The Beat

As healthcare moves beyond hospital walls, reliable connectivity is becoming essential to patient care.

In this episode of The Beat's Interop Now at ViVE series, host Sandy Vance talks with Robin Goldsmith, Practice Leader of Healthcare at Verizon Business, about the networks powering modern healthcare delivery.

They explore remote patient monitoring, rural healthcare access, secure hospital connectivity, and business continuity. Robin also discusses how growing AI workloads are changing infrastructure demands and why health systems must plan for future data needs while balancing cost, security, and operational resilience.

Better connected healthcare starts with the infrastructure that makes it possible.

• Why connectivity is becoming foundational to care delivery inside and outside hospitals
• How private networks and in-building cellular coverage support modern clinical environments
• Why mobile EHR workflows require reliable, secure connectivity
• How wireless backup solutions can help hospitals maintain operations during network disruptions
• How remote patient monitoring can expand access to care at home
• Why rural healthcare requires creative connectivity solutions and partnerships
• How growing AI workloads are increasing demand for network capacity and data transport
• What healthcare CIOs should consider when modernizing legacy infrastructure
• Why long-term network planning must balance performance, resilience, and ROI 

Robin Goldsmith is Practice Leader of Healthcare at Verizon Business, where he helps healthcare, insurance, and life sciences organizations address connectivity challenges and support digital transformation. He works with industry leaders on secure network infrastructure, remote patient monitoring, rural healthcare access, and emerging technologies. Robin also hosts Verizon's Healthcare On Air podcast, featuring conversations about the future of healthcare.

For decades, healthcare phone automation was designed primarily to route calls and contain costs. Today's voice AI is beginning to change all of that.

In this episode of Health's Beat, host Sandy Vance talks with Lisa Gohil, Healthcare General Manager at Vapi, about how conversational voice AI is transforming the healthcare front door and creating opportunities that go far beyond traditional call center automation.

As voice AI evolves, Lisa argues that the opportunity isn't simply to replace calls handled by people. It's to make getting help easier, more proactive, and more personalized for patients.

• How voice AI is moving healthcare beyond the traditional phone tree
• Why voice AI can be a growth driver, not just a cost-cutting tool
• How proactive outreach can improve scheduling and referral conversion
• Why patient satisfaction may challenge assumptions about AI-powered calls
• How voice agents use context and knowledge to personalize conversations
• Why successful AI deployments require workflow redesign, not just automation
• Where human escalation belongs in an AI-powered patient experience
• How voice AI could make healthcare's front door easier to navigate

Lisa Gohil is a healthcare executive leader with 20 years of experience at the intersection of technology and healthcare: evaluating, selling, and buying technology solutions. Lisa specializes in matching problems with the right solutions and designing business models that can support sustainable transformation. Lisa currently leads Healthcare at Vapi, the leading enterprise voice AI technology. 

Prior to joining Vapi, Lisa spent 4 years at Stanford Medicine Health Care, where she led the Digital Health team and determined the enterprise’s 3-5 year digital health strategy and roadmap (for Adult Hospitals and Clinics). 

She also led Stanford’s Emerging Applications Laboratory (SEAL), an innovation team that incubates (designs, prototypes, generates user feedback) tech solutions for clinician pain points and de-risks emerging technology for the enterprise. Before Stanford Healthcare, Lisa led commercial and marketing functions for a clinical research startup and spent nearly a decade at Deloitte Consulting partnering with Fortune 500 healthcare companies on growth strategy. 

What if hospitals could predict bottlenecks before they disrupt patient care?

In this episode of The Beat's AI at HLTH series, host Sandy Vance talks with Bree Bush, General Manager of Command Center and CareIntellect at GE HealthCare, about how AI is helping health systems improve patient flow, capacity, and access to care.

Bree explains how CareIntellect for Operations uses predictive analytics to anticipate resource constraints, support discharge planning, and guide operational decisions. They also discuss measurable results, responsible AI, and the importance of integrating technology into existing hospital workflows.

