The CEO of Masimo speaks with WebMD CMO John Whyte, MD, MPH, about how wearables and AI can advance home-based care.
This transcript has been edited for clarity.
John Whyte, MD, MPH: Hello. I'm Dr John Whyte, the chief medical officer of WebMD, and you're watching Change Makers: The Future of Health. What does the future of healthcare hold over the next few years? Will we see a shift toward home-based care over hospitals? Will wearables become the go-to for diagnostics? Amidst the uncertainty, Joe Kiani, founder, chairman, and CEO of Masimo, is confident that he has the answers.
I caught up with Joe in sunny Southern California to dive into his CEO playbook, the game-changing impact of artificial intelligence (AI) in healthcare, the promising realm of wearables, and the battle against medical errors. Yet what truly impressed me was the unique way that Joe thinks about problems. He has a remarkable journey from immigrant — knowing just a few words of English — to becoming an industry powerhouse.
Driven by a passion for solving big problems and championing justice, he talks about the need to be an agent of good. He's also introduced me to this concept of "microfixing" that can empower all of us to make a difference.
Whyte: Joe, welcome to Change Makers: The Future of Health.
Joe Kiani: Thank you, John. Great to be with you.
Whyte: You've been talking a lot about the need to move medical care from the hospital into the home. But you started out with focusing on the hospital. So how did your thought process evolve?
Kiani: Great question. Our first goal was to make noninvasive monitoring accurate and reliable. Once we reached that goal, we began thinking about the best way to really take care of people. Twenty years ago we had the Blue Sky sessions: What should healthcare look like 20 years from now?
Whyte: That was 20 years ago?
Kiani: Yes, almost 20 years ago. You happen to be interviewing me on the 35th anniversary of the incorporation of Masimo. So, yes, we began thinking about it and imagining about how to solve the problems that are there today: errors of omission; overburdensome data; alarms hitting the clinicians in the hospital.
And there's what I call the "tyranny of now," where decisions are made based on that moment, instead of taking into account the history of the patient and the historical data that came with the patient.
Whyte: But did you always think that this eventually is going to be able to be done in the home? Or has it been more in recent years, as the technologies evolved, that the home might be the better place instead of the hospital in some circumstances?
Kiani: The original goal was to create more information about the patient as they come to the hospital. We wanted to get their baseline at home. We wanted to know what their resting heart rate was. What was their normal temperature? We're not all 98.6°. So that way, the AI database we were creating, called Halo, could take advantage of that data — maybe even the genotype — to then allow the clinician to know exactly what is wrong with this patient.
Call it personalized monitoring — precision monitoring. Not just precision medicine, but precision monitoring. That was the original goal. And then we began seeing that this technology we created for the wrist is so good. It really is continuous. It's really accurate.
Whyte: It's personalized.
Kiani: Personalized. And with COVID we began seeing how care can now be done at home, maybe better than at hospitals, maybe better than at physicians' offices. And we began thinking about how to accelerate that: How do we take it to the home faster?
Whyte: What's the barrier to doing more in the home? We talked a little bit about it beforehand. Is it reimbursement — that people don't want to pay for data that's collected at home? Is it patient acceptance? What I've learned over the years is that sometimes someone's home is kind of their sanctuary; they don't want to associate it with healthcare. Is it physician acceptance?
There's not a way to get that personalized, continuous data that you have on your wrist right now into the right place on the medical record. What do you think is the biggest barrier that's preventing us from change in how we deliver care?
Kiani: First of all, I think people like being taken care of at home, and I look at, historically, how clinicians used to come to the home, whether it was the neighborhood, person, the witch doctor, or the real doctor. So, really, what has kept monitoring and care away from home has been a slew of problems, like too many people, too much traffic.
Thirty years ago there was lack of reliable internet, or the days of dial-up modems. I think we've come to a day and age when we have reliable communication and we have microprocessing capabilities that we couldn't even have dreamed of. We can do videoconference calls at rates that we never dreamed of.
And then we also now have, thanks to Masimo, reliable monitors, so that you don't need a clinician to figure out what's really going on. So, I think the barriers have dropped. And now with the advent of AI that's become ubiquitous, which is really pattern recognition, we can finally give people at home the same kind of measurements — with some AI on top — that can help them figure things out. And if they need more care, they dial up to their doctor, dial up to the best doctor in the world — whatever they're looking for — and get most of what they need done at home.
Whyte: I'm glad you brought up AI because you've been writing about how AI can prevent medical errors. But as you and I both know, a lot of the discussion right now for AI is really about almost as an assistant. It's going to help with scheduling and reduce no-shows, or it's going to do the denial letters, not recognizing that insurance companies are going to use AI to write the response to the denial letter that someone used AI to write.
It's not harnessing the power to structure unstructured data and provide those diagnostic and therapeutic recommendations. What's the challenge there? Are we using AI in the right way right now?
Kiani: I guess it's a good thing that we all think differently. I can't even think about the things people are looking at using AI for. Like you, John, I think AI can be an amazing tool for picking up on patterns and reducing medical errors.
