Empowered Patient Podcast

Dr. Ravi Kapur, Co-Founder and CEO of AutoIVF, describes the current state of IVF as an expensive artisanal process with limited access due to structural constraints and a shortage of highly skilled embryologists. Bringing automation to the environment increases lab throughput and lowers costs, enabling a decentralized model where eggs are collected at an OB/GYN office. This data-driven technology can recover viable eggs that may have been discarded in the past, potentially improving success rates, greatly expanding access, and standardizing best practices across clinics.

Ravi explains, "Our mission is to expand access to fertility care by transforming IVF into a scalable, automated, and standardized platform. So the big picture goal here is to democratize IVF, enable affordable access to all patients who can benefit from IVF."

"Some of the big problems in IVF today are limited access and long wait times. This is in a demand-limited market. It's a supply-limited market, structurally constrained. Automation is going to enable increasing lab throughput. Automation will enable more cycles for the lab or embryologist, and automation enables uniquely meaningful, low-cost expansion into underserved regions."

"It's a very artisanal process. It requires a small pool of very highly skilled radiologists, and it takes years of training to get to that level of scale. What we aim to do is automate best practices into technology, which then drives standardized systems. And IVF is expensive. It's one of the key barriers to entry. It's $15,000 to $25,000 per cycle in the US and often requires multiple cycles to a live birth."

#AutoIVF #Fertility #HealthcareInnovation #IVF #Automation #ReproductiveHealth #FertilityCare #DigitalHealth #MedTech #AutomationInHealthcare #ReproductiveMedicine #AccessToCare

AutoIVF.com

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Dr. Ravi Kapur, Co-Founder and CEO of AutoIVF, describes the current state of IVF as an expensive artisanal process with limited access due to structural constraints and a shortage of highly skilled embryologists. Bringing automation to the environment increases lab throughput and lowers costs, enabling a decentralized model where eggs are collected at an OB/GYN office. This data-driven technology can recover viable eggs that may have been discarded in the past, potentially improving success rates, greatly expanding access, and standardizing best practices across clinics.

Ravi explains, "Our mission is to expand access to fertility care by transforming IVF into a scalable, automated, and standardized platform. So the big picture goal here is to democratize IVF, enable affordable access to all patients who can benefit from IVF."

"Some of the big problems in IVF today are limited access and long wait times. This is in a demand-limited market. It's a supply-limited market, structurally constrained. Automation is going to enable increasing lab throughput. Automation will enable more cycles for the lab or embryologist, and automation enables uniquely meaningful, low-cost expansion into underserved regions."

"It's a very artisanal process. It requires a small pool of very highly skilled radiologists, and it takes years of training to get to that level of scale. What we aim to do is automate best practices into technology, which then drives standardized systems. And IVF is expensive. It's one of the key barriers to entry. It's $15,000 to $25,000 per cycle in the US and often requires multiple cycles to a live birth."

#AutoIVF #Fertility #HealthcareInnovation #IVF #Automation #ReproductiveHealth #FertilityCare #DigitalHealth #MedTech #AutomationInHealthcare #ReproductiveMedicine #AccessToCare

AutoIVF.com

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Greg Miller, VP of Marketing and Business Development at Carta Healthcare, is focused on the multi-billion-dollar problem of manual clinical data abstraction in health systems, which is time-consuming, labor-intensive, and error-prone. The Carta hybrid intelligence solution combines AI with human expertise to surface and validate information, delivering dramatic ROI for clients through lower costs and higher data quality. Clinician adoption grows significantly once they have experienced the AI finding information they would have missed, ultimately making them more effective at their jobs.

Greg explains, "Health systems in the US, specifically, spend between $10 and $15 billion a year on manually abstracting data. And what are they abstracting data for?

"There are lots of different downstream use cases, but the most common reason is to populate clinical registries. And clinical registries are super important because they're used for accreditation of clinical programs. It's for revenue, it's for compliance and regulatory requirements. But the biggest use of registry data is to drive quality and process improvement initiatives."

"Unfortunately, today, every hospital has an abstraction function that is highly decentralized, and they have highly skilled labor, mostly nurses, who manually come through the electronic health record and other systems to find nuggets of information to answer questions in some registry system. And so it's very time-consuming, labor-intensive, and, because it involves humans, both expensive and prone to error."

