HealthTech2Care Podcast

S2E11: Flip's Voice AI Growth From Retail to Healthcare | HT2C Podcast With Bert Fernandez

HealthTech2Care (HT2C) Podcast featuring Brian Schiff, Co-Founder & CEO of Flip. Brian Schiff (Guest): 🔗 LinkedIn: https://www.linkedin.com/in/bschiff [https://www.linkedin.com/in/bschiff] 🌐 Website: https://flipcx.com [https://flipcx.com] 📺 YouTube: http://www.youtube.com/@goflipcx [http://www.youtube.com/@goflipcx] Bert Fernandez (Host): 🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez [https://www.linkedin.com/in/bert-fernandez] 🌐 Website: https://www.healthtech2care.com [https://www.healthtech2care.com] 📺 YouTube: https://www.youtube.com/@healthtech2care [https://www.youtube.com/@healthtech2care] 🎙️ In this episode, Brian Schiff shares how Flip evolved from early voice AI experiments in retail to a scaled platform serving 250+ brands and hundreds of millions of phone calls, including household names like Tory Burch and Under Armour. We unpack what triggered Flip's move into healthcare, why urgent care became the ideal entry point, and how the team scaled from a small pilot to thousands of clinics in under two years. Brian also breaks down the "phone problem" in healthcare, where 30–40% of calls go unanswered, and explains how replacing traditional IVRs with AI can improve patient experience, reduce missed visits, and ease pressure on front desk staff. This conversation highlights why voice AI is one of the fastest, lowest-friction ways for healthcare organizations to start adopting AI and drive immediate, measurable impact. ⏱️ Timestamps: 00:00 Intro 00:52 Brian's background and how Flip evolved from early voice AI to today 03:02 Move from retail to healthcare and what triggered the shift 07:33 What Flip saw in healthcare that others were missing 13:58 The phone problem in healthcare and what actually changes when replacing IVRs with AI 18:00 Why urgent care was the right entry point and why adoption happened quickly 22:02 Implementation vs reality and why Flip is easier to deploy (including integrations) 26:06 Expanding beyond urgent care and what makes a specialty a good fit 28:41 Inbound and outbound communication across the patient journey 32:04 How to engage with Flip and what to have prepared 🔑 Highlights: - Why voice AI adoption is accelerating in healthcare - The 30–40% missed call problem in urgent care - How call-to-visit conversion impacts revenue and access - Why Flip's industry-specific approach drives faster adoption - The opportunity to automate both inbound and outbound patient communication 👉 Learn more about Flip's voice AI product for Retail eCommerce, Transportation, and Healthcare Brands: https://flipcx.com [https://flipcx.com] 🔔 Subscribe to the HealthTech2Care YouTube channel for more in-depth conversations with healthcare innovators: https://www.youtube.com/@healthtech2care [https://www.youtube.com/@healthtech2care] #VoiceAI #HealthTech #PatientExperience #DigitalHealth #HealthcareInnovation #AI

S2E10: AI Adoption + Governance in Regulated Industries | HT2C Podcast With Bert Fernandez

HealthTech2Care (HT2C) Podcast featuring Marco Smit, Chief Commercial Officer (CCO) & COO of DomeLabs AI, which includes the ClearPath platform. Marco Smit (Guest): 🔗 LinkedIn: https://www.linkedin.com/in/marco-smit-ai [https://www.linkedin.com/in/marco-smit-ai] 🌐 Website: http://domelabs.ai [http://domelabs.ai] Bert Fernandez (Host): 🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez [https://www.linkedin.com/in/bert-fernandez] 🌐 Website: https://www.healthtech2care.com [https://www.healthtech2care.com] 📺 YouTube: https://www.youtube.com/@healthtech2care [https://www.youtube.com/@healthtech2care] 🎙️ In this episode, Marco Smit shares how organizations in healthcare, pharma, and other regulated industries are approaching AI adoption, and why treating AI as an IT problem is one of the biggest mistakes being made today. We unpack what's driving bottlenecks in AI implementation, including real-world examples where evaluating and deploying a new AI use case can take up to 8 months, and how that delay leads to shadow AI and increased risk. Marco also explains how DomeLabs AI's ClearPath platform helps organizations move from slow, fragmented approval cycles to more structured, scalable AI governance, while balancing speed, compliance, and risk. This conversation explores what it actually takes to turn AI potential into real-world impact in regulated environments. ⏱️ Timestamps: 00:00 Intro 01:18 What drew Marco to DomeLabs, and why this was the right moment to make the move 05:07 Biggest misconceptions about GenAI and agentic AI in healthcare and life sciences 08:52 What ClearPath actually does and what problems it solves 15:47 What it takes to turn AI potential into results from a governance perspective 23:41 How real the job displacement threat is and what employees should do 30:06 Whether open-source AI is a legitimate concern and how to handle it 36:02 Where people can learn more about DomeLabs and connect 🔑 Highlights: - Why AI should be treated as a business transformation, not an IT project - How long AI approval cycles create bottlenecks and risk - The rise of shadow AI in regulated organizations - How governance and control layers accelerate adoption - What organizations need to do now to stay competitive with AI 👉 Learn more about Domelabs AI (http://domelabs.ai [http://domelabs.ai]) 🔔 Subscribe to the HealthTech2Care YouTube channel for more in-depth conversations with healthcare innovators: https://www.youtube.com/@healthtech2care [https://www.youtube.com/@healthtech2care] #HealthTech #HealthcareAI #AIGovernance #AgenticAI #LifeSciences #DigitalTransformation

