Boombostic Health

Welcome to Boombostic Health, where we challenge the business of healthcare and explore bold ideas that drive meaningful change. Each week we bring you candid conversations with top experts, innovators and leaders exploring the latest trends and technologies shaping the future of healthcare.

When Hospital Alarms Become Dangerous Noise 07/21/2026

When Hospital Alarms Become Dangerous Noise Too Many Alarms, Not Enough Signal: How AI Can Make Hospitals Safer | Dr. Darren Klugman Show Notes Hospital alarms are supposed to protect patients. But when nearly every signal becomes background noise, the warning that actually matters may be the one no one hears. Live from ViVE, Marcus Gordon sits down with Dr. Darren Klugman, Chief Clinical Officer at CalmWave, to examine one of healthcare’s most overlooked risks: the growing gap between the volume of hospital data and the human capacity to interpret it. Dr. Klugman explains why alarm fatigue is more than an operational nuisance—it is a patient safety problem. Clinicians are being asked to manage increasingly complex patients, devices, scores, and alerts while still delivering the human care that technology cannot replace. The answer is not another dashboard or another point solution. It is a smarter operational foundation that unifies electronic health record and bedside device data, separates meaningful signals from noise, and turns information into recommendations clinicians can act on. The conversation explores how mathematical modeling and data science can improve patient monitoring, give clinical engineering real-time visibility into device performance, inform nursing resources, forecast patient recovery, and help hospitals move patients through the ICU more safely and efficiently. For health system executives, the business case is equally clear: reducing preventable harm, shortening length of stay, improving bed utilization, increasing patient throughput, and allowing clinicians to practice at the top of their expertise. Healthcare does not need to give clinicians more data to interpret. It needs to make the data they already have actionable. In this episode: Why excessive non-actionable alarms can cause clinicians to miss the signals that matter How unified hospital data can improve patient safety, staffing, device management, and patient flow Why health systems must move beyond disconnected point solutions and demand measurable operational value How AI can reduce cognitive burden without replacing clinical judgment Why today’s workforce and capacity crisis makes smarter hospital operations essential Timestamps 00:00 — Live from ViVE with Dr. Darren Klugman 00:27 — Unifying EHR and bedside device data 01:38 — When hospital alarms become dangerous background noise 04:20 — Reducing cognitive burden inside the clinical workflow 06:35 — Building one data foundation for hospital operations 08:05 — Patient safety, ICU throughput, and measurable ROI 09:58 — What health systems should demand from technology vendors 12:39 — Why healthcare’s workforce and capacity crisis demands action Subscribe to Boombostic Health for candid conversations with the leaders transforming healthcare through better data, smarter technology, and more accountable innovation. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/42173260

Healthcare AI Has to Prove Itself Now 07/07/2026

Healthcare AI Has to Prove Itself Now Healthcare is past the point of being impressed by AI demos. The next phase is harder: proving value. In this episode of Boombostic Health, Bradley Bostic talks with Mike Hollis, co-founder of Optura AI, about what healthcare leaders need to do now: move beyond pilots, cut through AI noise, and focus on the use cases that can actually deliver measurable outcomes. Mike shares why so many organizations are stuck between excitement and execution, how leaders can evaluate AI maturity, and why the future of healthcare AI may be defined less by token usage — and more by trust, transparency, and accountability. This conversation gets into the real work behind AI adoption: aligning teams, measuring ROI, building confidence, and choosing where AI can create both business value and societal impact. Especially in areas like rare disease and underserved conditions, Mike makes the case that AI’s biggest opportunity may not be where the hype is loudest. Watch this episode if you’re asking: How do we know which AI initiatives are actually worth pursuing? Why are so many healthcare organizations stuck in pilot mode? What does ROI really look like in healthcare AI? How do trust, transparency, and behavior change affect adoption? Where can AI create meaningful impact beyond operational efficiency? Featured moments: 00:00 — Why Optura AI was built 02:43 — AI’s economic and societal opportunity in healthcare 03:13 — Why organizations get stuck in AI decision paralysis 05:47 — The metrics that help prove value 06:56 — From token economics to trust economics 10:18 — Why transparency and behavioral science matter 12:23 — The lesson healthcare leaders cannot ignore: ROI matters Guest: Mike Hollis, Co-Founder, Optura AI Host: Bradley Bostic Podcast: Boombostic Health Subscribe to Boombostic Health for conversations with the leaders building the next era of healthcare. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41993485

The $19,000 Bill That Exposed Healthcare's Biggest Problem 06/30/2026

The $19,000 Bill That Exposed Healthcare's Biggest Problem Healthcare does not just have a care delivery problem. It has a payment problem. In this episode of Boombostic Health, Bradley Bostic sits down with Nitesh Shroff, CEO and co-founder of Arintra, live from ViVE, to discuss how AI is being used to tackle one of healthcare’s most painful and overlooked challenges: revenue cycle management. Arintra’s origin story started with a shocking $19,000 hospital bill caused by a coding error. That experience exposed how fragile, confusing, and expensive healthcare billing can be for patients and providers — and led Nitesh and his co-founder to build an AI-powered approach designed to make healthcare payments more accurate, transparent, and efficient. Nitesh explains how Arintra uses explainable AI, clinical and financial agents, and human-in-the-loop learning to automate medical coding, prevent denials, support prior authorization, and help health systems get paid accurately and on time. The company’s technology works directly inside EHR workflows, including Epic and athenahealth, helping reduce friction for providers while improving trust and adoption. This conversation goes beyond automation hype. It explores why revenue cycle has become mission-critical for health systems, why denials keep increasing, why the supply of skilled coders cannot keep pace, and why explainability may be the key to making AI work safely in healthcare. In this episode: 00:00 — Live from ViVE with Nitesh Shroff of Arintra 01:36 — The $19,000 hospital bill that sparked Arintra’s mission 04:22 — How explainable AI agents understand clinical and financial context 06:58 — Applying safety-first AI lessons from self-driving cars to healthcare 07:57 — Why documentation, coding, and payment must all align 09:04 — How customer pain points guide Arintra’s roadmap 10:07 — The ROI opportunity for health systems 11:23 — Why revenue cycle complexity and denials are accelerating 12:38 — What better billing accuracy means for patients 14:58 — The future of prior authorization, compliance, and payment transparency Healthcare revenue cycle is often treated as a back-office function. But as Nitesh and Bradley discuss, it is the financial lifeblood of healthcare — and one of the places where AI may create immediate, measurable impact. Watch the full conversation to hear how Arintra is helping health systems reduce complexity, improve accuracy, and bring more trust into one of healthcare’s most broken systems. Subscribe to Boombostic Health for more conversations with the builders, operators, and leaders transforming the future of healthcare. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41910225

