to streamline the hiring process. We want to make it more and more personalized, more and more automated, just make it easier for everyone to access fantastic opportunities.

Speaker 1

And I always wonder with a venture capital based company, h doctor sort of the long term ambitions are we perhaps going to see you ringing that stock market bell on I p O day someday or any any into what's to come as far as the next phase for Incredible Health.

Speaker 3

Yeah. So, our vision and our mission is to help healthcare professionals lead better lives and help them find and do their best work. So, and this is a very ambitious company. Our goal ultimately is to one day go public. But you know, a lot of work to do between now and then.

Speaker 2

All right, let's leave it there. I mean anything else to add? I think you've covered it all.

Speaker 3

Doctor, all right, thank you so much for having me. I appreciate it.

Speaker 2

That was fantastic, Doctor Iman Abuse, the co founder, chief executive officer of Incredible Health. Mike, you know we all have failures and shortcomings.

Speaker 1

Speak for yourself.

Speaker 2

I was going to say, I was going to include you in that list. By the way, our next guest has turned her failures and shortcomings into something of a science project. Amy Edmondson is author of The Right Kind of Wrong, The Science of Failing Well. I think we have to read this book because what it won the Business Book of the Year for the FT I am told that's pretty impressive. Hey, Amy, thanks for being on the program. What was your science project?

Speaker 4

My whole life has been the science project, I guess, but indeed, failure is a central thread that runs through it.

Speaker 2

And you know, we're all told in school there are no dumb questions and that we advance and learn from our mistakes. But do we really well.

Speaker 4

Yes, we really do, although we don't do it naturally. We need to be We need to learn the right mindsets and skill to actually learn from failures. I do make a distinction between failures and mistakes. Mistakes are by definition, deviations from known best practices or protocols or recipes, whereas failures can in fact be in new territory where there was no recipe and amy.

Speaker 1

I'm fascinated with the concept of studying a topic like failure from an academic sort of scientific approach. Could you could you walk us through how you did that? You know? Did you did you start with the kids who flunk your class and do brain scans on them? I'm kidding, but how did you? How did you approach this? Actually?

Speaker 4

I mean let me, let me be be more accurate. I don't study failure. I study organizations, and in organizations there are many failures. So I am fundamentally a management researcher, and one of my core passions is management decisions. And management actions that lead to preventable failures and even worse at times, that inhibit the productive experimentation and innovation activities that would lead to future successes.

Speaker 3

So I see both kinds of errors in organizations.

Speaker 4

A failure to experiment enough, necessarily incurring failures along the way, and a failure to prevent some of the preventable accidents and bad decisions that we see all around us.

Speaker 2

So I'm guessing for all this to work in an organization, you have to have a climate of openness and one that where you're not getting going to get in trouble if you venture out and make mistakes. And I don't know. For some reason, earlier today i was reading the preface to the book, and I'm thinking, like God, would this any of this apply to Congress? I don't think so.

Speaker 4

Well, you know, it's I think in earlier times it would apply to Congress. Congress is an organization just like any other. And I have to admit that most of you know, the research I've done and the organizations I've studied is done with an assumption of a good faith effort to perform well and a good faith effort to do your job, and even with a good faith effort to have a really effective organization that is serving its

clients or serving its constituents well. Mistakes and failures still happen. But when you have an organization where it no longer seems clear that the goal is to perform well and serve the public, then some of the basic assumptions of my research and my findings may no longer hold.

Speaker 1

Are there any sort of common causes of failure? Is it you know? Is it simple enough to boil them down to a few things I don't know, hubrius or you know, too much risk taking? Are there any sort of common threads that seem to appear over and over?

Speaker 4

Absolutely common? See I identify three kinds of failure. Basic failure is complex failures and intelligent failures. The third kind, the intelligent failures, are the good kind, the kind we want more of. They're essentially discoveries. There they bring new knowledge in territory that we haven't plowed yet. So it's it's they're invaluable.

Speaker 1

Could an example.

Speaker 4

Sure a scientific Let's say you're a I mean, this is maybe an obvious example, but if you're a scientist and you have and you're the leading edge of some scientific field and you have a hypothesis that something might work and be a great discovery, and then you try it and it doesn't work. That is a failure, but it is a discovery. It tells you that that hypothesis was wrong and gives you new information that you previously lacked about what to try next.

Speaker 3

That that's a science example. But in our lives, you know.

Speaker 4

Just let's say dating, you might have you might go on a on a date and have good reason to believe this could work out, but it falls short, and you can't call that any thing but an intelligent failure. Couldn't go in advance that it wouldn't work.

Speaker 2

And I got to ask this question because it's one of these market themes that we have. Where does artificial intelligence then fit into what you do and what organizations do well.

Speaker 4

Artificial intelligence, you know, essentially works quickly with a lot more data than our brains can work with. So it could it could be used to help us prevent these preventable failures that I was referring to before, the basic failures, the complex failures. It could it could help us when we're about to make consequential decisions that are either irreversible or at least very high stakes and under conditions of uncertainty. It could help us make those decisions with better data,

more informed by all the available data. And it could also help us generate better experiments, which would lead to maybe fewer intelligentailures and more discoveries.

Speaker 3

But still you'd have to have some intelligent failures.

Speaker 1

So you talk about failing, well, what's the opposite of that? What's just a failure at failing so to speak?

Speaker 4

Yeah, I mean, so there's two kinds of failures at failing, and one is we.

Speaker 2

Got to do it in a minute.

Speaker 4

So the failure the failures we get from not trying very hard, from mailing it in, you know, from sloppy work. That's the wrong kind of wrong, right, That's that's not failing well.

Speaker 3

And also the.

Speaker 4

Failure to experiment, to stretch, to grow, to try new things and therefore not failing at all, that's also not failing well.

Speaker 2

Amy, thanks so much, an absolute pleasure joining us from Cambridge. The author Amy Edmondson the right kind of wrong, and we should mention again the ft in Schroeder's business book of the Year.

Speaker 1

I'm inspired, John, I'm going to go home and fail at something. I don't know what it is.

Speaker 3

But

Speaker 2

Well make sure it's the right kind of that's that's Michael

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