How Digital Driver's Licenses Are About to Transform Healthcare Identity Verification

How Digital Driver's Licenses Are About to Transform Healthcare Identity Verification

In this episode of the AI at ViVE series on The Beat Podcast, host Sandy Vance welcomes back Peter Horadan [https://www.linkedin.com/in/peterhoradan], CEO of Vouched [https://www.vouched.id/], for a fascinating and forward-looking conversation about one of the most consequential shifts happening in digital identity right now. Digital driver's licenses are no longer a curiosity at TSA checkpoints. They are becoming a global standard, and healthcare is one of the industries that stands to benefit most.  From eliminating duplicate patient records to defending against deepfake fraud to solving the emerging challenge of AI agent identity verification, Peter lays out a clear and compelling vision for what healthcare identity infrastructure needs to look like in the very near future. If you work in telehealth, healthcare IT, compliance, or patient access, this episode will make you think very differently about something most organizations have never considered a strategic priority.  It is believed that about 7% of people in the United States have a digital driver's license today, with estimates reaching 30% adoption by the end of this year and 50% by the end of 2027. If you aren’t having conversations for this shift, learn why it matters and how to incorporate it into your patient intake.  In this episode, they talk about: * Seven US states are currently issuing digital driver's licenses, and over 30 have announced plans to do so * California has already issued over two million digital driver's licenses, and the EU mandates adoption across all 27 member nations by the end of this year * Digital IDs live in a secure chip on your phone, cannot be copied or forged, and require a live biometric to use * Between 5 and 15% of electronic health records either have duplicate records for the same patient or multiple patients sharing one record, and strong identity verification at intake is the fix * Vouched dramatically reduces patient drop-off rates at the identity verification step, as evidenced by MyStart Health's 40% net business impact * Digital IDs actually enhance privacy because they allow users to share only the specific attributes needed, like confirming age without revealing anything else * AI agents are already showing up in healthcare workflows, and healthcare organizations need to think now about how to verify that an agent is trustworthy, authorized by a real patient, and actually who it claims to be * Vouched released the MCP-I specification a year ago as an open standard for AI agent identity verification, now adopted by the Decentralized Identity Foundation and expanded under the name KYA-OS * By the end of 2026, Vouched predicts 40 to 50% of US adults will have a digital driver's license  A Little About Peter: Peter Horadan is the CEO of Vouched, the AI identity verification platform that’s transforming how leading Healthcare and Financial Services companies onboard and verify people—instantly and securely. Throughout his career, Peter has led the charge in replacing slow, manual workflows with scalable, automated systems that unlock efficiency, reduce costs, and create measurable impact. From digitizing expense reporting at Concur to streamlining sales tax compliance at Avalara, Peter has helped modernize core business processes across industries. His leadership reflects a deep understanding of how automation can drive growth, compliance, and customer experience at scale. Peter has also held leadership positions at Alavara, Scout Analytics, Microsoft, Corillian, and BEA Systems.

How Bland Is Replacing Legacy IVR Systems and Fixing Healthcare's Phone Problem

In this episode, host Sandy Vance chats with Isaiah Granet [https://www.linkedin.com/in/isaiah-n-granet/], co-founder and CEO of Bland [https://www.bland.ai/], for a sharp and eye-opening conversation about one of the most overlooked bottlenecks in healthcare: the phone call. Bland now handles 3.5 million phone calls a week, has raised over $100 million, including a $40 million Series B, and is backed by Emergence Capital, Scale, and Y Combinator. Isaiah brings a refreshingly honest take on what it actually takes to get voice AI into production in healthcare, why most vendors are just talking about it rather than doing it, and why the security risks hiding in third-party AI dependencies should be keeping every healthcare CIO up at night. In this episode, they talk about: * Most people call a call center because they are at the end of the line and cannot solve their problem any other way * The best voice AI systems conform to the caller, not the other way around * Intake is the fastest path to ROI for health systems deploying voice AI for the first time * Bland tracks emotional sentiment, call escalation rates, and a unique metric called utterances to measure patient experience quality * Bland does not use OpenAI or any third-party LLM under the hood, meaning PHI never touches an outside vendor * Health systems should demand that calls go live within 30 days and measurable automation within 60 days * A single third-party dependency, three steps removed from a vendor, recently led to a class action lawsuit * Always declare that it is an AI agent on the call; deceptive practices destroy the trust that voice AI depends on * The CIO role is becoming one of the most important in any healthcare organization, as AI decisions multiply A Little About Isaiah: Isaiah values community, family, and impact above all else. He believes that building for impact is what makes life. In addition to being the cofounder and CEO of Bland, he also sits on the board of the nonprofit he founded, the San Diego Chill.

How Limina Is Making Sensitive Health Data Safe for AI

In this episode, host Sandy Vance sits down with Patricia Thaine, [http://linkedin.com/in/patricia-thaine?originalSubdomain=ca] co-founder and chair of Limina [https://www.getlimina.ai/en] (formerly known as Private AI), for a fascinating conversation about one of the most underappreciated bottlenecks in healthcare AI adoption: the privacy of unstructured data.  With a background in natural language processing and privacy research, Patricia built the company from the ground up to solve a problem most organizations did not even know they had. Today, her platform helps health systems, research organizations, and payers de-identify everything from clinical notes to ambient listening data so they can train models, share data for research, and move their AI initiatives forward without putting patient privacy at risk.  If your AI initiative is stalled because of privacy concerns, this episode is exactly what you need to hear. In this episode, they talk about: * 80 to 90% of healthcare data is unstructured, and most organizations have no idea what sensitive information is hiding in it * Cloud providers require you to send your data outside your environment, and that alone is a dealbreaker for many health systems * De-identification is not just about removing names; quasi-identifiers like age ranges, locations, and diagnoses all factor into re-identification risk * The goal is to keep re-identification risk below 0.04%, not just strip out obvious fields * Training AI models on real PHI creates a memorization problem where the model can regurgitate patient information in production * Providence Health has used Limina since the early days to train patient and physician-facing chatbots safely * A mature privacy-to-AI operating model requires statisticians, product teams, IT, governance, and legal all at the table * LIMINA rebranded from Private AI because the old name kept attracting requests for on-premise LLMs, which is not what they do A Little About Patricia: Patricia Thaine is the Co-Founder & Chairwoman of Private AI, a Microsoft-backed startup that raised their Series A led by the BDC. Private AI won the Privacy Innovation Award at PICCASO 2024, was named a 2023 Technology Pioneer by the World Economic Forum, and was a Gartner Cool Vendor. Patricia is also the host of The Data Frontier podcast and was on Maclean’s magazine Power List 2024 for being one of the top 100 Canadians shaping the country.

