Unified Health Information Systems

One platform. One login. One data model. When we first set out to build the Ennov platform, we had a choice. We could follow the common path—create separate systems for Quality, Regulatory, Clinical, and so on, connected by integrations. Many vendors do it this way. On paper, it looks flexible. But in practice, it creates complexity. I’ve seen it firsthand: Teams working in silos Duplicated product data Disconnected processes And the biggest frustration of all—multiple sources of truth. Each system had its own interface, its own repository, and its own logic. Collaboration became a challenge, and regulatory and quality teams were left working in parallel, not together. We decided to take a different approach. We built a TRUE unified platform—a single system where Quality, Regulatory, Clinical, and other business units share the same data, the same workflows, and the same user experience. Why? Because organizations need agility. They need one place where a change in labelling can automatically trigger a regulatory variation, or where product data updates are reflected everywhere—not maintained in different silos. They need one source of truth they can trust. And they need systems that don’t slow them down when they’re trying to protect patient safety or expand into new markets. That's why Ennov is different. One platform. One login. One data model. And a lot less complexity. Hearing from our customers, this has definitely been the right choice. #TrueUnifiedPlatform #LifeSciences #Ennov

We’re experimenting with OMOP as a foundation for more flexible data sharing and AI-readiness in healthcare. Healthcare data doesn’t come in one flavor. Some apps get FHIR, others see HL7v2 or CCDA. Hospitals often store even more data that doesn’t fit neatly into any of those buckets. OMOP may offer a practical foundation for modern health data sharing and a powerful complement to FHIR. We’re testing OMOP as the internal storage layer for all incoming formats. We’re converting HL7 v2, CCDA, and FHIR into a unified OMOP structure. Then, when an app needs access to that data, we can serve it back out through FHIR APIs. That’s the bridge: OMOP for internal consistency and analytical power. FHIR for interoperability and app access. 🧠 Why does this matter for AI? Training AI models requires context-rich, normalized data. OMOP helps with longitudinal queries and makes use of standardized vocabularies from OHDSI to reduce ambiguity. 📊 And when you’re ready to analyze or train? OMOP’s structure is designed for analytics, with built-in schemas for patient-level prediction, comparative effectiveness, and cohort-based research. 📌 The diagram below shows how we’re thinking about this: standardize incoming data (FHIR, HL7v2, CCDA) into OMOP, then expose it back out via FHIR for apps and integrations. This approach supports everything from AI model development to real-time reporting. OMOP gave us a pretty good foundation, but we still had to extend it in areas and add custom tables to support all the data we need. 🔗 Learn more about OMOP and the OHDSI community: https://lnkd.in/gKSzQN2i #DigitalHealth #HealthData #FHIR #OMOP #OHDSI #Interoperability #HL7 #HL7v2 #CCDA #AIinHealthcare #HealthIT #HealthcareAI #EHR #CommonDataModel #DataStandardization #SmartOnFHIR

80% of Healthcare Data Is Trapped in Silos. Here’s How to Unlock It. Did you know that 80% of healthcare data—clinical notes, imaging reports, patient histories—is unstructured, buried in formats like PDFs or free-text entries? This fragmentation delays diagnoses, increases costs, and risks patient safety. [Source: NCBI] But there’s hope. Below are 7 actionable strategies to break down data silos and build a truly connected healthcare ecosystem:    1. FHIR-First Approach for EHR Integration  Why it matters: FHIR (Fast Healthcare Interoperability Resources) standardizes data exchange across systems.  Do this: Use FHIR APIs to connect hospitals, labs, and telehealth platforms.  Impact: Cleveland Clinic reduced duplicate testing by 30% post-FHIR adoption. 2. AI-Powered Data Unification  Why it matters: AI and NLP can map unstructured data (e.g., clinician notes) to structured formats.  Do this: Deploy tools like Google’s Care Studio to reconcile mismatched records.  Impact: AI-driven systems at Mayo Clinic cut patient matching errors by 40%. 3. Zero-Trust Security Architecture  Why it matters: 95% of healthcare breaches start with human error.  Do this: Combine RBAC, MFA, and end-to-end encryption.  Impact: Kaiser Permanente reduced breaches by 60% with zero-trust frameworks. 4. Blockchain-Backed HIEs  Why it matters: Centralized HIEs are vulnerable to tampering.  Do this: Build decentralized Health Information Exchanges with blockchain audit trails.  Impact: Estonia’s blockchain HIE ensures 100% data integrity across 1,000+ clinics. 5. IoMT & Wearable Integration  Why it matters: Remote devices generate 50% of healthcare data by 2025 (Deloitte).  Do this: Use edge computing to process wearable data locally before syncing to EHRs.  Impact: Johns Hopkins reduced ER visits by 25% via real-time remote monitoring. 6. Automated Compliance Engines  Why it matters: Manual compliance checks delay interoperability by weeks.  Do this: Deploy tools like Redox to auto-validate HIPAA/GDPR compliance.  Impact: Intermountain Healthcare accelerated integrations by 70%. 7. Patient-Led Data Ownership  Why it matters: 78% of patients want direct access to their records (ONC).  Do this: Build apps with granular consent controls (e.g., Apple HealthKit).  Impact: NHS England saw a 35% rise in patient engagement with shared records.    The Bottom Line:  Unstructured data isn’t just a tech problem—it’s a patient safety crisis. By adopting these strategies, we can turn fragmented data into actionable insights, reduce costs, and save lives.    Let’s stop talking about interoperability and start building it.   Repost if you believe connected healthcare is non-negotiable.  Comment with the #1 barrier your organization faces in achieving interoperability.    #HealthcareIT #DigitalHealth #Interoperability #FHIR #AIinHealthcare #PatientSafety #HealthTech