Whyte: And that's what you're doing?
Kiani: Yes.
Whyte: Why aren't more people doing that, then?
Kiani: Well…
Whyte: Is it fear? Is it "don't get in my lane," in terms of the doctors not wanting to give up any authority? Is it fear of malpractice? Is it that we're just holding AI to an unrealistic standard of perfection, when we currently don't have perfection in clinical care?
Kiani: I think the tools have not been available. I don't think that doctors are pushing back. They see that we are overwhelmed by patients. They see that we're going bankrupt trying to care for patients. I think the doctors and nurses that I speak to are cheering us on. They want more care at home. They want the use of AI at home.
They want the use of AI in their hospital. In the past, if you think about the problem with AI, first it was the lack of the tools; second, there is this whole walling off of data that companies like mine used to do in hopes of monetizing their data. Well, if everyone is walling off their data, then it's impossible for AI to look at all the data and help people figure out what's going on.
One of the barriers that we helped bring down is the lack of data availability, because at the end of the day it's the patient's data. And it should be used for their care, not for each one of us to try to see how much we can make off of it. Now, with 90 companies pledging to share their data, I think there is an ecosystem for people to be able to develop algorithms like Halo, which we developed to look at everything coming from the monitors, coming from the infusion pumps, anesthesia machines, imaging, blood work, to help clinicians figure out patterns and problems before it's too late.
Whyte: Let's use a practical example related to opioids. And we know the challenges of opioid treatment — opioid overdoses. You're using this strategy of algorithms, looking at data to address it. Tell us a little bit about these tools that you're using around opioids.
Kiani: Absolutely. In fact, we do use AI with our Opioid Halo device.
Whyte: That's why I brought it up.
Kiani: Thank you for asking. It's the first and only FDA-approved device to help reduce opioid-induced respiratory depression. People are struggling with opioids. Opioids reduce pain. Well, guess what other pain it reduces: that pain you feel when you stop breathing when CO2 is increasing. So, because of that, people die in their sleep because they forget to breathe; it doesn't hurt when they don't breathe.
With Opioid Halo, we have looked at the patterns of drops in SpO2, changes in pulse rate, changes in other variables underneath, to detect when you're going into that state. And when you are, we try to wake you with our own alarms.
And if you don't respond to that — which, by the way, many people do; they won't even need Narcan because they'll wake up from it — then we send a message to the people you've preassigned to get the alerts. If they don't come to you in time, then the alert goes to the nearest ambulance with your location to come rescue.
So, this is a great example of how AI and reliable monitoring can help save lives. Last year, approximately 110,000 to 117,000 people died from opioid overdose. What if we could reduce that to zero or even to 20,000?
Whyte: You have a great way of thinking about problems. For the past 2 weeks, I've been studying Joe, reading about him, watching videos. I watched a video that you did for a TED Talk 11 years ago; you talked about this concept of microfixing. Do you remember that? Explain to us what you mean by that.
Kiani: I doremember the talk. As many young people are, I was an idealist, and I was seeing all the injustices of the world, waiting for the solutions to come — big, radical solutions. I noticed that sometimes those things caused our own problems. And I began thinking that if we could all make small improvements around us, every one of us tackle the little problems we can tackle, then maybe eventually all the problems are solved because some of us can tackle bigger problems than others.
The idea of microfixing, and the way I approach problems, is that when I come across a problem that I think I can solve, I feel compelled to go after it. I wish everyone would find their own microfix and go after the problems that they think might be a little bit bigger than them but that they can fix. If we all did that, imagine 50 years from now: We might have a very idealistic world.
Whyte: What's an example now where people should think about this concept of microfixing? Is it for AI? Is it for digital tools?
Kiani: In a professional sense, in the world that I am in, I find that I have several tools that nobody else has. I have this technology that gives us accurate data: pulse oximetry data, ECG, EEG, and so forth. I also have spent 20 years developing the AI algorithms for Halo, and we also have access to this incredible video compression/decompression technology. We have this cloud we've created. So I feel compelled that I've got to take all those solutions and help usher in 22nd-century healthcare. And what is that 22nd-century healthcare? When you and I are not feeling well, we figure out what we need to do at home. And only if there's something that needs to be done to us dowe go out to the hospital or to a specialist. I want to put together the tool set — not just these; there are other things coming — that helps you figure out everything you need to figure out at home. And then, second, when you go to the hospital, I want all that information to go with you, including your genotype, your phenotype, so that someone who doesn't know you can use AI systems like Halo to help them know whether an oxygen saturation of 93 is really dangerous or whether, because you're normally 95, it's not that bad for you.
Whyte: When are we going to get there? Because we've been talking about issues of interoperability. That's something you've been referencing ever since I've been a physician — for 25 years. You're an optimist by nature. I know that from having talked to you. When are we going to get there, Joe, tothis vision that you have?