AI Won’t Save Healthcare If the Data Layer Is Broken 06/24/2026

AI Won’t Save Healthcare If the Data Layer Is Broken AI is everywhere in healthcare right now. But Nancy Wright of GE HealthCare makes a sharper point: AI will only be as useful as the infrastructure underneath it. In this episode of Boombostic Health, recorded live at ViVE 2026 in Los Angeles, Bradley Bostic sits down with Nancy Wright, VP of Digital Platforms at GE HealthCare, for a practical conversation about interoperability, cybersecurity, connected devices, workforce shortages, and the operational future of healthcare. Nancy explains why interoperability is no longer just about exchanging clinical data. Health systems now need a more connected view across operations, finance, clinical workflows, biomedical engineering, supply chain, and cybersecurity. The challenge is not replacing every system. It is creating a smarter data layer that allows existing platforms to keep working while giving leaders better visibility, stronger security, and more actionable intelligence. The conversation also explores why healthcare cybersecurity must become proactive, why connected devices are expanding the risk surface, and how agentic AI could help reduce the burden on clinical and technical teams already stretched thin. This is a conversation about what healthcare needs before AI can truly scale: connected infrastructure, secure data, and operational intelligence. In This Episode Bradley and Nancy discuss: Why healthcare’s AI future depends on the data layer beneath it What interoperability really means inside modern health systems Why disconnected operational, clinical, and cybersecurity data creates risk How connected devices and IoT endpoints are changing healthcare cybersecurity Why health systems need proactive security partners, not reactive fixes How agentic AI could support biomedical, clinical, and operational teams Why partnership will matter as healthcare innovation accelerates Key Moments 00:00 — Welcome from ViVE 2026 with Nancy Wright of GE HealthCare 01:08 — How AI is changing operations, labor, and interoperability 03:20 — Why interoperability needs a clearer definition 05:28 — Building a smarter layer across existing health system platforms 06:31 — Cybersecurity, bad actors, and healthcare’s growing risk surface 08:48 — Connected devices, IoT endpoints, and proactive risk planning 12:09 — Why ViVE creates momentum for healthcare partnerships 14:15 — Agentic AI, workforce shortages, and the future of healthcare operations Why It Matters Healthcare does not need more disconnected technology. It needs infrastructure that helps leaders see across the enterprise, secure connected assets, support overloaded teams, and turn fragmented data into action. That is the foundation required for AI to become more than hype. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41794140

The $15 Billion Problem Hiding Inside Hospital Workflows 06/18/2026

The $15 Billion Problem Hiding Inside Hospital Workflows The $15 Billion Problem Hiding Inside Hospital Workflows Everyone wants to talk about AI in healthcare. Greg Miller wants to talk about the work no one sees. In this live conversation from ViVE, Greg Miller, VP at Carta Healthcare, joins the Boombostic Health Podcast to expose one of healthcare’s most expensive hidden problems: the billions spent manually abstracting clinical data for registries, quality reporting, accreditation, CMS measures, and benchmarking. This is not basic data entry. It is highly skilled clinical work. Nurses and clinical experts are digging through EHRs, interpreting complex patient records, and making judgment calls that directly impact how hospitals measure quality and performance. Greg calls it “swivel chair interoperability,” and it is costing U.S. healthcare an estimated $10–$15 billion every year. But the answer is not just “throw AI at it.” Greg makes the case for hybrid intelligence: AI powerful enough to accelerate the work, with clinician oversight strong enough to earn trust. Because in healthcare, accuracy is not optional, workflow matters, and the market is moving past AI hype toward solutions that prove ROI fast. The real question is no longer whether healthcare will use AI. It is whether AI can actually solve the messy, expensive, high-stakes problems buried inside the system. Timestamps 00:00 — Why clinical data abstraction is healthcare’s hidden cost center 02:16 — Why registry work still requires clinical judgment 04:37 — The trust gap: why AI needs clinician oversight 05:38 — How Carta Healthcare repositioned around “hybrid intelligence” 10:01 — Why the AI hype cycle is giving way to ROI 11:54 — Why healthcare technology fails when it sits outside the workflow Best Moments Greg breaks down why some registry questions cannot be answered by simply searching the EHR. They require clinical inference, context, and expertise. He also explains why healthcare buyers are getting sharper. A year ago, AI was the shiny object. Now, health systems want practical implementation, workflow integration, and measurable financial impact. Key Takeaway AI will not win in healthcare because it sounds impressive. It will win when it removes burden, protects accuracy, fits the workflow, and earns clinician trust. That is the promise of hybrid intelligence. Featured Guest Greg Miller VP, Carta Healthcare Follow Boombostic Health for more conversations with the leaders building the future of healthcare. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41694355

From Chart Review to Clinical Capacity Duke’s AI Strategy 06/16/2026

From Chart Review to Clinical Capacity Duke’s AI Strategy How Duke Is Building AI That Actually Works in Healthcare | Matt Cox, Duke Health Healthcare does not need more AI hype. It needs AI that can survive clinical reality: compliance, governance, patient safety, workflow, physician adoption, and the brutal operational pressure every health system is facing. In this episode of Boombostic Health, Bradley Bostic sits down live at ViVE 2026 with Matt Cox, Executive Director for Digital Value Creation at Duke Health, to unpack how Duke is moving from AI experimentation to real-world clinical impact. Matt shares how Duke is building its own AI capabilities, including the Scout LLM platform, to safely support use cases across the health system — from clinical research and chart review to virtual nursing, ambient documentation, operational efficiency, and clinician burnout. The standout example: Duke used Scout to review 200 pancreatic cancer patient charts in less than two hours — work that would typically take a PA or nurse practitioner one to two weeks. That is not theoretical AI. That is capacity creation. That is clinicians working at the top of their license. That is the future healthcare actually needs. In this episode Bradley and Matt discuss: Why Duke chose to build internal AI infrastructure instead of relying only on outside tools How Duke evaluates AI through governance, compliance, safety, bias, and clinical decision support The role of Duke Institute for Health Innovation and EHRX in exposing health data safely How Scout is helping accelerate chart review, clinical research, and protocol compliance Why AI’s biggest opportunity may be giving time back to clinicians Duke’s approach to investing in startups that solve real internal health system problems The growing importance of virtual nursing, ambient AI, and operating-room intelligence Why human factors may determine whether healthcare AI succeeds or fails What Matt is watching across the healthcare innovation landscape after ViVE Key Takeaways 1. The winning health systems will not just buy AI. They will govern it. Duke is not treating AI as a shiny object. It is building processes to test whether tools are safe, compliant, clinically appropriate, and operationally useful before scaling them. 2. AI only matters if it removes real friction. The Scout example shows the real promise: not replacing clinicians, but removing time-consuming administrative and review work so highly trained people can focus on patients, research, and care delivery. 3. Innovation starts with the problem, not the pitch deck. Duke’s venture approach begins with internal pain points — nurse burnout, clinician burnout, access, capacity, and workflow — then looks for companies that can help solve them. Chapters 00:00 — Live from ViVE 2026 with Matt Cox of Duke Health 01:22 — Matt’s role leading digital value creation at Duke 04:05 — How Duke built the foundation for healthcare AI through EHRX 05:04 — Why Duke created its own LLM capability 05:52 — Governing AI through safety, compliance, and clinical decision support 07:21 — Inside Scout, Duke’s AI platform 08:18 — Reviewing 200 pancreatic cancer charts in under two hours 10:11 — Using AI to free clinicians and expand capacity 11:52 — Duke’s shift from reactive innovation to targeted venture investing 12:44 — Why nurse burnout and virtual nursing are top priorities 14:07 — Ambient AI and the fastest adoption Matt has seen in healthcare 15:44 — How Duke prioritizes investment and implementation opportunities 17:42 — What Matt is learning at ViVE: human factors, new roles, and the future of work Featured Guest Matt Cox Executive Director, Digital Value Creation Duke Health Mentioned in this episode Duke Health Duke Institute for Health Innovation EHRX Scout LLM Platform Ambient AI Virtual Nursing Algorithm-Based Clinical Decision Support ViVE 2026 About Boombostic Health Boombostic Health puts a spotlight on the people, technologies, and ideas moving healthcare forward. Hosted by Bradley Bostic, each conversation explores the practical innovations reshaping care delivery, diagnostics, data, AI, and the future of healthcare. Subscribe for more conversations with the leaders building what comes next in healthcare. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41667015