#CartaHealthcare #HealthcareAI #HybridIntelligence #ClinicalAI #HealthTech #DigitalHealth #AIinHealthcare #LifeSciences #HealthData #AIgovernance #ResponsibleAI #ClinicalInnovation #HealthcareLeadership #HealthcareInnovation #ClinicalData #QualityImprovement #PatientSafety #DataAbstraction #HybridIntelligence

carta.healthcare

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Greg Miller, VP of Marketing and Business Development at Carta Healthcare, is focused on the multi-billion-dollar problem of manual clinical data abstraction in health systems, which is time-consuming, labor-intensive, and error-prone. The Carta hybrid intelligence solution combines AI with human expertise to surface and validate information, delivering dramatic ROI for clients through lower costs and higher data quality. Clinician adoption grows significantly once they have experienced the AI finding information they would have missed, ultimately making them more effective at their jobs.

Greg explains, "Health systems in the US, specifically, spend between $10 and $15 billion a year on manually abstracting data. And what are they abstracting data for?

"There are lots of different downstream use cases, but the most common reason is to populate clinical registries. And clinical registries are super important because they're used for accreditation of clinical programs. It's for revenue, it's for compliance and regulatory requirements. But the biggest use of registry data is to drive quality and process improvement initiatives."

"Unfortunately, today, every hospital has an abstraction function that is highly decentralized, and they have highly skilled labor, mostly nurses, who manually come through the electronic health record and other systems to find nuggets of information to answer questions in some registry system. And so it's very time-consuming, labor-intensive, and, because it involves humans, both expensive and prone to error."

#CartaHealthcare #HealthcareAI #HybridIntelligence #ClinicalAI #HealthTech #DigitalHealth #AIinHealthcare #LifeSciences #HealthData #AIgovernance #ResponsibleAI #ClinicalInnovation #HealthcareLeadership #HealthcareInnovation #ClinicalData #QualityImprovement #PatientSafety #DataAbstraction #HybridIntelligence

carta.healthcare

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Joe Kiani is Executive Chairman at Willow Laboratories and Founder of the Patient Safety Movement Foundation. He makes the point that the vast majority of medical harm is avoidable through the implementation of evidence-based healthcare best practices. Technology, particularly AI and remote monitoring of data from medical devices, is crucial for creating predictive models that can alert clinicians to problems and identify root causes of medical errors. The goal is to unite all healthcare stakeholders to work collaboratively toward zero preventable deaths.

Joe explains, "In the US, we lose about 200,000 people a year, and about 15 times that rate is the serious harm caused by medical errors. Worldwide, we think the number is close to three million. And the reason we call it preventable is that the vast majority could be eliminated if evidence-based practices were put in place. As you can imagine, people make mistakes, and there are a lot of medical errors that may not be preventable because there is an evidence-based practice in place to avoid them. But when it comes to things like hospital-acquired infection, VTE, sepsis, failure to rescue, CLATSI, there are known evidence-based practices that, if possible, put them in place, we might get to zero, and if not zero, we'd be pretty close to zero."

"Well, honestly, all patients are at risk. If you want to focus on those most at risk, we've got to miss the ones that really go wrong. If we can imagine someone going in for a simple procedure, even a cosmetic one, like a hip replacement, and the procedure goes really well."

"But while there's a catheter inside the artery, someone could walk in and, without cleaning their hands, touch the patient, the bacteria could enter the bloodstream and cause a serious infection. So really, you've got to create a culture of safety where you look for ways to mitigate people's mistakes, and those are what we call evidence-based practices. There are about 20 of them, starting with cultural patient safety, on the Patient Safety Movement Foundation website that people can freely download and implement, and therefore not get into these problems."

#PatientSafetyMovementFoundation #PatientSafetyMovement #PatientSafety #HealthcareQuality #ZeroHarm #EvidenceBasedPractice #AIinHealthcare #ClinicalSafety #HospitalLeadership #MedTech #CultureOfSafety #PreventableHarm #FailureToRescue #Sepsis #VTE #PatientExperience #ClinicianBurnout

willowlabs.ai

psmf.org

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Joe Kiani is Executive Chairman at Willow Laboratories and Founder of the Patient Safety Movement Foundation. He makes the point that the vast majority of medical harm is avoidable through the implementation of evidence-based healthcare best practices. Technology, particularly AI and remote monitoring of data from medical devices, is crucial for creating predictive models that can alert clinicians to problems and identify root causes of medical errors. The goal is to unite all healthcare stakeholders to work collaboratively toward zero preventable deaths.

