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Sourcery · 5 min instead of 1 h 10 m · Oct 14, 2026

How Cadence's remote monitoring saves Medicare $2.5M a week

Nworah Ayogu

Partner, Thrive Capital

Physician who ran Amazon Clinic, was Amazon Pharmacy's first chief medical officer and was on Cityblock Health's founding team.

  • Molly O'SheaHost · Founder, Sourcery

    Ex-Upfront Ventures investor; has interviewed Alex Karp and Palmer Luckey.

About this segment

Cadence pairs home devices, AI monitoring and clinicians across 7,000 care sites, cutting hospitalizations 25%. Its AI med recommendations match prescribers 98% of the time, and it intervenes at the moment of the reading.

From “Thrive Capital’s Dr. Nworah Ayogu on Why Neuralink Is More Interesting Than SpaceX”, Oct 14, 2026. Watch the full episode

“So the key thing is I need to call you right when you're taking the blood pressure measurement because now you're in that mode.”
Nworah Ayoguat 1:00:14 · Sourcery1:00:14

Takeaways

  1. Patients spend 8,000+ hours a year outside the doctor's office; monitor those hours
  2. Results: 25% fewer hospitalizations and $2.5M saved for Medicare every week
  3. Calling at the moment of the reading raised patient contact rates by 70%

In this episode

Full episode
  1. 40:00Early reasoning models solved hard diagnostic cases doctors often miss2:47
  2. 55:43How Cadence's remote monitoring saves Medicare $2.5M a week5:24

  3. 48:08The US spent $40 trillion in a decade with no life expectancy gain3:36Up next

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 55:47

    I'm so curious from your perspective, seeing on the private side of all these companies develop new innovations through many different types of healthcare, what have been the biggest outcomes or the biggest impact that you've seen on outcomes within the portfolio? Leo? Yeah. So one of our companies, Cadence. So what Cadence does is they're a remote patient monitoring company. So they send patients home with hardware. So they'll mail hardware to a patient's home. So think of a blood pressure cuff, a scale. That way they're getting kind of continuous data from these patients who are at home. And these are fairly sort of sick patients.

  2. 56:26

    Now, beyond the hardware, they also have a system behind them. So they have both AI that is monitoring these signals at all times. And then they have people that are also watching and kind of interacting as well that the AI can kind of escalate to. The other thing they've done is I think there are people who believe in building in different ways. Some people believe you build outside the system. Some believe you build with the system. Cadence is built with the system. So Cadence works and partners with health systems. You know, their partner, they're in about 7,000 sites of care today, over 100,000 patients who they're actively monitoring at all times.

  3. 56:55

    and they integrate in the EHRs of these patients. That way the doctors are also aware of sort of what's happening. So they're both monitoring you at home, but they're also bridging your care with your doctor, and they have kind of AI monitoring and overseeing all of it. So that is Cadence's model. Think of it as the fact that, you know, let's say you see your doctor four times a year, right? That is four hours, if you're lucky, let's be real.

  4. 57:20

    It's more like one hour because most visits are 15 minutes. But let's be generous. four hours, because your doctor spends an hour with you every time of your time of the entirety that's spent there. Most of the other 8,000 plus hours of your year are spent outside of that doctor's office. So if we're actually going to change your care, we need to be monitoring you at all of those moments. And that's Cadence's special sauce is being able to actually monitor you at all of those times outside. So if you measure your blood pressure and your blood pressure is kind of high, or let's say you have heart failure, and for heart failure, We need to know your weight so that we can make sure that your fluids are right.

  5. 57:55

    As you step on that scale, we can see, huh, your weight's higher than it normally is, or your blood pressure is too low or it's too high. It can intervene right away. And with that, they've been able to see, and they've had this published in the New England Journal of Medicine, the Journal of Cardiology, the Mayo Proceedings. They found that, one, they've been able to reduce people's hospitalizations by 25%.

  6. 58:15

    Wow. They've been able to increase the amount of folks who actually have their blood pressure controlled, which prevents you from getting strokes by over 80%. They've been able to reduce people's A1Cs and sort of diabetes by almost a full point. And I think one of the other things that's been amazing is they're also saving folks money, the healthcare system money. They save Medicare $2.5 million every week.

  7. 58:39

    Every week, $2.5 million. So they are both reducing costs and kind of increasing outcomes. And this isn't outcomes like, you know, you feel better, which matters. Patient experience matters. But these are hard outcomes in terms of you being in the hospital. Is your blood pressure controlled? What's your A1C? Are you having less strokes? These are hard, hard outcomes. And it's amazing the way in which they do it because people talk a lot about, you know, doctor, how do doctors interact with kind of AI and sort of what's the system?

  8. 59:04

    Is it, you know, which is better? Is AI better? Is this doctor better? Who's better at diagnosing? And what they've said is, no, no, no. The real question is how do we integrate these two things so that everyone is doing what they're best for? So they have these new AI agents now who are sort of driving some of the med titrations. And what they found is that they actually, what the AI does is it'll learn all of that doctor's kind of practicing patterns over time.

  9. 59:27

    And what they have now is a 98% concordance with the prescriber and the doctor. So when the prescriber looks at what they would have done, 98% of the time the doctor agrees with the recommendation that AI is putting forward to do the prescription. So they're truly working kind of syntonically together. I think the other thing that's interesting is that they found that they have a – they've had a 70% increase in the amount of getting cold of folks with AI.

  10. 59:56

    So what they found is that when you measure your blood pressure, because the agents are always monitoring it, if your blood pressure is high, but then I call you an hour later to say, hey, your blood pressure is high. Are you feeling dizzy? Because if you're feeling dizzy, this might be a more serious thing. Or maybe you need to take this other medication. If I wait an hour, I might not get you because you might be playing bingo.

  11. 1:00:14

    You might be at Trader Joe's. You're playing with your grandkids. You're not going to answer the call then. So the key thing is I need to call you right when you're taking the blood pressure measurement because now you're in that mode. And with AI, they can do that. They can intervene at the moment they get the signal. They can get the signal, process it, go through your pass charts to say, are you someone whose blood pressure just runs high?

  12. 1:00:32

    160 for you would be a problem. 160 for someone who's always at 160, that's something that matters, but we're not going to change your medication for that sort of right away. So they have that kind of broader context. And I think that's the power of what they're building because they've been able to integrate your doctor, your EHR, your health care system with their agents, with the devices that are in the patient's home.

  13. 1:00:55

    They're actually able to bring kind of those two worlds together. That's incredible. It's kind of, you know, if you asked a 10-year-old what should health care be like, I feel like cadence is what they would draw out.