Why Healthcare AI Needs Better Data Before Bigger Promises 06/12/2026

Why Healthcare AI Needs Better Data Before Bigger Promises Why Healthcare AI Needs Better Data Before Bigger Promises | Michael Meucci, CEO of Arcadia Episode Description: AI is moving fast in healthcare, but the real question is not who has the newest tool. It is whether the data behind it can be trusted. In this episode of Boombostic Health, Marcus Gordon sits down with Michael Meucci, CEO of Arcadia, to discuss what it will actually take for AI to improve care delivery, reduce friction, and create measurable impact across the healthcare system. Michael shares why healthcare organizations need complete, timely, clinically relevant data to make AI useful and safe. He explains how fragmented information can create risk instead of intelligence, why rural healthcare may become one of the most important innovation opportunities in the country, and how leaders need to rethink workflows instead of simply layering AI on top of broken processes. The conversation also explores the growing role of the healthcare consumer, the pressure facing hospitals and health plans, and why the next 24 months may reshape how care is delivered, measured, and experienced. Key Takeaways: AI in healthcare is only as strong as the data behind it. Michael explains why trusted, complete, timely, and relevant data is essential for AI to support better decisions and avoid creating more noise. Rural healthcare may become a major innovation frontier. With new national attention and investment, rural hospitals and critical access facilities have an opportunity to adopt modern care models, virtual-first approaches, and advanced technology in ways that could reshape access. Leaders need to redesign workflows, not just adopt tools. Michael challenges healthcare leaders to rethink long-standing assumptions around EHRs, operating models, automation, and how teams use technology to manage patients, panels, and performance. Topics Covered: Healthcare AI beyond the hype Why trusted data matters in clinical decision-making The risk of incomplete or outdated data How AI can support providers, patients, health plans, and health systems The role of longitudinal patient data Rural healthcare transformation Health equity and access to care Leadership in an AI-driven operating environment Why workflow redesign matters The future role of the healthcare consumer Timestamps: 00:00 Introduction: Michael Meucci, CEO of Arcadia 00:16 What it means to lead a healthcare data and AI company today 01:18 Why healthcare needs AI to work amid cyber threats and margin pressure 02:48 Trust, efficacy, and data integrity in healthcare AI 03:28 Why AI models need timely, complete, and transparent data 05:00 The opportunity to expand access in rural communities 05:35 Rural health transformation and the future of critical access hospitals 08:05 Leadership, workflow redesign, and changing how teams think about AI 10:27 Rethinking tools like Salesforce, EHRs, and workflow systems 12:56 What is most exciting about the next 24 months in healthcare 13:29 Rural care, data liberation, and the rise of the healthcare consumer 14:57 Closing thoughts Guest: Michael Meucci, CEO of Arcadia About Boombostic Health: Boombostic Health features conversations with the leaders, innovators, and builders shaping the future of healthcare. Hosted by Bradley Bostic, the podcast explores the ideas, technologies, and operating models transforming care delivery, diagnostics, data, AI, and patient outcomes. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41626290

Can Diagnostics Solve the Healthcare Cost Crisis? 06/09/2026

Can Diagnostics Solve the Healthcare Cost Crisis? Unlocking the Future of Healthcare: Diagnostics, Data, and Value-Based Innovation Healthcare transformation will not happen through technology alone. It will happen when diagnostics, data, clinical workflows, and incentives finally work together. In this episode of Boombostic Health, Bradley Bostic sits down with Gary Albers and Steve Serota for a practical conversation on how diagnostics can move healthcare from reactive treatment to proactive, value-based care. The discussion explores why laboratory medicine is often one of the most underutilized levers in healthcare, despite its ability to influence earlier intervention, better medication decisions, lower costs, and more personalized care. Gary and Steve share how health systems, payers, providers, and innovators can use diagnostic intelligence to close gaps in care, improve trust, and create measurable outcomes. From pharmacogenomics and primary care workflow redesign to AI, biometric monitoring, and payer partnerships, this episode goes beyond theory and looks at what it actually takes to make value-based care work in the real world. In this episode: How diagnostics can drive earlier, smarter, and more cost-effective care Why laboratory medicine needs a larger role in value-based healthcare strategy Gary Albers on building high-value outcomes through better diagnostic collaboration Steve Serota on turning lab data into actionable clinical intelligence Why fee-for-service adoption is slow and what is accelerating the move toward value-based models How pharmacogenomics and medication optimization can reduce avoidable costs The importance of primary care workflows in making diagnostics usable at scale How AI and continuous measurement can support more personalized interventions Why trust, privacy, and patient engagement matter in a more connected healthcare ecosystem The future of healthcare through biometrics, personalized medicine, and integrated care models Key Takeaways: Diagnostics are not just tests. They are decision-making tools that can help identify risk earlier, guide treatment, and reduce waste across the healthcare system. Value-based care requires more than new payment models. It depends on better data, stronger workflows, aligned incentives, and measurable clinical impact. The future of healthcare will be more proactive, personalized, and data-driven, but adoption will depend on trust, usability, and proving value in real-world care settings. Timestamps: 00:00 Introduction: Why diagnostics matter in healthcare transformation 01:01 Collaboration as a driver of value-based care 01:34 Gary Albers on high-value diagnostics and laboratory medicine 04:02 Steve Serota on lab data, patient outcomes, and clinical intelligence 07:19 Why value-based care adoption has been slow 08:36 Policy, incentives, and the strategic role of clinical data 10:52 Precision medicine, medication optimization, and cost savings 12:11 Measuring the impact of interventions in real time 14:05 Reimbursement models and the economics of diagnostics 15:01 Funding innovation and upfront investment in value-based care 16:12 Why primary care workflow is critical to diagnostic adoption 19:10 AI, data, and proactive healthcare decisions 22:38 Building trust with more complete patient data 27:43 Biometric monitoring, patient responsibility, and privacy 38:11 Tech giants, health plans, and the future of cost control 44:25 How diagnostics can deliver actionable, affordable outcomes 46:24 Final thoughts: Building the future through collaboration About Boombostic Health: Boombostic Health explores the people, ideas, and innovations reshaping healthcare. Hosted by Bradley Bostic, the show brings together leaders across diagnostics, data, AI, value-based care, and healthcare transformation to discuss what is working, what needs to change, and where the industry is headed next. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41586995