Joe explains, "In the US, we lose about 200,000 people a year, and about 15 times that rate is the serious harm caused by medical errors. Worldwide, we think the number is close to three million. And the reason we call it preventable is that the vast majority could be eliminated if evidence-based practices were put in place. As you can imagine, people make mistakes, and there are a lot of medical errors that may not be preventable because there is an evidence-based practice in place to avoid them. But when it comes to things like hospital-acquired infection, VTE, sepsis, failure to rescue, CLATSI, there are known evidence-based practices that, if possible, put them in place, we might get to zero, and if not zero, we'd be pretty close to zero."

"Well, honestly, all patients are at risk. If you want to focus on those most at risk, we've got to miss the ones that really go wrong. If we can imagine someone going in for a simple procedure, even a cosmetic one, like a hip replacement, and the procedure goes really well."

"But while there's a catheter inside the artery, someone could walk in and, without cleaning their hands, touch the patient, the bacteria could enter the bloodstream and cause a serious infection. So really, you've got to create a culture of safety where you look for ways to mitigate people's mistakes, and those are what we call evidence-based practices. There are about 20 of them, starting with cultural patient safety, on the Patient Safety Movement Foundation website that people can freely download and implement, and therefore not get into these problems."

#PatientSafetyMovementFoundation #PatientSafetyMovement #PatientSafety #HealthcareQuality #ZeroHarm #EvidenceBasedPractice #AIinHealthcare #ClinicalSafety #HospitalLeadership #MedTech #CultureOfSafety #PreventableHarm #FailureToRescue #Sepsis #VTE #PatientExperience #ClinicianBurnout

willowlabs.ai

psmf.org

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Sam Yeruva is Founder and CEO of PyCube, a company that provides software solutions to US hospitals to digitize workflows and improve operational efficiency. He points out that many hospital processes still rely on paper, which hinders the collection of data necessary for operational intelligence and forecasting. The key to success is breaking down data silos across departments to better track assets, samples, and pharmaceuticals, improving patient care, reducing clinician burnout, and driving cost savings.

Sam explains, "PyCube is a software solutions company serving US health systems across the Continental States. We provide solutions with digitized workflows around operational efficiency of the hospitals because there are a lot of things that happen in the hospitals. A lot of things move, a lot of patients move, a lot of samples move, assets move. There are many moving parts in service environments, such as hospitals, which are well-equipped to care for patients. We help them to digitize those workflows and be more efficient. They're hearing hospitals actually running on thin margins. We assist the hospitals to utilize technology, to be more efficient, cut down the cost, improve revenue, and do what they're supposed to do normally, which they do really well, and take care of the patients. So that's where we try to assist hospitals in adopting technology, especially AI, as it is growing these days as well."

"Operational intelligence is a term coined to mean being smarter or doing things more smartly. You'll see when you go to a hospital, most of the things are still written on pen and paper. You don't get intelligence when you don't know where things are, and you don't know where data is not flowing. So we digitize those workflows so that, first of all, you use the right tools for digitizing the workflows. And then once you have that, we will instill some intelligence into the operation as well."

#PyCube #HealthcareInnovation #HospitalOperations #DigitalHealth #WorkflowAutomation #AIinHealthcare #OperationalIntelligence #PatientSafety #NurseWorkflow #InventoryManagement #HealthIT

pycube.com

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Sam Yeruva is Founder and CEO of PyCube, a company that provides software solutions to US hospitals to digitize workflows and improve operational efficiency. He points out that many hospital processes still rely on paper, which hinders the collection of data necessary for operational intelligence and forecasting. The key to success is breaking down data silos across departments to better track assets, samples, and pharmaceuticals, improving patient care, reducing clinician burnout, and driving cost savings.

Sam explains, "PyCube is a software solutions company serving US health systems across the Continental States. We provide solutions with digitized workflows around operational efficiency of the hospitals because there are a lot of things that happen in the hospitals. A lot of things move, a lot of patients move, a lot of samples move, assets move. There are many moving parts in service environments, such as hospitals, which are well-equipped to care for patients. We help them to digitize those workflows and be more efficient. They're hearing hospitals actually running on thin margins. We assist the hospitals to utilize technology, to be more efficient, cut down the cost, improve revenue, and do what they're supposed to do normally, which they do really well, and take care of the patients. So that's where we try to assist hospitals in adopting technology, especially AI, as it is growing these days as well."