The takeaway: Better hospital operations start with anticipating problems, not just reacting to them.

• Why rising demand, staffing constraints, and complex care make hospital capacity harder to manage
• How AI can help hospitals move from reactive to predictive operations
• How CareIntellect for Operations forecasts bottlenecks up to 72 hours ahead
• Why imaging, discharge planning and departmental coordination affect patient flow
• How predictive tools can help health systems make better use of existing resources
• What health systems should measure when evaluating operational AI ROI
• Why responsible AI, workflow integration and continuous learning matter
• How change management helps hospitals turn new technology into sustained improvement

Bree Bush is the General Manager for GE HealthCare Command Center software and CareIntellect operations application. Her focus is on helping leading health systems enhance their operations by streamlining patient flow, optimizing capacity, eliminating inefficiencies, and improving access to care. 

Bree was a founding member of the Command Center software team when the solution launched more than a decade ago. It has since been adopted by nearly 500 hospitals and medical facilities globally. Bree is also General Manager for GE HealthCare’s CareIntellect enterprise applications, including a forthcoming hospital operations application. CareIntellect is GE HealthCare’s family of clinical and operational applications, designed to help customers optimize care delivery and quality across health networks and care settings.

Bree has led healthcare organizations through operational transformation initiatives at GE HealthCare for two decades. Whether her efforts were focused on improving the operating room block schedule or reducing length of stay for inpatients, she has implementedsimulation modeling and systems engineering methodology to drive measurable results and create a culture of continuous improvement.

Healthcare AI can deliver answers in seconds, but how can clinicians trust the evidence behind them?

In this episode of The Beat's AI at ViVE series, host Sandy Vance talks with Yvonne Ridge, Head of Product at BMJ Group, and Dr. Kieran Walsh, Clinical Director at BMJ Group, about bringing trustworthy, evidence-based clinical intelligence into AI-powered healthcare.

They explore how BMJ's clinical knowledge graph connects medical evidence to patient care, why more information doesn't always mean better decisions, and how transparent, continually updated recommendations can help address AI's risks. Better healthcare AI starts with reliable evidence, not just more data.

• Why faster AI answers aren't enough without trustworthy clinical evidence
• How BMJ Group is evolving from traditional publishing to digital clinical intelligence
• How knowledge graphs connect clinical guidelines, conditions, tests, and treatments
• Why complex patients need more than rules-based clinical decision support
• How evidence-based recommendations can help address AI hallucinations and explainability
• Why conflicting clinical guidelines require careful interpretation, not just aggregation
• How clinical intelligence can fit into existing healthcare workflows
• Why clinician involvement is essential when designing AI-powered healthcare tools

Yvonne Ridge is Head of Product at BMJ Group, bringing 25 years of experience in healthcare product development. She leads the development of digital health solutions that make trusted clinical evidence more accessible and actionable, helping healthcare organizations integrate reliable medical knowledge into AI-powered tools and clinical workflows.

Dr. Kieran Walsh is Clinical Director at BMJ Group and a geriatrician with a background in medical publishing and education. He oversees the safety and quality of BMJ's digital clinical knowledge resources, helping ensure healthcare professionals have access to accurate, evidence-based guidance that supports better clinical decisions.

Healthcare doesn't necessarily become less human when AI enters the conversation. It can become more human if AI removes the frustrating parts of healthcare that humans aren't particularly good at.

Voice AI is moving beyond demos and novelty applications and into the everyday infrastructure of healthcare. From scheduling and intake to wellness checks, translation, and patient communication, AI-powered voice technology is beginning to change how patients interact with hospitals, clinics, and care networks.

In this episode of The Beat's AI series, Sandy Vance speaks with Isaiah Granet, co-founder and CEO of Bland, about the evolution of voice AI in healthcare and what it takes to make these systems reliable enough for real-world patient interactions. Isaiah explains why BLAND chose to build its own models rather than rely on frontier model providers, how that approach can help address healthcare's data privacy and security concerns, and why highly specialized AI can outperform general-purpose models for specific healthcare tasks.

