How Optura Is Helping Healthcare Organizations Actually Transform

How CGI Is Helping Federal Health Agencies Get AI-Ready

In this episode, host Sandy Vance chats with Brad Schoffstall [https://www.linkedin.com/in/brad-schoffstall-28b9b547], Vice President of Health and Compliance Programs at CGI [https://www.cgi.com/us/en-us/federal], and Dr. James Peake [https://www.linkedin.com/in/james-b-peake-md-ltg-ret-8a2a6313/], Senior Vice President and former Secretary of Veterans Affairs and Army Surgeon General. They have a wide-ranging and practical conversation about what it actually takes to modernize data infrastructure at federal health agencies. With Brad's 35 years at CGI and Dr. Peake's 16 years, this is a conversation grounded in hard-won experience rather than theory. Today’s conversation is a refreshingly honest and deeply practical perspective for anyone working at the intersection of government, healthcare, and AI.  In this episode, they talk about: * Federal health agencies are running some of the largest healthcare operations in the world, with the VA equivalent in size to a Fortune 5 company * Data silos created by contract-by-contract procurement are the primary barrier to AI-ready infrastructure at federal agencies * Federated data platforms allow data to stay in its own repositories while being discoverable, mappable, and usable across the organization * Policy is often the biggest obstacle to data sharing, and changing it requires executive-level support and shared governance * Technology is the third most important factor in transformation; policy and business understanding come first and second * CGI improved NHS Spine performance tenfold while reducing infrastructure to a tenth of its original size, saving a million euros in annual expenses * Improper payments across federal health programs run into billions of dollars annually and represent one of the highest-impact areas for AI-driven improvement * AI for AI's sake is not the answer; start with the business problem and work backward to the data strategy * Start small with two or three systems, demonstrate value, and build from there rather than attempting a massive all-at-once implementation A Little About Brad and James: Brad Schoffstall has wide-ranging experience, deep knowledge, and skills in information technology. He has led multiple digital transformation efforts. He has 37 years of experience with a diverse set of architectures, operating systems, languages, and technologies. His experience includes enterprise architecture, cloud migration, and hands-on development. He also has significant experience in business development and project management. He has implemented large, complex systems on platforms ranging from mainframes to Microservices. He has successfully performed many solution architecture and SDLC engagements that include characteristics like high-volume processing, DevOps, and automation. He demonstrates expertise in multiple service-based secure architectures utilizing multiple application and enterprise solution sets, e.g., Data Driven, Microservices, Cloud, etc.  Dr. James Peake is an American politician and former lieutenant general who served as the sixth Secretary of Veterans Affairs from 2007 to 2009. In 2004, he retired from a 38-year United States Army career, having served as the 40th Surgeon General of the United States Army. After retiring from the Army, Peake served as Executive Vice President and Chief Operating Officer of Project Hope,[4][5] a non-profit international health foundation operating in more than 30 countries. While at Project HOPE, he helped to orchestrate the use of civilian volunteers aboard the Navy Hospital Ship Mercy as it responded to the tsunami disaster in Indonesia and also as part of the Hurricane Katrina response aboard the Hospital Ship Comfort. Just before he was nominated Secretary of Veterans Affairs, Peake served as Chief Medical Officer and Chief Executive Officer for QTC, one of the largest private providers of government-outsourced occupational health and disability examination services in the nation.

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.