Privacy vs. Progress: Can We Keep Patient Data Safe? 06/02/2026

Privacy vs. Progress: Can We Keep Patient Data Safe? Unlocking the Value of Real-World Data in Healthcare This episode dives into the critical role of real-world evidence and data in transforming healthcare, emphasizing how data privacy, de-identification, and innovative tokenization unlock large-scale insights with minimal risk. Presented by industry veterans, it explores methods to responsibly utilize data for research, clinical trials, and patient care improvements, while addressing common misconceptions and trust issues. In this episode: The importance of real-world data and evidence for healthcare advancement How de-identification and tokenization protect patient privacy while enabling large-scale analysis The benefits of open source tokenization models versus proprietary solutions Practical steps to start using de-identified data for research and clinical decision-making The emerging role of AI, wearables, and consumer data in personalized healthcare The evolving landscape of data monetization, partnerships, and purpose-driven analytics Future of comprehensive data access, trust-building, and patient ownership considerations How AI accelerates insights while ensuring data quality and security Timestamps: 00:00 - Introduction: Healthcare innovation in Indianapolis & the focus on real-world evidence 00:34 - Why healthcare data privacy regulations were designed for protection, not suppression 01:03 - Industry veterans John and Julie on safe data usage and innovation 01:56 - The 18-year journey into real-world data and evidence with HC1 02:38 - How de-identification preserves privacy, scales data, and enables AI-driven insights 03:21 - The role of data in addressing diagnostic gaps and patient journeys 03:53 - The necessity of large-scale, unbiased data for research and healthcare delivery 04:50 - Explaining tokenization simply and why it matters 05:06 - The challenge of integrating data from multiple sources without bias 06:17 - How consumer wearables add depth to patient understanding 07:10 - Therapy development, clinical trials, and the power of de-identified data 07:42 - The significance of bias reduction in healthcare data analytics 08:36 - Path to monetization: Purpose-driven data use versus the race to the bottom 09:00 - The importance of aligning with organizations sharing your mission 09:48 - Clinical trials and real-world evidence improving enrollment and outcomes 10:57 - Strategies for building trust and ensuring patient security in data sharing 11:25 - Practical steps for initiating de-identification & tokenization 12:17 - Privacy-preserving record linkage & open source tokenization solutions 13:20 - The significance of rigorous de-identification processes and certification 14:13 - How tokenization connects disparate datasets without compromising identity 15:11 - Open source solutions versus commercial fee-based tokenization providers 16:45 - The importance of responsible data sharing and avoiding exploitative marketplaces 17:41 - Enhancing clinical trials with real-world evidence and reducing risks 20:13 - The impact of regulatory changes and partnerships in trials 21:06 - Enabling precision medicine through aggregated, de-identified data 22:22 - The role of CROs and third-party organizations in trial success 23:20 - Using advanced AI for device tracking, supply chain, and supply chain data 24:18 - Challenges and opportunities with physician notes and unstructured data 25:41 - The ongoing need for AI refinement and risk management in de-identification 27:02 - Addressing the potential consequences of data breaches and errors 28:41 - The technical feasibility and limitations of perfect de-identification 29:46 - Handling physician notes, abbreviations, and unstructured data responsibly 31:07 - The future of diagnostics, genomics, and embedded AI in healthcare standardization 32:07 - How tokenized, integrated data empowers providers and payers 33:13 - The importance of clean, trusted data for AI accuracy 34:24 - Personalized, real-time insights improving patient care and provider decision-making 36:47 - The untapped potential of lab and rare disease data for proactive care 38:49 - The challenge of small data scale in specialty labs and opportunities for collaboration 40:37 - Using de-identified lab data to predict disease progression and improve outcomes 43:13 - Integrating consumer wearable and biometric data into healthcare insights 44:14 - The power of personal health data for early detection and prevention 45:24 - Expanding access to EHR data and overcoming legislative barriers 47:11 - Building a culture of data ownership and creating trust with patients 48:32 - The potential influence of patient incentives, transparency, and societal changes 50:09 - Closing thoughts: Trust, purpose, and technology shaping the future of healthcare data /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41511150

Cancer Doesn’t Stop at 5 PM: Rebuilding Oncology Around the Patient 05/26/2026

Cancer Doesn’t Stop at 5 PM: Rebuilding Oncology Around the Patient Cancer care has made extraordinary clinical progress, but too many patients still fall through the cracks once they leave the clinic. In this episode of Boombostic Health, Bradley Bostic sits down with Dr. Justin Bekelman, oncologist, co-founder, and CEO of Daymark Health, to discuss how value-based oncology can create a better care model for patients, providers, and health plans. After more than two decades at Penn Medicine, Dr. Bekelman left to build Daymark Health, a company that supports patients receiving active cancer treatment through in-home and virtual care. Daymark partners with health plans and works alongside each patient’s oncology team to address clinical, behavioral, and social needs when and where they arise. The conversation explores why fee-for-service often fails to support the full cancer journey, why oncology is especially suited for value-based care, and why better care requires more than coordination. It requires the ability to act. As Dr. Bekelman explains, “Cancer doesn’t stop at five o’clock.” Timestamps Welcome and personal connection to cancer prevention Dr. Bekelman’s background and why patients still fall through the cracks What value-based care means in oncology Why supportive cancer care is under-reimbursed in fee-for-service How Daymark Health partners with health plans Supporting patients at home, virtually, and at no additional cost Episodic capitation, shared savings, and oncology economics Why cancer care is well suited for value-based models Daymark as the “connective tissue” around the oncologist Why coordination alone is not enough Daymark’s work with Blue Cross Blue Shield of Rhode Island Steven’s story and why cancer does not stop at 5 PM Patient experience, home visits, and measurable results Why this model could become the standard for cancer care In this episode: Why cancer patients need support beyond the clinic How value-based care is being applied to oncology Why Daymark works through health plan partnerships The difference between care coordination and clinical action How in-home care can help prevent avoidable complications Why behavioral health and social support matter in cancer treatment How better patient support can reduce total cost of care Why oncology may be one of the next major frontiers for value-based care /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41428680

