Integrating Healthcare Services

This well-intentioned claim has killed more provider-focused healthcare startups than any other: "We'll integrate with any EHR!" The reality of healthcare integration: Epic integration isn't just technical – It's political. Without App Orchard certification, you're facing 6+ months of custom work per client. With it, you still need local IT champions and competing priorities. Cerner's domain model creates fundamentally different data structures across implementations. What works at Intermountain won't work at Ascension without significant customization. Meditech/CPSI/Athena customers often lack the technical resources to manage complex integrations – regardless of what your sales team promises. HL7 isn't a standard – it's a framework. Each organization implements it differently, with custom segments, Z-segments, and proprietary extensions. FHIR readiness varies wildly – Most health systems have implemented just enough to meet Meaningful Use requirements, not enough to support your full workflow. The operational blindspots: Integration governance means your solution competes against 50+ other projects. Interface engine capacity is a finite resource you didn't budget for. Testing environments that don't match production. Downtime procedures you didn't design for. This isn't just a technical challenge. It's a market architecture problem that must be solved pre-sale. The most successful healthcare technology companies don't have the "best" integration – they have the most pragmatic implementation strategy that aligns with how health systems actually work. If your deals are stalling during implementation, let's diagnose the real issues. #healthcareintegration #implementationstrategy #ehrimplementation

🧬 We talk about “health data” as if it’s one thing, but it’s really hundreds of incompatible languages trying (and failing) to talk to each other. Every layer speaks a different dialect: • EHRs: HL7 v2, CDA, FHIR • Claims: X12 837, UB-04, CMS-1500 • Labs: LOINC, SNOMED CT • Devices: DICOM, IEEE 11073 • Genomics: VCF, FASTQ, BAM Each was built for a single purpose, not interoperability. The result? 🚑 A patient’s data is scattered across 40+ systems, each with its own schema, timestamps, and access controls. But things are shifting. Newer models are moving beyond formats to: • Graph-based data structures • Semantic layers • Federated architectures These approaches preserve context, not just content, across systems. FHIR paved the road. But the next frontier is semantic interoperability. That’s not just data exchange; it’s data understanding. 🧠 The future of healthcare intelligence isn’t in collecting more data, it’s in connecting meaning. #HealthTech #DataInteroperability #FHIR #HealthcareAI #KnowledgeGraphs #SemanticWeb

Epic's comprehensive response to the Centers for Medicare and Medicaid Services (CMS) Request for Information on the Health Technology Ecosystem reveals unprecedented opportunities for health tech entrepreneurs and vendors. I wrote a long analysis (linked in comments) that examines seven key areas where Epic's recommendations could fundamentally reshape the healthcare technology landscape: 1) National Healthcare Directory: Creation of a unified, federated directory system requiring specialized implementation services and integration solutions 2) Digital Identity Infrastructure: Development of interoperable credential service providers and patient-centric identity management tools 3) TEFCA Expansion: Broadening use cases for the Trusted Exchange Framework creating new API-based business models 4) Certification Streamlining: Reducing regulatory barriers while maintaining interoperability standards 5) Quality Measurement Evolution: Transition to FHIR-based reporting systems and real-time analytics 6) Information Blocking Safe Harbors: Clear compliance pathways encouraging innovation and market entry 7) LLM Integration: Opportunities for AI-powered healthcare applications using structured and unstructured data These recommendations signal a shift toward open, standardized, and patient-controlled healthcare data ecosystems, creating fertile ground for entrepreneurial innovation across infrastructure, applications, and services.

We are entering a new paradigm in #healthcare: consumers will soon generate and collect more health data than what is captured within the healthcare system and stored in Electronic Health Records (#EHR). This is great news for individuals. But it should concern healthcare systems. The pace of data collection in EHRs hasn’t changed much in decades—prescriptions, diagnoses, lab results, services provided, and occasional notes. It’s the same velocity as 20 years ago when #paper #files were the norm. Meanwhile, the speed and volume of data collected by #smartwatches, #smartphones, and other smart devices are skyrocketing. We’re approaching a point where the gap between #consumer #data and #EHR #data will be so large that it could lead to a loss of trust in healthcare systems. If healthcare systems don’t start integrating consumer data into EHRs, they will roll out the red carpet for #bigtech companies to take on the role of healthcare and well-being providers. The result? A healthcare system misaligned with social and technological progress—and one that no one trusts. Do you agree?