• How voice AI is moving from novelty to infrastructure across healthcare
• Why BLAND chose to build its own AI models instead of relying on frontier model providers
• How specialized AI can address healthcare's unique privacy, security, and reliability requirements
• Why AI-powered automation could actually make healthcare more human
• How BLAND is scaling voice AI across scheduling, patient engagement, translation, and other healthcare use cases
• Why the quality of the patient interaction has to come first
• How AI could become a more accessible "front door" to healthcare

Isaiah Granet is the CEO and co-founder of Bland, where he’s building production-grade voice AI for real customer conversations. A Y Combinator alum (S23), he has raised $65M to build reliable, enterprise-scale voice systems.

Before founding Bland, Isaiah founded San Diego Chill, a nonprofit providing one-on-one ice hockey mentoring for children with developmental disabilities. For this work, he was named a CNN Heroes Young Wonder.

Healthcare has made enormous strides in using AI to generate better data, predictions and insights. But generating intelligence is only part of the equation. How do healthcare organizations turn that intelligence into meaningful, coordinated action?

In this episode of Health's Beat, host Sandy Vance sits down with Sundar Subramanian, CEO of Zyter, to explore why much of today's healthcare AI transformation may still be functioning as a "Band-Aid" layered over outdated systems and workflows.

Sundar explains why organizations need to move beyond isolated AI pilots and rethink processes from end to end. He introduces the idea of "connected action," where AI agents, people, systems and workflows work together to execute complex healthcare processes safely and consistently. They also talk about the challenges of deploying probabilistic generative AI in high-stakes healthcare environments and the importance of domain-specific AI architecture.

Sandy and Sundar examine what it will take to move healthcare AI from promising experiments to trusted, scalable transformation.

• Why isolated AI use cases can become a "Band-Aid" instead of true healthcare transformation
• The shift from AI-generated intelligence to connected action
• Why healthcare workflows must be redesigned, not simply automated
• How AI could transform complex processes like prior authorization
• Why probabilistic AI creates unique challenges in high-stakes healthcare
• What human-in-the-loop governance should actually look like
• How trusted AI can help clinicians focus their judgment where it matters most
• Why end-to-end AI transformation could improve care while helping bend the cost curve

Sundar Subramanian is Chief Executive Officer of Zyter, where he leads the company’s strategy and growth as it advances AI-powered transformation across healthcare and other complex, regulated industries. Prior to Zyter, Sundar spent more than 16 years at PwC, where he led strategy consulting and advised Fortune 500 companies on growth, AI-enabled transformation, and operating model redesign. He previously held leadership roles at Booz & Company, WellCare Health Plans, and McKinsey & Company. Sundar holds an MS from MIT, an MBA from The Wharton School, and a B.Tech from IIT (BHU) Varanasi. 

Artificial intelligence in healthcare is moving beyond simply summarizing things that have already happened. In behavioral health, AI is beginning to help clinicians make better-informed decisions before care happens; things like bringing clinical protocols, payer requirements, documentation, and a patient's real-time condition together at the point of care.

In this episode, host Sandy Vance talks with Mehmet Kazgan, CEO and Founder of Cliexa, and Susan Jerlow, VP Enterprise Applications at ERC Pathlight, about their collaboration to use AI to reduce friction across behavioral health workflows. They discuss how AI can help clinicians evaluate medical necessity, improve documentation quality, support authorization processes, and make transitions between levels of care smoother for patients and their families.

The conversation also digs into one of the biggest questions facing healthcare organizations today: How do you actually measure the ROI of AI? 