Diagnostics at the Center: Turning Real-World Data Into Better Care 05/20/2026

Diagnostics at the Center: Turning Real-World Data Into Better Care Diagnostics are no longer just about confirming what is wrong. They are becoming one of the most powerful tools for predicting what comes next. In this episode of Boombostic Health, Bradley Bostic leads a timely conversation with healthcare and diagnostics leaders on how real-world patient data, genomics, AI, and embedded research models are changing the way healthcare systems identify risk, close care gaps, and deliver more personalized care. The discussion moves beyond the promise of innovation and into the practical realities of adoption. How do we turn routine care into continuous learning? How do we prove the value of advanced diagnostics to payers? How do we expand access without creating new forms of bias? And how do we help patients and providers trust the data, the science, and the recommendations that follow? From home-based testing and consumer-driven care to reimbursement, incidental findings, data diversity, and health economics, this episode explores what it will take to move diagnostics from the edge of healthcare innovation into the center of everyday clinical decision-making. What You’ll Learn How diagnostics are shifting from episodic testing to continuous healthcare intelligence Why real-world data is essential to predicting outcomes and improving care pathways How genomics and AI can support more personalized, proactive care What it takes to build the business case for diagnostic innovation Why reimbursement models must evolve to keep pace with scientific progress How embedded research can make routine care more evidence-driven Why patient trust, education, and transparency are critical to adoption How data diversity can help reduce bias and improve care for underserved populations Why This Conversation Matters Healthcare does not have a data shortage. It has an actionability problem. The future of diagnostics will depend on the ability to connect data to decisions, research to routine care, and innovation to measurable impact. This conversation makes the case for diagnostics as a strategic foundation for better care, smarter economics, and more equitable outcomes. Key Moments 00:00 — Why diagnostics are becoming central to healthcare innovation 02:38 — Embedding research into routine care 04:17 — Using data to predict health outcomes 06:10 — Making the case for payer coverage and cost savings 09:58 — Bringing diagnostic models into clinical workflows 11:14 — The rise of home-based and consumer-driven testing 14:23 — Managing incidental findings responsibly 17:34 — Connecting diagnostics to health economics 24:07 — Addressing disparities, access, and data bias 27:33 — Moving from research to routine clinical care 32:39 — Empowering patients through health technology Featured Topics Real-world evidence Personalized medicine Genomics and AI Diagnostic innovation At-home testing Reimbursement and payer coverage Health economics Data diversity and bias Patient engagement Clinical workflow integration Resources Closing Thought The next era of healthcare will not be defined by more testing alone. It will be defined by whether diagnostics can help turn real-world data into earlier action, better decisions, and measurable improvements in care. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41365510

The Hospital Room That Watches Over Patients (Without Replacing Nurses) 05/12/2026

AI Is Rewriting Diagnostics - Here's What's Coming Next 05/05/2026

AI Is Rewriting Diagnostics - Here's What's Coming Next Transforming Diagnostics: Unlocking Value in the Future of Healthcare In this episode of Boombostic Health, Bradley Bostic sits down with Robert Michel, founder of Executive War College and editor-in-chief of The Dark Report, for a wide-ranging conversation on the past, present, and future of laboratory diagnostics. From the origin story behind Executive War College to the rise of genomics, AI, remote monitoring, and personalized medicine, Robert shares why diagnostics are far more than a line item in healthcare spending. They are one of the most powerful levers for improving outcomes, reducing cost, and helping health systems act earlier. The conversation explores how lab data can move from being underused information to a strategic asset that supports better decisions across maternal health, chronic disease, medication optimization, aging in place, and preventive care. In this episode Bradley and Robert discuss: Why the name Executive War College reflects the strategic decisions lab leaders face How genomics has evolved from early PCR testing to affordable whole-genome sequencing Why diagnostics are central to early detection, patient monitoring, and better outcomes How proactive lab-driven interventions can reduce avoidable healthcare costs Why lab services are often viewed as a cost center despite their impact on total medical spend How labs can become strategic partners by turning data into actionable insight The role AI may play in faster, more precise diagnostic decision-making How wearables, remote monitoring, robotics, and personalized health data could reshape care Why nutrition, microbiome, lifestyle, and prevention are becoming harder to separate from healthcare What longevity research and Blue Zones can teach us about healthspan Why early adopters and innovation communities matter in advancing healthcare transformation Key takeaways Diagnostics are no longer just about test results. They are becoming a strategic intelligence layer for healthcare. Lab data has the potential to help health systems identify risk earlier, intervene sooner, and reduce avoidable cost. The future of healthcare will be shaped by the convergence of diagnostics, AI, remote monitoring, personalized medicine, and more proactive care models. Timestamps 00:00 — Why “Executive War College” became the name and what it signals about lab leadership 02:09 — The evolution of genomics technology since 1995 04:49 — From genetic research to practical diagnostic applications 06:14 — Unlocking the value of lab data for outcomes and cost savings 09:57 — How proactive lab testing can improve maternal and neonatal health 12:56 — Addressing anemia, medication optimization, and other preventable gaps 16:54 — The future of diagnostics, AI, and rapid medical insight 17:43 — Biometric wearables, holistic health, and extending healthspan 20:08 — Nutrition, microbiome, and the shift toward preventive care 25:38 — Lessons from Blue Zones on diet, longevity, and lifestyle 27:24 — Robotics, AI, and aging-in-place care models 32:02 — The future of pharmaceuticals, longevity, and space-age innovation 33:08 — Why innovation communities and early adopters drive progress /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/41164815