🚨 Case Study Highlight: The Power of ŌURA Integration & GluCare.Health's Continuous Care 🚨 Today in the clinic, we witnessed a fantastic example of how our Oura Ring integration and continuous care model are revolutionizing patient diagnostics and outcomes! 🌟 An existing GluCare diabetic patient came in for a routine stress test with our Cardiologist, Dr. Idalys. During the test, we observed abnormal heart rate recovery and numerous PVCs (premature ventricular contractions). Instead of relying solely on the test results, Dr. Idalys took a proactive approach and checked the patient’s historic Oura Ring data. 📊 Here’s what we found:  ✅ Heart Rate Sync: The Oura heart rate readings were perfectly aligned with the ECG’s readings based on timestamps.  ✅ Hidden Patterns: The Oura data revealed that the patient had been experiencing borderline high heart rates for a while—something previous in-clinic tests had missed. Despite a normal ECG a few days prior and no current symptoms, the data indicated a potential issue. Typically, a heart rate > 120 for more than 10 minutes warrants arrhythmia screening. In this case, the data showed that the patient had Intermittent Ventricular Bigeminy, where every other heartbeat is a premature contraction.  He’ll wear a Holter monitor for 24 hours, and if the PVC burden is > 24 %, the likelihood of developing PVC induced cardiomyopathy is high – but a curable condition (typically ablation). This situation perfectly illustrates how combining continuous real-time data with in-clinic diagnostics offers a more comprehensive view of patient health. 🌐❤️ 🔍 Key Takeaway: Traditional episodic care might miss crucial trends and abnormalities. By integrating continuous monitoring with clinical insights, we’re able to detect issues that might otherwise go unnoticed, leading to better patient care and outcomes. 👩⚕️📈 Ihsan Almarzooqi Zeina A. Yousef Said, MD Idalys Roman Fernandez MD Tom Hale Hannah Parish #HealthcareInnovation #PatientCare #Cardiology #OuraRing #ContinuousMonitoring #HealthTech #GluCare #MedicalDiagnostics #Arrhythmia #HealthData #ClinicalInsights

Most healthcare AI doesn't stall because models underperform. It stalls because infrastructure is fragmented. We are no longer constrained by algorithmic creativity. We are constrained by data silos, privacy governance, interoperability gaps, compute access, and the operational friction of translating retrospective research into prospective clinical impact. This brief examines this structural bottleneck through the Mayo Clinic Platform. The authors focus on something foundational: building an AI-ready ecosystem designed to accelerate real-world clinical research at scale. The platform provides a secure, cloud-based research environment built on de-identified, standardized EHR data from more than 15 million patients. Key capabilities include: ⭐ OMOP-aligned data models for interoperability ⭐ Structured and unstructured data ⭐ Cohort-building and schema exploration tools ⭐ Integrated workspaces with scalable CPU/GPU infrastructure ⭐ Both no-code and advanced coding environments Unlike traditional institutional repositories, Mayo Clinic Platform enables access for external researchers, supports federated multi-institutional data contributions, and embeds analytics within a privacy-preserving architecture. The paper highlights four applied studies conducted within MCP: 1️⃣ RCT emulation for heart failure drug efficacy using observational data 2️⃣ Validation of antihypertensive medications and reduced dementia risk 3️⃣ Deep learning prediction of mild cognitive impairment progression to Alzheimer’s disease 4️⃣ Neural network prediction of major adverse cardiovascular events after liver transplantation Extracting a cohort of ~15,000 patients took approximately one week. Training and running a deep learning model required roughly 10 minutes on moderate compute resources. When infrastructure friction is minimized, research velocity changes materially. Competitive advantage in healthcare AI is increasingly defined by: 💫 Data harmonization at scale 💫 Federated, privacy-preserving architectures 💫 Reproducible research pipelines 💫 Integrated compute environments 💫 Lower barriers for clinician engagement The authors also point toward multimodal expansion (notes, imaging, genomics), large-scale cross-institutional validation, and “Clinical Trials Beyond Walls” models that broaden participation and diversify real-world evidence. For those shaping AI strategy in health systems, pharma, or digital health, this paper offers a concrete example of production-grade, AI-ready infrastructure. The future of healthcare AI will not be won by isolated models. It will be won by platforms that integrate data, governance, compute, and workflow into a coherent operating system for translational impact. John Halamka, M.D., M.S. and team, great work! #HealthcareAI #HealthSystems #RealWorldEvidence #ClinicalResearch #DigitalHealth #TranslationalMedicine #PrecisionMedicine #HealthData #AIInfrastructure #MedicalInnovation