S2E9: Fixing Contracting Upstream in Healthcare | HealthTech2Care Podcast With Bert Fernandez

HealthTech2Care (HT2C) Podcast featuring Danielle Haugland, Sr. Director of Global Alliances at Agiloft Danielle Haugland (Guest): 🔗 LinkedIn: https://www.linkedin.com/in/danielle-haugland-67473a39 [https://www.linkedin.com/in/danielle-haugland-67473a39] https://www.healthtech2care.com🌐 Website: https://www.agiloft.com [https://www.agiloft.com]https://www.linkedin.com/in/bert-fernandez 📺 YouTube: www.youtube.com/@Agiloft [https://www.youtube.com/@Agiloft] Bert Fernandez (Host): 🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez [https://www.linkedin.com/in/bert-fernandez] https://www.healthtech2care.com🌐 Website: https://www.healthtech2care.com [https://www.healthtech2care.com] https://www.linkedin.com/in/bert-fernandez 📺 YouTube: https://www.youtube.com/@healthtech2care [https://www.youtube.com/@healthtech2care] 🎙️ In this episode, Danielle Haugland shares how her background in commercial litigation shaped her perspective on contracts, and why by the time a contract becomes a legal issue, the operational damage has already been done. We discuss why healthcare systems are rethinking contract lifecycle management as a core operational lever, especially amid reimbursement pressure, rising costs, and financial strain across provider organizations. Danielle also walks through real-world examples, including Agiloft's work with Rush University Medical Center, where fragmented workflows, long approval timelines, and process workarounds were replaced with centralized, structured contracting that improved speed, visibility, and control. This conversation highlights how fixing contracting upstream can reduce risk, improve financial discipline, and create more resilient healthcare operations. ⏱️ Timestamps: 00:00 Intro 01:09 What Danielle's litigation background taught her about what goes wrong with contracts 04:45 What pressures are driving provider organizations to get a better handle on CLM 09:47 What happened in the Rush University Medical Center case study and what outcomes came from fixing CLM upstream 14:43 Why it is so difficult for health systems to fix this with their existing stack 17:36 Why centralization matters in disruptions and how it helped organizations like Children's National respond 22:03 Why configurability matters in CLM and how Agiloft addresses the nuance across provider organizations 26:00 What common sticking points keep coming up and how Agiloft helps address them in the platform 30:26 What other provider use cases come up beyond payer contracting and where CLM fits operationally 33:47 How providers should engage Agiloft and what they should have prepared before starting the conversation 35:43 Whether Agiloft itself provides audits or works through partners 🔑 Highlights: -Why most contract issues start as operational problems, not legal ones -How healthcare systems can use contracting as a financial lever -The impact of fragmented workflows and long approval timelines -Results from centralizing and restructuring contracting processes -Why centralization is about resilience, not bureaucracy 👉 Learn more about Agiloft (https://www.agiloft.com [https://www.agiloft.com]) 🔔 Subscribe to the HealthTech2Care YouTube channel for more in‐depth conversations with healthcare innovators: https://www.youtube.com/@healthtech2care [https://www.youtube.com/@healthtech2care] #CLM #HealthcareAI #HealthcareOperations #Procurement #RevenueCycle #DigitalTransformation

S2E8: Closed-Loop Platform for Research + Conversational Agents | HT2C Podcast with Bert Fernandez

