Originating from the healthcare sector, Medscio combines healthcare expertise with smart AI technology to make healthcare data meaningful, reusable, and interchangeable: the foundation for future-proof healthcare.
Hospitals & Laboratories
Standardized results
Faster standardization with AI
Accurate Clinically validated
User-friendly Intuitive and transparent
Efficient, smart and reliable standardization. AI recognizes local terms and metadata, and links them to international standards such as SNOMED-CT, LOINC and UCUM. Local clinical experts easily validate and ensure medical accuracy. This results in meaningful healthcare data in one universal language for every system and every application.
Healthcare data and standards are constantly evolving: new parameters, outdated codes, and adjusted terms. AI automatically signals these changes and prepares relevant updates. Local clinical experts determine which updates to implement.
Ready for multi-purpose reuse of healthcare data. Standardized terms and codes are fed back into local systems, making them exchangeable via HL7 FHIR. This enables reliable data exchange between systems and institutions: for integrated care, quality improvement, and innovation.
Standardizing critical healthcare data is a meticulous task. The responsible use of AI, combining smart technology with human domain expertise, makes this process more efficient and delivers reliable results.
Healthcare generates large volumes of data, yet only a fraction is truly usable for improved care, decision-making, and innovation. Why? Data is fragmented across systems, varies in structure and meaning, and lacks the context needed for reliable reuse.
The consequences are substantial:
The solution is semantic interoperability: a ‘unity of language’ where data retains the same meaning and context across every system and provider. Only then can healthcare data become truly reliable, reusable, and safely exchangeable: the foundation for healthcare data that finally works
“If you organize it properly from the start and code it truly correctly once, it doesn’t matter if it’s used for primary or secondary purposes. That foundation can then be reused for multiple use cases. Really, we should just say: we need to make this happen.”
Dr. Ruben Smeets
Chair of the AICT committee (Automation, Information and Communication Technology) NVKC and clinical chemist Radboudumc
“I’ve achieved more in two hours using the app than in the past two years.”
Arnoud Loof,
ICT coordinator / project manager Radboudumc
“Manual standardization is far too error-prone; it takes an enormous amount of time and you easily miss essential test properties. The AI application largely eliminates that risk.”
Dr. Maurits de Rotte
Clinical chemist Amsterdam UMC
“The only way to truly achieve national data standardization is through central coordination. Medscio is a strong medical-technical partner that fulfills this role in an enthusiastic and motivating way. Without Medscio’s central role and technology, we get stuck and data exchange remains too fragmented. What makes Medscio’s team special is that they get everyone on board and truly recognize and leverage the power of domain experts – not only in the lab, but also from healthcare and IT. That’s why Medscio stands where they are today, and you see the desired acceleration in practice.”
Dr. Judith Gillis,
Chair of the NVKC Editorial Board and clinical chemist at Amsterdam UMC
From healthcare, for healthcare.
Medscio was born from practical experience. During the first COVID wave, two physicians struggled firsthand with fragmented, difficult-to-exchange data. That experience formed the foundation of our mission: making healthcare data meaningful, reusable, and safely exchangeable so it actually improves care.
Today, Medscio has grown into a multidisciplinary team of clinicians, data scientists, interoperability experts, engineers, and designers. What unites us is a deep commitment to healthcare and the belief that technology only has value when it advances healthcare in practice.
We combine clinical knowledge with technical expertise. Through AI-powered standardization processes leveraging Large Language Models, we make healthcare data reliable, reusable, and safely exchangeable. Our approach integrates with existing systems and workflows, enabling healthcare professionals to use the results immediately, without added administrative burden.
Our goal is clear: to improve and connect healthcare data for a future-proof healthcare system.
Semantic interoperability means healthcare information retains the same meaning everywhere, regardless of the system, provider, or organization. We achieve this through a shared agreement on language, codes, and definitions: a “unity of language” in healthcare.
With semantic interoperability, different systems, hospitals, and providers can correctly exchange, understand, and reuse healthcare data, ensuring everyone interprets information the same way.
Why it matters:
The bottom line: Semantic interoperability makes healthcare data unambiguous, reliable, and usable wherever it’s needed
Healthcare Provider: You get the right information on your screen faster, without the endless searching or correcting. This saves time and prevents errors. You can make better-informed decisions and spend more time with your patient instead of managing data.
Hospital: Standardized data means reliable registrations, simple exchange, and lower management costs. Innovations like AI and clinical decision support can finally scale. The hospital anticipates WEGIZ/EHDS legislation requirements and builds a future-proof digital infrastructure.
Patient: As a patient, you benefit from faster diagnoses, safer care, and more control. Your data is available and understandable the same way everywhere, whether you visit another hospital or seek a second opinion. This increases trust and leads to better care outcomes.