In my travels around the world, I get to see many norms and rules aimed at harnessing the power of data and digital technologies, but none of them match the ambition, complexity and promises of the European Health Data Space (EHDS). Last week, I took part in a panel discussion on "EHDS: Unlocking Europe's Health Data Future Together", and I was reminded that the EHDS is not just another European regulation, but it is the perfect illustration of a European project in motion: a data sharing project to transform patient care, drive innovation, and boost Europe’s competitiveness. Are we ready to turn this vision into reality? Here are three key points for successful EHDS implementation: 1️⃣ A Unified System Across the EU: For the EHDS to succeed, it must be consistently applied across all member states. A unified approach will streamline healthcare systems, foster innovation, and enhance patient care throughout Europe. 2️⃣ Boosting Innovation: The EHDS unlocks valuable health data for innovation. Clear guidelines around intellectual property and data protection will support both large and small innovators, giving Europe a competitive edge, particularly in AI-driven healthcare advancements. 3️⃣ Effective Implementation: Successful EHDS implementation requires time, investment, and commitment. National healthcare systems need to be prepared for large-scale data exchanges, and collaboration through the EHDS Stakeholder Forum will be crucial for a smooth transition. There is no other health data space like this one in the world. Let’s work together to ensure it delivers on its promises for a healthier and more innovative Europe. Watch the replay here: https://lnkd.in/eiQYrHgd DIGITALEUROPE #EHDS #HealthcareInnovation #HealthData #Europe #PatientCare #DigitalHealthEU #EU #HealthUnion

In the evolving landscape of healthcare, New Zealand has been on a journey of transformation driven by the integration of healthcare information systems and the efficient exchange of health data. The vision for the future involves creating a seamless, interoperable, and patient-centric health information ecosystem. The NZ healthcare sector has long recognised the need for improved information exchange. Studies reveal that a considerable gap exists between the available information and the evidence needed to support informed care decisions. This 'inference gap' hampers effective patient care and decision-making processes. While there is strong support among clinicians for better electronic access to healthcare information, challenges such as incompatible systems and funding limitations persist. Significant steps have been taken towards achieving full interoperability across NZ's digital health ecosystem. The Health Information Standards Organisation (HISO) has released announced that they are working on an Interoperability Roadmap, guiding the sector towards the adoption of the New Zealand Core Data for Interoperability (NZCDI) standards. These standards, adapted from international models, will aim to facilitate the exchange of core personal health information in clinical workflows and enhance consumer access to health data. The now paused Hira programme is another cornerstone initiative aimed at transforming health data accessibility. The rollout of My Health Record, which replaced the My Covid Record, enables citizens to access a broader range of health information, including National Health Index details, vaccination records, and more. The adoption of FHIR is pivotal in modernising NZ's healthcare information exchange. FHIR provides an open-source standard for healthcare data exchange, promoting seamless data sharing across disparate health systems. Looking ahead, the focus will be on refining and expanding these initiatives to cover more aspects of healthcare delivery. The integration of various data sources, including hospital electronic medical records, general practice systems, and consumer-held data from wearables, will create a holistic view of patient health. This integrated approach will not only support clinical decision-making but also enable proactive healthcare management and personalised care. Moreover, the continued development of technical standards and frameworks will be crucial. Health NZ's efforts in establishing API standards are steps aiming to streamline data sharing processes and enhance the overall quality of healthcare services. By leveraging technologies and fostering a collaborative approach among stakeholders, we can achieve a fully integrated health information system. This will not only improve patient outcomes but also create a more efficient and effective healthcare system that is responsive to the needs of all New Zealanders. Aceso Health Digital Health Association (DHA) Samantha Ford