• How AI can bring clinical protocols, payer requirements, and real-time patient information together at the point of care
• Using AI to reduce documentation burden and improve consistency in behavioral health
• How ERC Pathlight uses AI to support admissions and level-of-care decisions
• Why keeping clinicians in the loop is essential for quality, compliance, and trust
• How ERC Pathlight reduced admission declines by 20% through its Enhanced Admission Review process
• Why AI adoption and measurable outcomes are more meaningful than simply promising time savings
• How healthcare organizations can build trust and successfully integrate AI into clinical workflows

Susan Jerlow is a healthcare technology executive and AI strategist leading one of the most advanced real-world AI transformations in behavioral health today. As Vice President of Enterprise Applications, Analytics, and AI at Eating Recovery Center | Pathlight Mood & Anxiety Center, she architects and executes an end-to-end enterprise AI ecosystem across clinical, operational, and analytical domains.

Her work moves beyond pilots and proofs of concept - deploying AI directly into live care environments to reduce clinician burden, improve documentation quality, and enable more consistent, data-driven decisions across the patient journey. Her portfolio includes ambient AI documentation, automated clinical audits, AI-guided assessments, admissions intelligence, and a governed semantic data layer that powers enterprise-wide insights.

She is particularly focused on how AI can separate signal from noise in complex clinical environments - turning fragmented data into clear, actionable insight that improves both patient outcomes and operational performance.

Mehmet Kazgan is the Founder and CEO of cliexa, the Denver-based healthcare AI company he launched in 2016. His path to founding cliexa runs through some of the most influential names in technology and healthcare — Adobe, Google, Microsoft, PayPal, Visa, and Aetna — where he learned to build at consumer scale while mastering the exacting standards of financial services and the realities of how care actually gets delivered.

It was his time in executive leadership at Aetna that proved formative. Working inside one of the nation's largest health insurers, Mehmet saw firsthand where healthcare breaks down: the gap between what clinicians know is right for a patient and what the system will recognize, approve, and pay for. That vantage point — sitting where medicine, coverage, and technology collide — became the founding insight behind cliexa. He built the company to close that gap, giving clinicians the clarity to know what's medically necessary and appropriate at the moment care happens, rather than after the fact. 

Under his leadership, cliexa earned selection into the Mayo Clinic Platform_Accelerate program, forged a co-development partnership with the American College of Cardiology, and delivered its flagship enterprise deployment with ERC Pathlight. A frequent speaker, mentor, and advisor across digital health, Mehmet has built cliexa into a company whose partners include the American College of Cardiology, ERC Pathlight, Columbia University, Astellas, and more.

As healthcare AI evolves from tools that generate recommendations to agents capable of accessing data and taking action across systems, governance has to evolve with it.In this episode of The Beat's AI at ViVE series, host Sandy chats with Corinne Pellows, the Director of product management at Rhapsody about the growing need for real-time AI governance.

They explore why written policies alone aren't enough, how health systems can manage AI agent permissions and data access, and where human oversight belongs in increasingly autonomous workflows. Corinne also discusses how organizations can use Rhapsody® Guardian to build flexible safeguards that evolve alongside AI.     

Remember, responsible AI requires more than setting policies. It requires putting them into action.

●      Why AI agents introduce new governance risks when they move from advice to action

●      How to manage AI agent permissions like employee access privileges

●      Why written AI policies need real-time technical enforcement

●      How Rhapsody Guardian supports AI and API governance

●      Why healthcare organizations need visibility into what data AI agents access

●      When human oversight is essential and when it can create unnecessary friction

●      How risk-based policies can evolve alongside AI technology

●      Why effective AI governance must work with existing healthcare infrastructure

Healthcare and life sciences have a unique challenge when it comes to using AI for marketing, sales, and communications: accuracy isn't a nice-to-have. It's a must-have.

In this episode of The Beat's AI at Health series, host Sandy Vance talks with Divya Srungaram, VP of Healthcare Solutions at WRITER, about how AI agents are helping healthcare organizations accelerate highly regulated workflows without sacrificing compliance, accuracy, or human oversight.

Divya shares why healthcare marketing campaigns can take nine to 12 months to move from brief to launch, and how AI agents can embed legal and compliance requirements directly into the content creation process, reducing the back-and-forth that traditionally slows teams down.