The Test That Could Catch Pancreatic Cancer Before It's Deadly 04/21/2026

The Test That Could Catch Pancreatic Cancer Before It's Deadly Are we really close to catching pancreatic cancer early? This silent killer still kills 75% within the first year of diagnosis. But what if we could spot clues before it becomes deadly? Transforming Pancreatic Cancer Detection with Amplified SciencesIn this episode, Bradley Bostic hosts Diana Caldwell, CEO and co-founder of Amplified Sciences, to explore groundbreaking advancements in early detection of pancreatic cancer. Given the devastating prognosis of late-stage diagnosis, their discussion highlights how innovative diagnostics can shift the paradigm towards earlier, less invasive screening—saving lives and improving outcomes.Main insights: The dire statistics of pancreatic cancer survival rates highlight an urgent need for better screening. Amplified Sciences has developed a multi-omics approach that detects precancerous cysts, much like colon polyps, allowing preemptive intervention. The current standard, often reactive, diagnosis leads to late-stage detection; the new method aims to identify risks before symptoms appear. They discuss the importance of high negative predictive value (NPV) to rule out malignancy non-invasively. The platform uses minimal cyst fluid — only 10 times less than existing tests — crucial for small lesions. The approach combines various biomarkers (proteomic, enzymatic, genetic) to improve accuracy. Blood-based screening for early detection remains challenging, but amplification of fluid samples offers more precise insights. Regulatory milestones, like CAP accreditation, position Amplified Sciences for wider clinical adoption. Payer and coverage discussions are ongoing but vital for making this technology accessible. The episode emphasizes how technological innovation, multidisciplinary collaboration, and early detection can revolutionize pancreatic cancer care. Timestamps: 00:11 - Introduction and personal story highlighting the importance of early cancer detection 01:08 - Diana Caldwell's background and motivation to improve gastroenterology diagnostics 04:38 - The science behind Amplified Sciences' diagnostic platform and research origins 07:27 - Current challenges in pancreatic cancer diagnosis and the limitations of standard tests 09:18 - Understanding the brutal statistics and silent progression of pancreatic cancer 10:12 - How genetic factors and incidental screening can identify high-risk individuals 12:41 - The patient journey: from incidental detection to invasive procedures and unmet needs 14:15 - The role of the PANSIS Pro test, regulatory milestones, and sample requirements 16:03 - Differentiating between benign cysts and pre-malignant lesions like IPMN 17:24 - The significance of multi-omic diagnostics and reducing unnecessary surgeries 21:18 - Screening strategies: incidentally detected lesions and the importance of size and location 24:04 - Limitations of current biomarkers like CA 19-9 and the promise of multi-marker panels 26:02 - The unique approach of liquid-focused diagnostics versus traditional blood tests 29:18 - Reimbursement hurdles and the importance of demonstrating clinical utility 32:13 - The mental health impact of uncertain diagnoses and proactive testing benefits 33:55 - The vision for a future where early detection becomes routine and standard careResources & Links: Resources & Links: Amplified Sciences Official Website: Connect with Diana Caldwell on LinkedIn: https://www.linkedin.com/in/dianathompsoncaldwell/ This episode underscores the power of innovative diagnostics to intercept pancreatic cancer early, transforming a deadly prognosis into manageable health outcomes. It highlights the collaborative effort needed across research, regulation, and healthcare platforms to ensure these breakthroughs reach patients. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/40955875

Healthcare is still broken 04/14/2026

Healthcare is still broken How Health Gorilla is Transforming Healthcare Data Interoperability This episode dives into the story of Health Gorilla and its founder, Bob Watson, revealing how innovative approaches are tackling one of healthcare’s most persistent problems: data interoperability. With decades of experience, Bob shares strategic insights and the evolving landscape that is shaping the future of healthcare information exchange.In this episode: Bob Watson’s background at Cerner and lessons from early interoperability efforts The evolution of data blocking strategies and shifting industry tactics How TEFCA’s implementation is creating new momentum for healthcare data sharing The core value propositions behind Health Gorilla’s platform The importance of high-quality, AI-ready healthcare data Challenges and opportunities in integrating medical images into electronic sharing How legacy systems are connected through Health Gorilla’s architecture The role of government regulation and penalties in driving compliance The vision for a future where healthcare data is seamless, actionable, and patient-centric Timestamps:00:00 - Introduction to Bob Watson and the origins of Health Gorilla 00:08 - Bob's experience at Cerner and pioneering early health IT initiatives 00:32 - Building the Connected Community and lessons from early EHR adoption 00:58 - Data blocking strategies in the 90s and their impact on interoperability 01:44 - Bob's transition to turnaround leadership and lessons from multiple engagements 02:15 - The importance of the right team and strategic focus for tech companies 02:28 - Narrowing down core customer profiles and target markets 02:43 - Focus on Epic, Cerner, and e-clinical work as key interoperable systems 03:07 - Value-based care and the role of data in Medicare Advantage programs 03:26 - Developing private lab networks and new use cases under TEFCA 03:52 - How TEFCA’s implementation increases data exchange traffic 04:21 - Facilitating patient data access and reciprocity in information sharing 04:48 - Industry impact of data blocking lawsuits and regulatory changes 05:13 - The federal push for interoperability akin to the HITECH Act 05:39 - Penalties and non-compliance consequences as enforcement tools 06:01 - Delivering high-quality, actionable data for AI and clinical decision-making 06:23 - Personal story: navigating healthcare data transfer challenges as a patient 06:45 - The future of incentivizing interoperability through economic measures 07:07 - Infrastructure at the endpoints vs. legacy system dependencies 07:25 - Delivering consumable, easy-to-interpret data for busy clinicians 07:53 - Reducing care gaps through comprehensive, uniform health records 08:18 - The importance of high-certainty data for AI training and predictive care 09:02 - How Health Gorilla’s curated, accurate data supports advanced AI applications 09:41 - Bob’s return from retired life to address relentless interoperability challenges 10:26 - The evolving role of images and challenges in flowing medical imaging data 11:11 - Vendor issues and technical constraints in transmitting medical images 11:27 - The goal to improve data quality and flow from legacy systems like Meditech 11:51 - Connecting all legacy networks for comprehensive data sharing 12:05 - The potential for Health Gorilla to be a significant player in healthcare interoperability 12:29 - The importance of government support—sticks and carrots—in fostering industry change 12:42 - Closing thoughts: the future of seamless, actionable healthcare data /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/40872040

Why Diagnostics Will Power the Future of Care 04/08/2026

Why Diagnostics Will Power the Future of Care Insights from Eric Strafel of Molecular Testing LabsDiscover how industry veterans are reshaping healthcare through innovative diagnostics, integrating systems thinking, and leveraging AI. In this episode, Eric Strafel discusses the intersection of aerospace principles with healthcare, the future of home testing, and the power of diagnostics as the healthcare data engine. Key Topics: Transition from aerospace innovation to healthcare diagnostics and systems thinking The balance between structured processes and innovation in lab operations How program management practices from defense are transforming healthcare workflows The role of diagnostics in unlocking personalized, data-driven care Impact and evolution of home testing post-pandemic Bridging consumer health and traditional care with digital health tools AI's role in automating workflows and enhancing patient engagement The future of diagnostics as the foundational infrastructure of healthcare Leadership strategies for agility, innovation, and scaling in healthcare labs The importance of early diagnostic engagement for healthy aging Timestamps: 00:00 - Introduction to Eric Strafel and his transition from aerospace to healthcare diagnostics 02:24 - The importance of systems thinking and process robustness from aerospace in healthcare 03:17 - Impact of program management practices in healthcare labs 04:37 - The role of diagnostics in addressing barriers to testing and care engagement 05:24 - The evolution and future of home testing post-pandemic 07:15 - The integration of consumer-centered health and traditional care through digital tools 07:35 - How AI automates lab workflows and improves capacity 09:06 - The vision of diagnostics as the data engine powering personalized healthcare 10:24 - The critical role of diagnostics in the future of healthcare data ecosystems 11:13 - The importance of early diagnostics for healthy aging 12:11 - Leaders' focus on innovation, agility, and scaling in the diagnostic industry Resources & Links: /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/40773195