Turning Healthcare AI from Vision to Verified Impact with Pegasus One

What does it really take to get a healthcare AI product past the proof-of-concept stage and into production? In this episode of the AI at ViVE series on the BEAT Podcast, host Sandy Vance sits down with Tushar Puri [https://www.linkedin.com/in/tusharpuri/], CEO of Pegasus One [https://www.pegasusone.com/], and Sebastian Ouslis [https://www.linkedin.com/in/sebastian-ouslis-3446b9148/], Co-Founder of ChartR Health [https://www.chartrhealth.com/], to find out. Together, they pull back the curtain on how ChartR is building an autonomous analytics platform that lets hospitals interrogate their own data across silos in real time, and how Pegasus One's SONG framework is the foundation making it possible. From managing agent drift to the very real stakes of lagging data in sepsis care, this conversation is a masterclass in building healthcare AI that can actually go from pie-in-the-sky to impact you can quantify.  In this episode, they talk about: * Why most healthcare AI projects never reach production * The real meaning behind the SONG framework * How data silos slow down hospital decision-making * Turning weeks of analysis into minutes with AI * The hidden cost of poor workflow integration * Why governance must be built in from day one * The importance of designing for real-world healthcare systems * How ChartR enables continuous analytics across hospital data * What agent drift is and why it matters long term * The role of partnerships in building scalable AI products A Little About Tushar and Sebastian: Tushar Puri is the Founder and CEO of Pegasus One, where he helps organizations build scalable AI and software products that actually make it to production. With more than 15 years in product engineering, he specializes in bridging the gap between technical innovation and real-world implementation, especially in healthcare. Sebastian Ouslis is the Co-Founder of ChartR, an AI-driven healthcare analytics platform focused on turning complex clinical data into real-time insights. His work centers on using AI to help hospitals continuously learn, adapt, and improve patient outcomes.

How UAMS Is Scaling AI Across the Enterprise with Luma Health

AI in healthcare is moving fast, but what does real, operational impact actually look like? In this episode, host Sandy Vance chats with Aditya Bansod [https://www.linkedin.com/in/adityabansod/], CTO and co-founder of Luma Health [https://www.lumahealth.io/], and Michelle Winfield-Hanrahan [https://www.linkedin.com/in/michelle-winfield-hanrahan-msn-mha-bsn-rn-b3b2593b/], RN BSN MHA MSN about this very topic. They share how the University of Arkansas for Medical Sciences [https://www.uams.edu/] is scaling AI beyond the call center and into complex, high-friction workflows like fax processing and patient access. From backfilling missed appointments to transforming referral intake, this conversation dives into what it takes to build trust, move quickly, and turn AI into measurable results across an entire health system. In this episode, they talk about: * How UAMS identified a high-impact, low-risk entry point for AI in call center workflows * Turning after-hours cancellations into filled appointments and improved patient access * Why trust in the partner matters just as much as trust in the technology * Expanding from AI call handling to backend fax automation * How AI is reducing referral lag time and improving data visibility * The power of an EHR-first strategy and working inside existing workflows * Avoiding “AI sprawl” and the challenge of managing too many point solutions * Real talk on ROI: operational efficiency, revenue lift, and happier patients * Why success builds momentum for scaling AI across departments * Practical advice for health systems navigating the explosion of AI vendors A Little About Aditya and Michelle: Aditya Bansod is CTO and co-founder of Luma Health. With a lifelong passion for building software, Bansod leads Luma Health’s technical vision and strategic direction for building a Patient Success Platform that empowers healthcare providers to serve their patients better and improve healthcare outcomes. With over 15 years of experience as a product management leader developing mobile solutions at Adobe and Microsoft, and at venture-backed start-ups, Bansod made the transition from B2B software solutions to healthcare in 2015 to have a meaningful and measurable impact on how providers use mobile technologies to engage with and communicate with their patients. Michelle Winfield-Hanrahan, RN BSN MHA MSN, is a seasoned healthcare clinical operations executive with over 20 years of experience in optimizing patient access, improving patient engagement, and streamlining clinical operations. Throughout her career, Michelle has demonstrated a strong ability to lead cross-functional teams and implement strategic initiatives that enhance the patient experience, increase operational efficiency, and drive sustainable growth. In her current role as Chief Clinical Access Officer and Associate Vice Chancellor of Access at the University of Arkansas for Medical Sciences, Michelle oversees patient access and flow from both the outpatient and inpatient setting, ensuring seamless patient flow and appointment scheduling, reducing wait times, and improving overall patient satisfaction. She has spearheaded innovative solutions that leverage technology to enhance patient communication and engagement, ensuring that patients remain informed, involved, and empowered throughout their healthcare journey. Michelle is dedicated to driving innovation in healthcare operations and is committed to making quality healthcare more accessible and efficient for all.