HealthTech2Care (HT2C) Podcast featuring Amir M. Rahmani, Professor at UC Irvine and Co-Founder of Integrated AI Systems, which includes Centralive (Closed-Loop Platform for Clinical Research) and openCHA (Conversational Health Agents). In this episode, Amir M. Rahmani shares how his background in computer science, IoT, and digital health research led to building platforms designed for real-world clinical research and patient engagement. He explains why so many research teams end up reinventing the wheel with every new grant, and why platforms often disappear once funding runs out. We also cover how Centralive and openCHA address this problem by providing reusable, modular infrastructure for data capture, real-time sensing, analytics, and intervention. Amir breaks down the idea of "closed-loop" systems using simple analogies, like cruise control and navigation, to explain why continuous sensing, sense-making, and action are critical for personalization in healthcare. This conversation explores how conversational health agents fit into closed-loop workflows, why large language models alone are often overkill for healthcare problems, and how agents can orchestrate evidence-based knowledge, validated models, and real patient data. Amir also shares how these platforms are being used across academia, RPM programs, decentralized trials, and digital therapeutics, along with what kinds of partners and pilots he's looking for next. Timestamps: 00:00 Intro 01:05 What pulled Amir into healthcare tech, and how it led to Centralive and openCHA 04:51 What problems in academic research led to productizing Centralive 09:48 What makes Centralive different and how it simplifies sensing, EMAs, analytics, and interventions 16:02 How study teams adopt Centralive and what the grant-driven adoption path looks like 20:28 What inspired openCHA and how it supports workflows like RPM, research, and decentralized trials 30:34 What partners and opportunities Amir is looking for across Centralive and openCHA 34:12 Best way to get in touch or try Centralive and openCHA Highlights: - Why do most research platforms disappear when a grant ends - How closed-loop systems enable real-time personalization - The difference between static workflows and adaptive interventions - Why conversational agents need evidence, not just LLMs - Where closed-loop platforms and agents fit in clinical research, RPM, and DTx Learn more about Centralive (https://centralive.health) and openCHA (https://www.opencha.com) Amir M. Rahmani (Guest): 🔗 LinkedIn: https://www.linkedin.com/in/amir-m-rahmani-26555b44 [https://www.linkedin.com/in/amir-m-rahmani-26555b44] 🌐 Website: https://centralive.health [https://centralive.health] 📺 YouTube: http://www.youtube.com/@CentraliveTeam [http://www.youtube.com/@CentraliveTeam] Bert Fernandez (Host): 🌐 Website: https://www.healthtech2care.com [https://www.healthtech2care.com] 🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez [https://www.linkedin.com/in/bert-fernandez] 📺 YouTube: https://www.youtube.com/@HealthTech2Care [https://www.youtube.com/@HealthTech2Care] Subscribe to the HealthTech2Care YouTube channel for more in‐depth conversations with healthcare innovators #DigitalHealth #ClinicalResearch #ClosedLoop #HealthcareAI #ConversationalAI #RemotePatientMonitoring #HealthTech

S2E7: The First On-Device Medical LLM | HealthTech2Care Podcast With Bert Fernandez

HealthTech2Care (HT2C) Podcast featuring Stephen Rouse, Co-Founder and Head of Growth at Savva.AI Stephen Rouse In this episode, Stephen Rouse shares how his experience building one of the earliest FHIR apps shaped Savva's approach to consumer health technology. We unpack why multi-year hospital buy cycles pushed the team to build directly for patients, how the ONC Cures Act unlocked large-scale access to health data, and why Savva chose to build the first on-device medical LLM to prioritize privacy and security. We also cover how Savva connects to nearly 300,000 care sites through 110+ EHRs, why keeping medical AI off the cloud matters, how Apple Health enables aggregation across wearables and devices, and how caregiver and clinician access could become a stepping stone toward real-world care escalation. This conversation explores what it truly means for patients to own their health data and why this moment feels like a turning point for consumer-driven healthcare. Timestamps: 00:00 Intro 01:17 Lessons from Protocol First and why hospital sales cycles pushed a consumer-first approach 03:44 How Savva unlocked scale through the ONC Cures Act and FHIR access 05:42 What it means to be an on-device medical LLM and why privacy drove that decision 08:51 How Savva aggregates wearable and Apple Health data into one experience 12:30 The caregiver and clinician vision for real-world care delivery 16:41 Beta strategy, early traction, and what's next for Savva 🔑 Highlights: - Why four-year hospital buy cycles pushed Savva to build for consumers - How the ONC Cures Act enabled third-party access to EHR data at scale - What makes an on-device medical LLM different from cloud-based AI - How Savva aggregates wearables, apps, and devices through Apple Health - The role of caregivers and clinicians in turning raw data into action (Guest): 🔗 LinkedIn: https://www.linkedin.com/in/rousestephen [https://www.linkedin.com/in/rousestephen] 🌐 Website: https://www.savva.ai [https://www.savva.ai] 📺 YouTube: http://www.youtube.com/@getSavva [http://www.youtube.com/@getSavva] Bert Fernandez (Host): 🌐 Website: https://www.healthtech2care.com [https://www.healthtech2care.com] 🔗 LinkedIn: https://www.linkedin.com/in/bert-fernandez [https://www.linkedin.com/in/bert-fernandez] 📺 YouTube: https://www.youtube.com/@HealthTech2Care [https://www.youtube.com/@HealthTech2Care] 🔔 Subscribe to the HealthTech2Care YouTube channel for more in‐depth conversations with healthcare innovators: https://www.youtube.com/@HealthTech2Care [https://www.youtube.com/@HealthTech2Care] #HealthTech #DigitalHealth #HealthcareAI #ConsumerHealthApp #PatientData #PrivacyByDesign #FHIR #ONCCuresAct