The Future of Diagnostics Will Be Consumer Driven 04/01/2026

BROKEN ACCESS: 40% CAN’T REACH CARE 03/26/2026

BROKEN ACCESS: 40% CAN’T REACH CARE Transforming Healthcare Access with Simple Health Kit and Mark Cuban Partnership Discover how Dr. Sheena Menezes and Simple Health Kit are revolutionizing healthcare through community-centered platforms, innovative lab kits, and a strategic partnership with Mark Cuban's Cosplus Pharmacy. This episode details the vision for equitable access and the integration of technology in healthcare. In this episode: The foundation and mission of Simple Health Kit in providing accessible healthcare How the platform partners with enterprises to engage underserved populations The significance of Mark Cuban’s Cosplus Pharmacy partnership and its impact on medication affordability The origin story of Sheena Menezes: from Kuwait refugee to healthcare innovator The role of digital and physical channels in delivering health kits and lab testing Vision for the future: bringing high-quality, personalized healthcare to rural and underserved areas The importance of primary care access, especially in rural health settings The influence of technology, including AI and community-focused models, in preventive care Timestamps: - Welcome and overview of Simple Health Kit's mission - How Simple Health Kit puts individuals at the center of care - Major announcement: partnership with Mark Cuban’s Cosplus Pharmacy - Benefits of the partnership for medication access and affordability - Sheena Menezes' inspiring origin story - The drive to bring care to those who need it most - The growth and scale of Simple Health Kit over seven years - How patients can access Simple Health Kit products via health plans, stores, and online - Physical in-store health kits and direct-to-consumer options - The range of lab testing available: diabetes, kidney, cancer, STI - Strategic channels: payers, providers, and pharmacies - Vision for universal healthcare access in the next decade - Focus on high-level, concierge care in underserved areas - Exciting future developments and Mark Cuban connection Resources & Links: Connect with Dr. Sheena Menezes: /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/40633910

80% of Healthcare Data Is Locked Away. AI Is Finally Breaking It Open. 03/24/2026

80% of Healthcare Data Is Locked Away. AI Is Finally Breaking It Open. Show Notes What if the most valuable data in healthcare has been sitting in plain sight the entire time, buried inside millions of clinical notes no one can actually use? Live from ViVE, Marcus Gordon sits down with Dr. Tim O’Connell, co-founder and CEO of Emtelligent and a practicing radiologist, for a conversation about one of the biggest blind spots in modern healthcare: unstructured data. Dr. O’Connell breaks down why health systems are overflowing with information yet still starving for actionable insight, and why unlocking clinical notes at scale could change everything from patient care to cost control to real-world evidence. This episode gets into the real tension behind AI in healthcare. The technology is moving fast, but the stakes are too high for blind automation. Diagnoses, claims, treatment decisions, and chart review cannot become black-box exercises. Dr. O’Connell makes the case for clinician-led AI, where humans stay firmly in control and technology does what it does best: surface critical information faster, more accurately, and at scale. The conversation also explores why radiology has long been seen as a digital pioneer, why AI adoption in clinical workflows may actually be moving faster than in imaging, and what it will take for health systems, payers, and life sciences companies to responsibly share data in ways that improve care without compromising trust. This is a conversation about where healthcare is actually headed, not in theory, but in practice. In this episode: Why an estimated 80% of healthcare data lives in unstructured clinical notes The real reason health systems are data rich but insight poor Why human-in-the-loop AI is non-negotiable in healthcare How AI-assisted chart review can reduce friction for clinicians Why radiology may not be the AI leader people assume it is What better data sharing could mean for cost, quality, and real-world evidence Why the future of healthcare depends on turning documentation into decisions /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/40604890

Beyond AI Hype: What’s Real in Healthcare Now 03/18/2026

The Operating System for Modern Healthcare 03/13/2026

From Bedside to Webside Manner: Telehealth’s Impact on Rural Healthcare 03/10/2026

AI Accelerates Patient Empowerment 03/09/2026

AI, Outcomes, and the Future of Care with Aneesh Chopra, First U.S. CTO 03/03/2026

Blood Health: The Bottleneck Nobody's Talking About 02/11/2026

Brain & Spinal Injuries: When Insurance Says You’re Done | Ep. 60 02/03/2026

Brain & Spinal Injuries: When Insurance Says You’re Done | Ep. 60 Insurance funded therapy often ends fast. Recovery does not. In this follow up episode, Bradley Bostic talks with Chris Leeuw, CEO of NeuroHope, about the “rehab cliff” facing spinal cord injury, brain injury, stroke, and MS patients when they leave inpatient care and quickly run out of covered visits. Chris shares what NeuroHope is building in Indianapolis to keep recovery going: a model that blends skilled therapy, trained kinesiologists, adaptive fitness, and a true community so patients can continue progressing long after insurance stops paying. They also unpack the expanding vision behind the Driven Neuro Recovery Center, developed with the Conquer Paralysis Now, and why this kind of recovery ecosystem is becoming essential infrastructure for the disability community. In this episode, you’ll learn Why “30 visits” is not neuro recovery How NeuroHope makes long term therapy more affordable after coverage runs out What’s changed since last year including 30 percent growth in services Early outcomes from a two year study tracking complications and readmissions Why community is often the difference between surviving and thriving What’s emerging in rehab tech including trans spinal stimulation and what it could unlock The bigger campus vision and what partners could help make possible Help NeuroHope close the rehab gap If you believe recovery should not end when insurance does, here are three simple ways to help: Watch and share this episode Send it to one person navigating stroke, spinal cord injury, or brain injury recovery, or to a clinician who needs a better option to refer to. Support NeuroHope’s mission NeuroHope relies on community support to keep long term therapy accessible after coverage runs out. If you’re able, consider donating or becoming a sponsor. Partner in Indianapolis NeuroHope is building a broader recovery ecosystem and is looking for aligned partners across adaptive sports, mental health, vocational rehab, DME, and innovative rehab technology. Guest Chris Leeuw is the CEO of NeuroHope, focused on expanding access to long term neuro recovery through therapy, wellness, and community. View the NeuroHope Wellness Center: Learn more about NeuroHope: https://www.neurohopewellness.org/ /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/39982020

A $2,000 Voucher and 600 Patients: The Math Behind Fixing Care | Ep. 59 01/20/2026

