Can Diagnostics Solve the Healthcare Cost Crisis?

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.

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

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 00:00 [https://www.youtube.com/watch?v=ccNxEOeqPPI] Welcome and personal connection to cancer prevention 03:01 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=181s] Dr. Bekelman's background and why patients still fall through the cracks 05:30 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=330s] What value-based care means in oncology 07:28 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=448s] Why supportive cancer care is under-reimbursed in fee-for-service 09:17 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=557s] How Daymark Health partners with health plans 10:32 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=632s] Supporting patients at home, virtually, and at no additional cost 12:44 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=764s] Episodic capitation, shared savings, and oncology economics 15:18 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=918s] Why cancer care is well suited for value-based models 17:24 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=1044s] Daymark as the "connective tissue" around the oncologist 20:34 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=1234s] Why coordination alone is not enough 23:01 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=1381s] Daymark's work with Blue Cross Blue Shield of Rhode Island 24:08 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=1448s] Steven's story and why cancer does not stop at 5 PM 27:37 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=1657s] Patient experience, home visits, and measurable results 30:19 [https://www.youtube.com/watch?v=ccNxEOeqPPI&t=1819s] 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

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 hc1 [https://hc1.com/] uMed [https://www.umed.io/about-us] Simple HealthKit [https://www.simplehealthkit.com/about] 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.

The Hospital Room That Watches Over Patients (Without Replacing Nurses)

The hospital room is becoming intelligent. In this episode of Boombostic Health, Bradley Bostic sits down with Adam McMullin, CEO of AvaSure, to discuss how AI-enabled virtual care is helping health systems improve patient safety, support nurses, and extend clinical capacity without losing the human touch. AvaSure pioneered virtual safety and is now helping hospitals move beyond pilots into scalable, ROI-driven care transformation. Adam shares how intelligent room technology, computer vision, virtual nursing, and open platform integrations are changing what care teams can see, how quickly they can act, and where scarce clinical resources can be used most effectively. The conversation gets into the real pressures facing health systems today: patient falls, ED boarding, documentation burden, specialty access, workforce shortages, and the rising issue of violence against care teams. This is not a conversation about AI replacing clinicians. It is about using AI and virtual care infrastructure to give clinicians better visibility, better support, and more time with patients. Key Topics Virtual safety and the future of patient observation How intelligent rooms can reduce risk and improve workflow Why hard-dollar ROI matters for scaling healthcare technology The role of AI, computer vision, and virtual nursing in care delivery How AvaSure is helping health systems bring more human connection back into care Key Takeaway The future of hospital innovation is not more disconnected technology. It is intelligent infrastructure that helps care teams act sooner, work smarter, and care better.