"Operational intelligence is a term coined to mean being smarter or doing things more smartly. You'll see when you go to a hospital, most of the things are still written on pen and paper. You don't get intelligence when you don't know where things are, and you don't know where data is not flowing. So we digitize those workflows so that, first of all, you use the right tools for digitizing the workflows. And then once you have that, we will instill some intelligence into the operation as well."

#PyCube #HealthcareInnovation #HospitalOperations #DigitalHealth #WorkflowAutomation #AIinHealthcare #OperationalIntelligence #PatientSafety #NurseWorkflow #InventoryManagement #HealthIT

pycube.com

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Professor Mark Kendall, Founder and CEO of WearOptimo, is a pioneer in micro-wearable technology and highlights the limitations of current wearables that capture only basic signals. The WearOptimo platform uses a skin patch with painless microelectrodes to measure a range of biomarkers in the interstitial fluid just beneath the skin surface. The company's first product is a continuous hydration monitor designed to address the widespread and under-recognized health problems caused by dehydration due to lifestyle, disease, and working conditions.

Mark explains, "We are all familiar with wearables. They're everywhere these days. And when we think about wearables, we're thinking about really basic signals, like an Apple Watch, an Oura ring, or a Whoop. And they're useful for really basic things. But the challenge is that there are all manner of really important health signals out there that today's wearables, like those, are just unable to reach. So, what we're looking to tackle with our technology, our powerful platform, the micro-wearable platform, is gaining access to those key signals that today's wearables are unable to reach and really opening up genuine healthcare."

"It feels just like a sticker, as I said, but the important piece is something that's microscopic. It's microelectrodes. It's an embodiment of a field called microneedles, and I'm a founder of that field. And those microelectrodes just pierce this tough outer dead layer of skin, called the stratum corneum, and reach this location just below the skin's surface. And in that location is a rich reservoir of signals. And we measure those with bio-impedance sweeps. We pull out electrical signals from the body, and use our bespoke, novel AI model to read those signals and give us distinct health outcomes."

#WearOptimo #MicroWearable #WearableTech #HealthMonitoring #HydrationHealth # #MedTech #MicroneedleTechnology #PrecisionHealth #HealthcareInnovation #DigitalHealth #Wearables #Microneedles #HydrationMonitoring #Biomarkers #PatientSafety #PerioperativeCare #OccupationalHealth #MilitaryMedicine #AIinHealthcare #EdgeComputing #PreventiveCare

wearoptimo.com

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Professor Mark Kendall, Founder and CEO of WearOptimo, is a pioneer in micro-wearable technology and highlights the limitations of current wearables that capture only basic signals. The WearOptimo platform uses a skin patch with painless microelectrodes to measure a range of biomarkers in the interstitial fluid just beneath the skin surface. The company's first product is a continuous hydration monitor designed to address the widespread and under-recognized health problems caused by dehydration due to lifestyle, disease, and working conditions.

Mark explains, "We are all familiar with wearables. They're everywhere these days. And when we think about wearables, we're thinking about really basic signals, like an Apple Watch, an Oura ring, or a Whoop. And they're useful for really basic things. But the challenge is that there are all manner of really important health signals out there that today's wearables, like those, are just unable to reach. So, what we're looking to tackle with our technology, our powerful platform, the micro-wearable platform, is gaining access to those key signals that today's wearables are unable to reach and really opening up genuine healthcare."

"It feels just like a sticker, as I said, but the important piece is something that's microscopic. It's microelectrodes. It's an embodiment of a field called microneedles, and I'm a founder of that field. And those microelectrodes just pierce this tough outer dead layer of skin, called the stratum corneum, and reach this location just below the skin's surface. And in that location is a rich reservoir of signals. And we measure those with bio-impedance sweeps. We pull out electrical signals from the body, and use our bespoke, novel AI model to read those signals and give us distinct health outcomes."

#WearOptimo #MicroWearable #WearableTech #HealthMonitoring #HydrationHealth # #MedTech #MicroneedleTechnology #PrecisionHealth #HealthcareInnovation #DigitalHealth #Wearables #Microneedles #HydrationMonitoring #Biomarkers #PatientSafety #PerioperativeCare #OccupationalHealth #MilitaryMedicine #AIinHealthcare #EdgeComputing #PreventiveCare

wearoptimo.com

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