Kiani: I'm always a little too optimistic. Normally I'd say 5 years. We can get there in 5 years. But what I've noticed is that really consequential changes happen in 10 -15 years. So, I really believe that in 10-15 years, it will happen. And by the way, when you go to the hospital, you will be able to go home a lot earlier because these tools will exist in your home.
Remember, the longer you're in a hospital, the more likely you are to be subject to a medical error. The third leading cause of death in our country is medical errors. So I want to get people in and out of that hospital as fast as we can. AI can help do that.
Whyte: Much of Change Makers is about leadership, and you have a fascinating story. You came [to the United States from Iran] at the age of 9. You knew only three words of English. You said you wanted to be a doctor but chemistry did you in, so you became an engineer. You graduated high school at age 15. And what some people may not know is that your parents went back to Iran when you were 14.
You talk about how your sister helped take care of you and she was tough. She had curfews. I like that.
Kiani: Just a year older than me too — that's the crazy thing.
Whyte: How did that impact how you approach problems?
Kiani: I think I've lived in a high-problem state for many years of my life, and I think it made me pretty tough. But I also had to reflect many times as a young person: What does it all mean? And recognizing that death is inevitable; 100 years from now, unfortunately, everyone around us won't be here.
You just realize that you've got to take your best shot at things and be an agent for good. Just try. If you fail, you fail. What does it matter? So, that's how I approach things and I think I have a strong set of guiding principles: integrity, ethics, keeping my promises, and thriving on fascination and accomplishment, not power and greed.
It's about trying to make every day as fun as possible. Improving yourself every year. And don't forget that we're given a chance to help each other, and my effort is to help patients. My challenge is to help people. Even though I couldn't become a doctor, I still want to help people.
Whyte: Being an engineer and studying engineering is just as good. You talk about how, in many ways, you wanted to address injustice from an early age, and that you enjoy talking to people, getting to know people. You've talked about how you were fired as a busboy, one of your first jobs, because you talked too much to people. What is it thatyou like about talking to people?
Kiani: I know it sounds corny, but it's those wonderful, happy smiles and reflections we give each other that really matter. It's showing love to each other, showing kindness to each other. And I really feel like it can be infectious: If you show kindness toward me, I'll show kindness toward the next person.
If, someday, we do start genetically altering each other, then get rid of the mean gene and emphasize the kind gene. By talking to people, by hearing them, not only can you learn from them — you can learn something from everybody — but you can hopefully listen to them, see them, hear them, and help them on their journey.
Whyte: If I walked around this building and asked people, "What's Joe's leadership style?", what would they tell me?
Kiani: I don't know. I hope they would tell you that I lead by example. I hope they would tell you that I'm obsessed with making things better, helping people. I hope they would tell you that I'm kind. And that I appreciate every one of them. And that we wouldn't be here without everyone.
Whyte: We're here on the 35th anniversary of Masimo. What's your reflection on these past 35 years, and what do the next few years hold for you?
Kiani: It's just incredible. I am so proud of what we have accomplished. Our technology has eliminated blindness in the neonatal intensive care unit; 2000 babies a year in the United States were going blind because of retinopathy of prematurity, because pulse oximeters were falsely reading too low when they were wiggling, and the nurses and doctors were increasing the oxygen in those incubators. That's gone.
We have helped detect critical congenital heart defects in newborns. That couldn't be done before. They had to do echo, which nobody did. Now, with pulse ox, the accuracy is such that a pre-post ductal difference of 3% or more tells them there's something wrong. So, I have a lot to be proud of. We didn't just stop with pulse ox. My team and I brought something we call Rainbow, the only technology to measure hemoglobin noninvasively and continuously: carbon monoxide, methemoglobin, pleth variability index (PVi). That little tricorder we saw in Star Trek — we have made it and it's there for people to use. A hospital in France reduced mortality by 30% using our technology 30 and 90 days after surgery. I look to that and think that could be enough. We could just sail into the sunset and be proud of what we did. But I look at the next 35 years and what we just talked about: taking care to the home; bringing AI all around, from home to the hospital, to help clinicians detect problems before it's too late to help people live healthier, longer lives.
I think we're just starting, and I'm excited about what we're going to do in the next 35 years, as the team moves on with this incredible culture of solving problems that other people think are unsolvable.
Whyte: Why do you think differently from others when it comes to health?
Kiani: I don't know. That's a good one. Why do we think differently? Part of it is, I think it's a waste of life to try to do "me too" stuff. I think we have gifted people here. We've got to go after the problems that other people think are impossible. We've got to improve the science, improve medicine, by solving what people call unsolvable.
Otherwise, I think we're wasting time. The one thing I'm really proud of is this building. If this building weren't here with this team, a lot of these innovations wouldn't be here. Most of the companies around me, there are five other companies doing what they're doing. I think it's a waste to just copy things that make things slightly better instead of going for the hard problems.
Whyte: Joe, I want to thank you for taking the time today to share how you're thinking about changing the way we deliver healthcare.
Kiani: Thanks for having me on your program, John. Pleasure to meet you. I feel like I've found a like-minded individual across from me.