A $2,000 Voucher and 600 Patients: The Math Behind Fixing Care | Ep. 59 🤔 Did you know that 30-50% of Americans lack access to primary care? That's a staggering number! Bradley Bostic sits down with Matthew Holt (The Health Care Blog) for a blunt diagnosis of what’s broken in U.S. healthcare and a concrete, numbers-driven proposal to fix it. Holt doesn’t just complain. He names incentives, calls out the money flows, and lays out a primary-care “voucher” model designed to cut downstream costs while making primary care a top-tier, high-status job again. If your organization is still treating primary care like a loss leader and “leakage” like a KPI, this one will sting (in the right way). Timestamps 00:00 – 01:20 HLTH 2025 setup + dark humor about “keeping subscribers alive” 01:20 – 05:30 Holt’s blunt system diagnosis + “nonprofit” and executive pay critique (UPMC example) 05:30 – 08:45 Primary care access crisis + why the ER becomes the default front door 08:45 – 10:50 “Leakage” + the referral-engine reality inside employed primary care 10:50 – 13:15 The concierge-for-all voucher model (the simple math) 13:15 – 16:30 Bradley connects it to value-based care + incentive shifts 16:30 – 18:10 Wrap: fewer complaints, more solutions + where to follow Holt What you’ll hear Why the U.S. system is expensive by design — and why consumers carry the anxiety. The uncomfortable truth about “nonprofit” health systems, executive comp, and transparency. How primary care got turned into a referral engine for high-margin services. Holt’s two-step path to reform, including a “concierge-for-all” model with simple math behind it. Where this intersects with value-based care… and where today’s versions still fall short. To learn more about The Healthcare Blog, visit here: https://thehealthcareblog.com/blog/category/health-tech/matthew-holt/ /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/39804195

The $1 Trillion Problem Nobody Talks About in Healthcare 01/13/2026

The $1 Trillion Problem Nobody Talks About in Healthcare Guest: Fawad, Founder & CEO, Penguin AI (former CDO/data leader across major payer/provider organizations) Healthcare isn’t broke because we lack innovation. It’s broke because we spend a staggering amount of money moving paper, arguing over rules, and chasing “documentation” instead of outcomes. From the HC1 booth at Health 2025 in Vegas, Bradley sits down with Fawad—a veteran healthcare data operator turned founder—to talk about the real enemy: administrative waste at trillion-dollar scale… and why slapping GPT on top of messy systems just gives us a confident-sounding parrot. Penguin AI is building an AI-first healthcare platform designed to run workflows end-to-end across payers and providers—prior auth, revenue cycle, claims, coding, and more—without forcing teams to become AI engineers. What you’ll hear in this episode Why “AI in healthcare” is mostly theater if your data is fragmented, dirty, and politically guarded The uncomfortable truth: administration is the cost center eating the system alive Why GPT can sound brilliant and still be dangerously wrong (“a very smart fairy”) The case for healthcare-specific platforms (not generic clouds + hope) Why “payer vs provider” is an outdated segmentation—and processes prove it Founder reality: leaving big-title comfort for the zero-to-one grind The Penguin story: branding that grabs attention and signals how hard healthcare change really is Key takeaways 1) If your AI strategy starts with a chatbot, you’re already late. Start with the workflow. Start with the administrative bottlenecks. Then decide what intelligence belongs inside. 2) “Dr. GPT” is confident, not accountable. Fawad’s warning is simple: models generate plausible language from what they’ve seen. In healthcare, plausible can still be wrong—and wrong has consequences. 3) The real prize isn’t automating tasks. It’s removing friction across the payer–provider boundary. Prior auth doesn’t “belong” to one side. Neither does claims. Neither does adjudication. The process crosses the membrane—so the platform has to, too. 4) Healthcare doesn’t need more AI demos. It needs clean, longitudinal records and execution. Better models require better inputs—and partnerships that unlock high-quality, de-identified, longitudinal patient data for real learning (not internet noise). Notable moments (timestamps) 00:00 — Live from Health 2025 in Vegas: meet Fawad, founder of Penguin AI 00:26 — From big-company data leadership to startup founder 01:48 — The brand: why “Penguin” (and why most tech names are nonsense) 04:34 — The core problem: admin work at massive scale (prior auth, claims, RCM, scheduling) 06:00 — “Dr. GPT”: why it sounds right even when it’s wrong 07:31 — Funding + momentum: Penguin’s Series A and growth 08:00 — Building better clinical intelligence requires real healthcare-grade data 09:28 — Operator-to-founder: why more insiders need to jump into the arena 11:50 — What Penguin actually does: agents, customization, and “platform-level” scale 14:05 — Why payer vs provider is a false divide Who this episode is for Health system and payer leaders drowning in prior auth, claims, RCM, coding, and operational drag Operators skeptical of hype who want real automation + measurable cost reduction Founders building AI in healthcare who are ready to confront the data + workflow reality Investors looking for platforms that can win beyond “pilot purgatory” Call to action If your team is “doing AI” but still living inside manual workflows, this is your wake-up call: Stop demo-chasing. Start workflow-owning. 🎧 Watch/listen to the full episode: https://youtu.be/j_Fsuy-BfTM 📌 Learn more about Penguin AI: https://www.penguinai.co /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/39721905

Ep 57: IU Health CEO Dennis Murphy on Building a Healthcare System That Actually Works 01/06/2026

Ep 57: IU Health CEO Dennis Murphy on Building a Healthcare System That Actually Works IU Health CEO Dennis Murphy joins Bradley Bostic to unpack what it takes to drive innovation at scale—across 16 hospitals and 300+ clinical sites. They cover values-based culture, platform-first AI strategy, statewide data collaboration, philanthropy as a “margin of excellence,” and IU Health’s new flagship campus—set to see its first patients in December 2027. Chapters 00:00 Introduction to Healthcare Innovation 01:56 Leadership and Organizational Values 04:50 Flagship Hospital Project Overview 08:18 Optimism in Healthcare 12:08 Technology and AI in Healthcare 17:40 Philanthropy and Community Impact 23:13 Data Utilization in Healthcare 28:37 Personalization of Healthcare Experience 34:53 Future of IU Health and Closing Remarks In this episode of the Boombostic Health podcast, host Bradley Bostic interviews Dennis Murphy, CEO of IU Health, discussing his extensive experience in healthcare leadership, the importance of organizational values, and the innovative projects at IU Health, including a new flagship hospital. They explore the optimism surrounding advancements in healthcare technology, the role of philanthropy in enhancing patient care, and the significance of data aggregation in improving health outcomes. The conversation emphasizes the need for personalized healthcare experiences and the future of healthcare delivery. Takeaways Dennis Murphy has a diverse background in healthcare leadership. Organizational values are crucial for guiding employee behavior. Philanthropy plays a significant role in enhancing healthcare programs. Technological advancements are improving patient outcomes significantly. Data aggregation is essential for effective healthcare delivery. IU Health is focused on attracting top talent in the healthcare industry. The new flagship hospital aims to consolidate resources and improve care. Healthcare innovation is driven by both institutional providers and entrepreneurs. Personalized healthcare experiences are becoming increasingly important. Optimism in healthcare is fueled by ongoing advancements and creative solutions. /episode/index/show/84fc912f-3f91-4b5a-a3f8-d2addda898bb/id/39632775

Ep 56: How At-Home Lab Testing Works (Behind the Kit) 12/23/2025

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