Care delivery companies: don’t repeat my mistake! Don’t design for more efficiency when what you need is more humanity. A few months into building Iron Health, we had a problem: patients weren't attending follow-up appointments at the rate we expected. So we did what any rational product team would do - we built solutions. More personalized appointment reminders, SMS instead of email, simpler rescheduling flows. And it only kind of worked. We saw a small bump in appointment attendance, but not enough to move the business. So we went back to the data. We read every word of feedback, tracked every single patient journey, asked every provider what they were seeing. Here's what we learned: the patients who came back weren't the ones who received the most outreach. They were the ones who had a strong relationship with their provider. Not a good experience with the platform, a genuine connection with a person. They showed up for appointments because they didn't want to let someone down. Because they looked forward to time with someone who cared about them. Because that relationship carried weight, emotional and human weight, that no appointment reminder could replicate. So we changed our strategy. We stopped investing primarily in workflow optimization and started investing in relationship acceleration. We designed ways for patients and providers to connect before the first appointment. We created touchpoints between visits that built trust and continuity. We gave providers tools to be more present, more human, more themselves, at scale. Turns out, helping providers scale their humanity is good business strategy. When you do that, adherence goes up, retention improves, patients stay in care longer and show up more consistently. Not because you reduced friction but because you deepened connection. If your patients aren't engaging, take a step back from workflows and examine how your technology supports relationships. As sexy as your platform might be, it’s meaningful connections with providers that keep patients coming back. Design accordingly.

Empathy-powered. Digitally enabled. Patient connected In today’s fast-evolving healthcare landscape, connected care isn’t just about tech—it’s about enhancing human connection at every touchpoint. Key insights from Deloitte ’s 2025 Global Health Care Executive Outlook show how we can harmonize digital transformation with the human-centric care our patients deserve: 1. Prioritize integrated digital platforms • ~70% of global C‑suite leaders are investing in digital tools and services to enable seamless patient journeys . • This connectivity supports continuous care—whether in-hospital, remote, or at home. 2. Modernize core systems while keeping the human anchor • 60% are upgrading EMRs and ERP systems . • When clinicians can access integrated data swiftly, they spend less time documenting and more time connecting with patients. 3. Embed empathy into every digital interaction • Cybersecurity (78% prioritize) builds trust—patients feel cared for when their data is protected . • A secure, respectful environment is the foundation for truly human-centered care. 4. Enhance clinician well-being to improve connectedness • 80% of leaders recognize workforce strain; digital tools can reduce burnout and foster deeper patient engagement . • When staff feel supported, they show up both professionally and emotionally. 5. Expand virtual and hybrid care with a personal touch • 65% of consumers find virtual care more convenient —but scaling it successfully means integrating empathy and follow-up. • Reimagining care pathways ensures consistent human connection, whether digital or face-to-face. ⸻ 🎯 Managing connected care with humanity means: • Leveraging interoperable systems that share real-time insights across care teams. • Training clinicians in digital empathy—listening through the screen, addressing emotional cues. • Designing secure, intuitive platforms that empower patients without overwhelming them. • Supporting staff with AI-driven admin relief, enabling them to focus on people. • Creating holistic care pathways that blend telehealth, in-clinic, and home-based services under one cohesive plan. By weaving technology into our care systems thoughtfully, we can create a healthcare experience that’s efficient, personalized, and emotionally resonant. Looking forward to your thoughts: how is your organization balancing connectivity with compassion? Sara Siegel Link to the report: https://lnkd.in/etDPEc3a #connectedcare