Society: Through unambiguous healthcare data, we make care safer, more efficient, and affordable. Less duplicate testing, lower administrative burden, and better policy decisions ensure scarce resources are allocated to patient care. This strengthens our healthcare system, now and in the future.
Metadata is essential for correctly interpreting certain data. Without standardization (and sharing) of metadata, important meaning gets lost.
Thanks to AI suggestions and an intuitive interface, the work shifts from research and lookup to simple review. What previously took weeks of manual work now takes minutes to hours, while keeping validation transparent and traceable
We automatically monitor updates to both terminologies and local data. Relevant changes are presented to local clinical experts for review. Once approved, changes are processed immediately, keeping standardized data up to date and HL7 FHIR-ready.
Yes. Our solution is directly applicable for exchange in HL7 FHIR format, making integration into existing systems and registrations easy.
Yes. Standardized datasets make analyses reproducible, comparable across organizations, and suitable for quality registries such as NICE.
A “close match” creates downstream errors and correction costs. We aim for 100% accuracy and standardization at the most granular level. When codes are missing, we request them directly from organizations that maintain standards. This ensures consistently high quality.
Only partially. By the time data reaches the EHR, information may already be lost or transformed. Accurate standardization requires starting at the source: laboratory information systems (LIS), measurement instruments, and other primary data systems.
For laboratory data, that’s the clinical chemist; for culture results, the medical microbiologist. AI handles the heavy lifting, but professionals who understand the clinical context validate the results. All changes are fully traceable and transparent.
LOINC for tests and observations, SNOMED-CT for medical terms and context, UCUM for units, openEHR for data modeling, HL7 FHIR for exchange, and more. We always use the most up-to-date standards that align with international developments.
Privacy-by-design is built into our system. We only process the minimum data required for standardization, and all processing is fully GDPR-compliant.
When no suitable LOINC or SNOMED-CT code exists, you can submit a formal code request directly through our platform. We provide a pre-filled form with all relevant information already included: no complex procedures or manual searching required. Your dataset stays accurate and complete.
CLINICAL CHEMISTRY:
Laboratory tests and results are uniformly coded, including their metadata. This way, they remain interpretable in a reliable way and can be securely exchanged, both within and between healthcare institutions.
Standards include:
CLINICAL MICROBIOLOGY:
Both microbiological tests and results (such as serology and culture results) are uniformly coded, including associated metadata. This way they remain reliably interpretable and can be securely exchanged, both within and between healthcare institutions.
Standards include:
PROCEDURES:
Procedures and treatments are uniformly coded with SNOMED CT, the Procedures Thesaurus, and LOINC. This way, they are unambiguously recorded and securely shared between systems and departments. This makes documentation, handover, and reporting simpler and more consistent, with data that is accurate and understood.
Standards include:
QUALITY REGISTRIES:
Medscio helps clinical registries and hospitals to standardize quality registries and align them with international terminologies such as SNOMED CT and LOINC. AI supports the standardization of local data fields to these standards, after which domain experts validate the content. The result: unambiguous, traceable datasets that are directly usable, with less administration, and more reuse of existing data.
Standards include:
MEDICATION:
Medication data is recorded unambiguously, from drug names to dosage and route of administration. AI supports the standardization of local medication lists to international standards, after which pharmacists and clinical experts review and confirm the results. This creates reliable medication data that simplifies handover, prevents errors, and supports safe prescribing and administration.
Standards include:
SMART PROBLEM LIST (DIAGNOSES):
AI supports healthcare providers with intelligent recognition and coding of medical problems. Relevant conditions and medical history are automatically extracted from (referral) letters and presented as SNOMED-CT codes (including the Diagnosis and Procedures Thesaurus). Healthcare providers review the suggestions in a single, intuitive screen: fast, transparent, and fully in control.
The result:
This transforms the problem list from a registration task into a valuable care instrument: reliable, up-to-date, and clinically validated.
Standards include:
VITAL SIGNS:
Parameters such as blood pressure, heart rate, and oxygen saturation are unambiguously standardized to international terminologies. AI connects local measurement names and units to LOINC and UCUM, and enriches the data with clinical context through SNOMED-CT. This enables reliable tracking of trends over time and across departments, from daily monitoring to research and quality registries.
Standards include:
openEHR:
openEHR and HL7 FHIR together form the backbone for trustworthy health data reuse and exchange. openEHR describes how medical information is durably stored in a semantically meaningful way. FHIR determines how health data is securely and uniformly exchanged between systems. Combining both makes data unambiguous, traceable and future-proof: independent of applications, and usable everywhere.
Applications include:
