💡 What Happens After a Patient Visit? The Power of HIE & EMR Working Together Most people think the patient visit ends when they walk out of the exam room — but in healthcare data, that’s where the real work begins. After a visit, the Electronic Medical Record (EMR) finalizes documentation, updates clinical summaries, and syncs everything across systems. From there, the Health Information Exchange (HIE) securely transmits that data to other authorized providers, payers, and public health agencies to support continuity of care. Here’s what a typical post-visit flow looks like: ✅ Provider finalizes clinical documentation and codes ✅ Visit summary shared to patient portal ✅ Structured FHIR/HL7 data sent to the HIE ✅ Labs, imaging, and referrals routed to connected organizations ✅ Claims processed and quality metrics updated ✅ AI insights and analytics trigger follow-ups and care gap alerts This workflow ensures that every clinician, specialist, and patient stays on the same page — improving outcomes, speeding up billing, and reducing errors.
How HIE and EMR Work Together After a Patient Visit
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🚀 Correlate Health Launches AI Platform to Revolutionize Clinical Trial Recruitment and Diversity Analytics Body: We’re thrilled to announce the official expansion of LooPT CTM, Correlate Health’s AI-powered platform that’s transforming how healthcare organizations find, match, and enroll patients in clinical trials. 🔹 AI + FHIR interoperability means faster, smarter recruitment. 🔹 FDORA-ready diversity analytics make trials more equitable. 🔹 HIPAA-compliant automation reduces administrative burden. “AI automation should make healthcare more inclusive, not more complicated,” says Dr. Nailah Malak, our CEO & CTO. Correlate Health also invites professionals to join the Digital Health Implementation Mastery program — an 8-week certification beginning Feb 17, 2025, covering FHIR, AI, HIPAA, and Agile in healthcare. 👉 Learn more at correlatehealth.com #AIinHealthcare #ClinicalTrials #HealthTech #FDORA #FHIR #EHR #DigitalHealth #Automation #HealthcareInnovation #CorrelateHealth
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Meet Clinical—a modular AI agent system built to automate patient onboarding, diagnostics, billing, and compliance for healthcare providers. Designed for clinics, hospitals, and primary care visits platforms, Clinical streamlines operations while enhancing care precision. From intake to audit trails, it’s the future of healthcare—secure and scalable.
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🚀 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝗷𝘂𝘀𝘁 𝗴𝗼𝘁 𝘀𝗺𝗮𝗿𝘁𝗲𝗿. Our latest case study shows how a multi-facility healthcare provider improved clinical decision accuracy by 78% and reduced diagnostic time by 65% with EHR–CDS integration on Athena. 𝗧𝗵𝗲 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲? Fragmented data, manual processes, and a lack of real-time decision support were slowing providers down and increasing the risk of errors. 𝗧𝗵𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻? 𝗔 𝗰𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗯𝗿𝗶𝗱𝗴𝗲 𝘁𝗵𝗮𝘁: ✅ Unified EMR systems with Athena EHR ✅ Delivered real-time medication interaction checks & safety alerts ✅ Integrated evidence-based guidelines directly into clinical workflows ✅ Streamlined diagnostics with lab result analysis & interpretation tools The impact speaks volumes: 𝟳𝟮% 𝗳𝗲𝘄𝗲𝗿 𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗲𝗿𝗿𝗼𝗿𝘀, 𝗳𝗮𝘀𝘁𝗲𝗿 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀, 𝗮𝗻𝗱 𝘀𝗮𝗳𝗲𝗿 𝗽𝗮𝘁𝗶𝗲𝗻𝘁 𝗰𝗮𝗿𝗲. 📖 Read the full case study to see how seamless CDS integration is transforming healthcare operations: https://lnkd.in/dDNRrAh9 #HealthcareInnovation #EHRIntegration #ClinicalDecisionSupport #DigitalHealth
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Every day, millions of data points move between EHRs, labs, and registries — all in the name of keeping patient care connected. That’s the power of interoperability. When systems “speak the same language,” providers can see the full picture — not just a single visit. It means fewer duplicate tests, faster decision-making, smoother care transitions, and better outcomes. Standards like HL7 and FHIR make that possible, bridging the gaps between different technologies and vendors. Whether it’s an ADT admission, a scheduling SIU, or a vaccination VXU, each message plays a part in that data ecosystem. Interoperability isn’t just a tech term — it’s the foundation for patient-centered care. And as the industry continues to modernize, those who understand how data moves will be the ones driving the next wave of healthcare innovation. Love to hear more in the comments! How is your organization improving interoperability this year?
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How to make EHR work for Doctors and not against them - My Reflections Zia S. Hasan has posted her above nicely written article on LinkedIn https://lnkd.in/dPuBKk_A I am sharing my reflections based on my professional roles as a senior doctor, hospital administator, healthcare management and digital health & AI in Medicine exposures The Coordination of Care which was meant to improve clinical quality & outcomes is one of the prime goals for EHR adoption in clinical practice. Borrowing from the AI big data 5 V's principles; Volume, Variety, Velocity, Veracity & Value. High computing power is required to process this data. However, the volume, velocity, and multi-modal nature of health data along with CDSS +/- AI alerts have overwhelmed Clinicians to process patient data coolly. Earlier, the Clinicians used to have time to reflect on the patient's data and then take an informed decision. Now, the Clinicians have to react as if he is an Agentic AI agent. A clinical data scientist must be involved in getting a focused summarisation template, employing the principles of Agentic AI. This will reduce data processing overload, and at the same time clinicians will not miss the most relevant clinical data inputs. This, in turn will reduce clinician's fatigue and burn outs & improve clinical decision making Appreciate that the treating clinician is a human and not a computing machine. See how, the technology and intelligent data processing principles of ETL - Enter, Transform & Load can be used to help the clinician stay responsible & relevant in clinical practice
Healthcare Quality & Operations Strategist | Bridging the US and GCC Healthcare systems | Chronic Disease Management Expert | Microbiologist | Award Winning Entrepreneurship Coach
Every innovation in healthcare sounds exciting until you realize it adds another layer of pressure on the physician. Doctors should diagnose, not document. Doctors should see patients, not pages. When EHR interoperability was introduced, the vision was clear: a unified, up-to-date patient record accessible to every provider involved in a patient’s care. In theory, it means seamless communication and better outcomes. But here’s what I’ve observed in real world practice: the volume and fragmentation of incoming data make it nearly impossible for physicians to keep up. Every day, dozens of reports flow in from specialists, labs, and pharmacies, each one valuable, but together, overwhelming. Technology keeps evolving, but so does the complexity of managing it. Even the strongest system falters when the load falls entirely on the physician’s shoulders. That's why I always say that healthcare is and always will be A TEAM EFFORT! There are two ways to make it workable: ✅ Assign a Care Coordinator or Clinical Documentation Specialist to review incoming faxes/reports daily, and place them in the right folders in the patients' charts. Additionally, they should oversee the coordination of the care process, ensuring timely communication, follow-up, and information sharing among all providers involved in the patient’s care. ✅ Leverage AI-driven summarization tools within EHRs to auto-summarize reports and create an updated dashboard in every new encounter or SOAP note. Innovation should lighten the load, not increase it. Right? #Healthcare #innovation
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🌟 Transforming Healthcare Communication with Clardoc 🌟 At Clardoc, we recognize that the nuances of physician-patient conversations hold immense value in delivering precise medical care. That's why we've developed a groundbreaking solution that converts these vital discussions into standardized medical records effortlessly. Our technology encompasses a series of highly coordinated technical modules to ensure the highest accuracy and relevancy in healthcare data. Here’s how we do it: 🔍 1. Medical Entity Recognition - Symptom Recognition: Our system extracts crucial entities linked to physical discomfort, pain, and related symptoms. - Time Entities: Temporal information such as onset times and symptom durations are identified with precision. - Medication Information: We meticulously capture details regarding drug names, dosages, and usage frequencies as mentioned by patients. - Test Results: Previous test items and their outcomes are accurately identified to provide comprehensive insights. 📊 2. Semantic Understanding and Structuring - Relationship Extraction: We establish logical connections between symptoms, their timings, and severity to allow for a clearer understanding of patient conditions. - Causal Inference: Our analytics delve into causal relationships and the progression of symptoms, ensuring a holistic view of patient health. - Standardization Mapping: We convert colloquial descriptions into standardized medical terminology, adhering to recognized classifications like ICD-10 and SNOMED CT. 📄 3. EHR Template Adaptation - Template Selection: We choose the most suitable EHR templates tailored to specific departments and diseases. - Information Categorization: Our structured data is meticulously classified into categories, including chief complaint, present illness, and past medical history. - Format Conversion: Finally, we organize and present information to meet the formatting requirements of the selected templates. With Clardoc, we’re not just streamlining medical documentation; we’re paving the way for a more efficient, data-driven approach to healthcare that ultimately enhances patient outcomes. Together, let’s elevate the standard of care! #Healthcare #MedicalTechnology #EHR #ClarDoc #Innovation #PatientCare #DigitalHealth
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Healthcare administration consumes hundreds of billions annually with no clinical value. I've spent months tracking where that money goes and how AI is reclaiming it. Real implementations in hospitals, physician groups, and payers. My new course: AI and Healthcare Utilization. - See where $200-360 billion in annual savings comes from. - Hospitals optimizing ORs and predicting deterioration. - Physician groups managing value-based populations. - Payers automating prior auth and detecting fraud. Real use cases with ROI data. Built for clinicians, administrators, and leaders who want clarity over noise. Practical, systems-focused, immediately applicable. Launches THIS SUNDAY! Pre-enrollment $149 (regular $199). Closes November 8. Like my last course, How Healthcare Really Works: high-yield, evidence-based, useful. 🎓 Enroll here: [https://lnkd.in/e8m3vMDc]
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FHIR adoption is easy on paper, but embedding it into daily workflows is where the magic happens. Most healthcare organizations today say they’re “FHIR-ready.” But being FHIR-ready isn’t the same as being workflow-ready. Let’s look at what it means when FHIR actually runs inside a clinician’s day, not just in an API sandbox. Example Use-Case: A patient’s vitals and lab results are updated in the EHR. → The FHIR API streams this data in real time. → An AI engine calculates risk of deterioration or flags medication interactions. → A CDS (Clinical Decision Support) pop-up appears in-workflow, not in another app. → The clinician acts within the EHR- saving time, reducing clicks, improving safety. Key Enablers - FHIR Subscriptions for real-time event triggers - CDS Hooks / SMART on FHIR for in-EHR insights - AI engine consuming FHIR bundles (JSON → analytics → recommendation) - Unified logging + provenance for audit & compliance FHIR isn’t just a data bridge. When tied to AI workflows and surfaced contextually inside the EHR, it turns interoperability into intelligence. At Nirmitee.io, we build these FHIR-native, AI-driven workflows that fit seamlessly inside Epic, Cerner, and Athena EHRs, turning standards into smarter care. #FHIR #Interoperability #HealthcareAI #EHRIntegration #ClinicalDecisionSupport #ONC #HealthIT #DigitalHealth #FHIRAPI #SMARTonFHIR #HealthcareInnovation
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Data is the new currency in healthcare. Data has become the currency of healthcare. But not all data carries the same value. Labs, claims, and EMR entries tell part of the story. Patient-reported outcomes (PROMs) tell the rest — how patients actually feel, function, and heal. That’s the kind of data payers reward, providers can act on, and researchers desperately need. At OutcomeMD, we believe the future of healthcare belongs to those who harness patient voices at scale. 👉 What’s one decision you wish you had better patient data to support?
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