Finally, it's here! Regulation (EU) 2025/327 on the European Health Data Space (EHDS) is officially out. Here are 7 key points that professionals in the MedTech industry, especially those developing medical device software and working with electronic health records (EHR), must know: 1) Individuals will gain immediate, free electronic access to their own health data, significantly enhancing patient control across the EU. 2) The Regulation mandates a standardized European electronic health record exchange format, promoting seamless interoperability between healthcare systems. 3) Healthcare providers must implement interoperable EHR systems, which will require self-certification against stringent interoperability, security, and data logging standards. 4) Patients have the right to opt-out from sharing their health data for secondary purposes, but Member States retain authority to override this in critical public interest scenarios, such as serious cross-border health threats or urgent scientific research. 5) Transparency is central: Patients will see detailed records of who accessed their health data, the timing, and the purpose, fostering essential trust. 6) Wellness apps that claim interoperability with EHR systems must be clearly labeled, enhancing reliability and user confidence in digital health technologies. 7) Overall, this regulation sets a transformative benchmark, aiming to significantly enhance data accessibility, patient empowerment, and healthcare innovation, while ensuring stringent protection of personal health data. What impact will this have on your work or your organization? ✌️ Peace, Hatem Clinical Evaluation Expert for Medical Devices Follow me for more insights and practical advice. #EHR #HealthData #EHDS #Clinicalevaluation

Clinicians need comprehensive patient information to deliver higher-quality care. But how can you unify data from multiple stakeholders?     For answers, look to Dr. Denise Hines, DHA, PMP, FHIMSS, executive director of the Georgia Health Information Network (GaHIN), the state’s nonprofit health information exchange.    Dr. Hines is that rare leader who connects the dots in healthcare. Her deep experience in health systems, physician offices, technology vendors, and state government has prepared her to transform healthcare in Georgia.    How?    She’s advancing healthcare connectivity by expanding the HIE’s focus beyond traditional provider data. Leveraging InterSystems HealthShare, the exchange links to state agency information, historical lab results, telehealth data, and social determinants of health data.    A clinician can consult a patient’s admission, discharge, and transfer history alongside their housing data — all in an effort to treat patients in a more holistic way that addresses their full spectrum of needs.    This is exactly the kind of use case that makes our work worthwhile. It shows how patients thrive when you combine interoperable data with advanced technology and an innovative mission to serve patients and communities. Thank you, Dr. Hines.    Where else have you seen interoperability make a difference, not just in healthcare, but where society as a whole benefitted?    #Healthcare #Interoperability #HEI

🧬 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

The Single Patient Record is finally moving from concept to evidence, and NHS England has kicked off the Test and Learn phase. Three technical proofs of concept are being tested in the Test and Learn phase: 1. A Hub & Spoke model to link regional records via shared APIs 2. A Central Integration Model for real-time national access 3. A Virtual Data Layer that joins data on demand, not by duplication Each approach asks the same question 👉 Can we join up care safely, securely, and simply - without starting from scratch? For years, we’ve talked about interoperability like it’s a technology problem. It isn't. It’s a design and delivery challenge - and this phase is a chance to test what "good" really looks like at system scale. The interesting part is the approach is open, collaborative, and grounded in reality - discovery with frontline users, not just design in meeting rooms. If it works, it could redefine how health data flows across the NHS. Not a single system. A single understanding of the patient. Finally.

Part of Inter-American Development Bank's digital health case study series, the team has recently made the Implementation Process for the Unified Electronic Medical Record (UEMR) in Bogotá, 🇨🇴 case available in English. 🛣️ Quite an insightful journey: kudos to the team for making it available for the non-Spanish speaking audience - Fernando A. Portilla V. Luis Tejerina! Bogotá, with its 8 million residents, is a major healthcare hub in Colombia. The UEMR project and its key learnings have significantly influenced country's interoperability strategy, reflected in the Agenda de Transformación Digital e Interoperabilidad 2022-2031. This effort positions Colombia as a one of leading examples of healthcare digital transformation in Latin America. 💡Interestingly, the project, which kicked off in 2016 with a strong reliance on IHE XDS architecture and HL7 CDA, has gradually evolved to embrace FHIR. This shift made the UEMR to operate in a more flexible by also more complex, blended exchange mode. Any lessoned learned you could share Fernando? 🗒️ This is something to consider for us in 🇪🇺 as we navigate the gradual implementation of the EHDS's MyHealth@EU infrastructure, particularly as we plan for a longer transition period from CDA to FHIR. Ander Elustondo-Jauregui Alexander Berler Prof. Georgi Chaltikyan, MD, PhD Miguel Coelho Benedikt Aichinger Konstantin Hyppönen