Why does the Buurtzorg model work so well? Because it was designed around humans, not bureaucracy. For those unfamiliar, Buurtzorg is a Dutch community nursing model built on small, self-managing teams that deliver holistic care to patients in their homes. There are few managers, minimal protocols, and one clear aim: help people live independently for as long as possible. Most healthcare systems are structured very differently. Care is fragmented into tasks, professionals are managed through layers of control, and success is measured by activity rather than outcomes. The result is familiar: rising costs, burnout, inefficiency, and patient dissatisfaction. Buurtzorg succeeds because it aligns care delivery with three fundamental human drivers. Mastery Nurses are trusted to practice at the top of their training, managing the full care journey rather than isolated tasks. This strengthens clinical judgment, improves quality, and quietly eliminates waste. Sense of purpose The mission is explicit and shared: preserve patient independence. This clarity shifts care from dependency creation toward prevention, education, and coordination. Meaningful work reduces burnout and turnover, strengthening the system from within. Autonomy Decisions are made closest to the patient. Small teams own care planning, scheduling, and outcomes. Autonomy creates ownership. Ownership exposes inefficiency. Efficiency follows without heavy supervision. Why this Healthcare is not short of reforms, tools, or policies. What it lacks is coherent design that respects human motivation and professional judgment. Why now Workforce fatigue, cost escalation, and fragmentation are no longer future risks. They are present constraints. Models that restore trust and effectiveness are no longer “nice to have”. They are necessary. Why me I work at the intersection of clinical care, health systems research, and payment design. Teaching and studying these models has reinforced one lesson: incentives matter, but organisation of work matters more. The deeper lesson from Buurtzorg is simple but uncomfortable. Better healthcare does not begin with more control. It begins with trust. If you are interested in rethinking how we design healthcare, from bedside to system level, connect with me. Let us learn how to improve healthcare, one day at a time.

We solved half the problem & thought we bridged the gap. Ever worked on a solution that looked perfect on paper… but ended up creating more problems than it solved? That’s exactly what happened when I was called in to review a telehealth solution. It was well-designed, checked all the cybersecurity boxes, & allowed patients to consult doctors remotely. The project requirement was clear: enable remote consultations. And the solution delivered exactly that. But here’s the thing: While healthcare systems often operate in silos, patients experience their care as one continuous journey. And this solution missed critical parts of that journey: 🔸 No easy way to book follow-ups. Patients had to call, leading to missed care. 🔸 Medication collection still required hours of travel, making the platform’s convenience meaningless. 🔸 Administrative staff were overloaded, causing delays in care coordination. We solved one problem & unintentionally created three more. The solution was designed for the system’s convenience, not the patient’s journey. To shift the perspective, we expanded the conversation to include voices we hadn’t considered: 🔸 Pharmacists: To integrate medication delivery into the process 🔸 Community Health Workers: To provide local, hands-on support 🔸 Family Caregivers: To highlight logistical & emotional challenges at home 🔸 IT Teams: To automate follow-ups & reduce administrative burden 🔸 Local Transport Providers: To enable last-mile delivery of medications With these insights, we redesigned the solution into a comprehensive care experience: ✅ Patients could book follow-ups easily & get automated reminders ✅ Medications were delivered directly to their homes ✅ Caregivers & community workers ensured patients didn’t fall through the cracks I later learned that: 🔸 Missed follow-ups dropped by 40%. 🔸 Medication adherence & health outcomes improved significantly. The redesigned platform didn’t just connect patients to doctors, it completed the care journey. Next time you’re working on a solution, consider these points: 1️⃣ Patients see one journey While systems operate in silos, patients experience care as a unified process. 2️⃣ Identify all stakeholders Both direct & indirect voices like caregivers, pharmacists & community workers, are essential to closing gaps. 3️⃣ Design for continuity Address every touchpoint in the patient’s journey, ensuring nothing falls through the cracks. Have you worked on solutions where overlooked stakeholders made all the difference? What’s one gap you discovered that changed everything? #DigitalHealth #Innovation #HealthcareTransformation #PatientExperience #Collaboration 💡This post is part of 'Rethinking Digital Health Innovation' (RDHI), empowering professionals to transform digital health beyond IT and AI myths. 💡Find the ongoing series and resources on our companion website (URL in comments). 💡 Repost if this message resonates with you!