Some of the key takeaways include: organizations shouldn't start by trying to automate every step of an existing process. Instead, they should start with the outcome they need to achieve and then determine how AI can orchestrate the work.

As healthcare organizations move from experimenting with AI to deploying it at scale, Divya sees an inflection point ahead, one where domain expertise combined with AI fluency could become a significant competitive advantage.

• Why healthcare content creation is so slow and how AI agents can change the equation
• Building compliance and legal requirements directly into AI workflows
• Using checker agents and traceability to reduce AI risk
• How AI can accelerate complex Medicaid RFPs
• Why organizations should start with outcomes rather than existing processes
• The importance of data discipline and a clear source of truth
• Preparing employees for roles that will change as AI adoption grows
• Measuring AI ROI through speed, revenue, sales effectiveness, and efficiency
• How AI can make healthcare communications more empathetic and easier to understand
• Why healthcare organizations may be approaching an AI inflection point

Divya Srungaram is Vice President of Healthcare Solutions at WRITER, where she leads the healthcare vertical, helping health plans and providers deploy generative AI to drive measurable impact across commercial and operational workflows.

She is a healthcare AI executive with nearly two decades of experience transforming payer and provider operations through generative AI, machine learning, and advanced analytics. She brings deep expertise across claims, utilization management, care management, and risk adjustment, and has served as a trusted advisor to multi-billion-dollar health plans on enterprise AI strategy, responsible AI governance, and large-scale implementation. Her work focuses on translating data and AI into actionable insights and solutions that help health plans better understand employer populations, manage cost trends, and drive improved engagement and outcomes across Commercial and Medicare lines of business.

Divya was a leader in the Healthcare Strategy & Analytics practice at Deloitte, where she advised large healthcare organizations on transformation and led the development of AI-driven products and data platforms. She later served as VP of Product at Blue Health Intelligence, where she led the Employer Analytics platform supporting multiple Blue Cross Blue Shield plans and millions of members. Most recently, as SVP of Provider Growth and Product at Allymar Health, she led product strategy and growth for Medicare solutions, developing AI-enabled capabilities to improve documentation quality, risk adjustment accuracy, and clinical workflows.

She holds a Bachelor’s degree in Computer Systems Engineering from Massey University (New Zealand) and an MBA from Harvard Business School.

Millions of people struggle with behavioral health conditions that remain undiagnosed or undertreated. AI could help find those patients sooner and connect them to more effective care.

In this episode of the AI at ViVE series on The Beat, host Sandy Vance talks with Jeremy Kreyling, the SVP of Healthcare Informatics at NeuroFlow, about where artificial intelligence genuinely belongs in behavioral health and where clinical judgment and human connection remain irreplaceable.

Jeremy explains how NeuroFlow uses machine learning across claims, EHR, assessment, and engagement data to identify hidden behavioral health risk, and why models built around an organization's own population can provide greater confidence than a one-size-fits-all approach. They also discuss how AI can help reduce the number of patients lost between identification, referral, and effective treatment.

• How AI can identify behavioral health needs that haven't yet been diagnosed
• Why healthcare AI models should reflect the populations they're designed to serve
• How machine learning can make behavioral health outreach more targeted
• Why finding a provider isn't enough if the patient doesn't stay in care
• How AI agents can take administrative work off highly trained care managers
• Why behavioral health still lags physical health in analytics and integration
• How measurement-based care can identify when treatment isn't working
• Why AI should create more meaningful patient care, not simply more patient volume

Jeremy Kreyling is the SVP of Healthcare Informatics at NeuroFlow, the market leader in behavioral healthcare technology infrastructure, where he leads analytics strategy to integrate behavioral health into value-based care models. He brings more than 20 years of leadership in healthcare data and analytics, with prior roles at NOCD, ProgenyHealth, and Change Healthcare. Jeremy holds an MBA from the University of Arizona and a B.S. in Information Systems from Arizona State University.