Shared Health Records

The cardiologist prescribed a beta-blocker. The endocrinologist had just changed the insulin dose. Neither knew what the other had done.

The data existed. It was in two separate systems, neither of which talked to the other. The patient was managing two chronic conditions across two departments in the same hospital — and their complete picture existed nowhere. Not for the clinicians. Not for the pharmacist. Not even for the patient.

This isn't a technology failure. It's the predictable outcome of building clinical systems that store data in silos and call it done.

❌ Without Shared Health Records

Each system owns its own data. A complete patient view requires logging into 3 systems, exporting CSVs, and manually reconciling conflicting records. Point-to-point integrations multiply with every new system added. When a system is replaced, its data stays behind. Clinicians make decisions with partial information — and they know it.

✅ With Atomik as the shared backbone

All systems push to one openEHR repository. Every authorized clinician queries the same longitudinal record — vitals, diagnoses, medications, labs — in one place. New systems integrate once. Old systems retire without stranding their data. The patient's complete history is always one query away.

A Unified Clinical Data Backbone

Modern healthcare organizations rarely suffer from a lack of data — they suffer from fragmentation. Clinical information is distributed across EHRs, departmental systems, labs, imaging platforms, and patient-generated sources, making it impossible to build a complete, trustworthy view of the patient.

Atomik Server acts as the single source of truth for shared health records — an openEHR‑compliant clinical and demographic repository that aggregates data from any source and makes it queryable by any authorized consumer: clinicians, analytics tools, decision support engines, patient portals.

The usual process for aggregating patient data that resides on different isolated data silos, following the openEHR model, includes the following steps:

  1. Analyze which data should be shared between your systems, start small, focus on the basics: general encounters, vital signs, allergies and other diagnosis, family history, immunizations, etc.
  2. Model that information using openEHR representations as archetypes and templates. Check the openEHR basics guide to understand how openEHR models clinical information. This will serve as a canonical model that will standardize the information coming from different systems.
  3. Transform your data sources into canonical model instances, from designing the data mappings to actually generating valid openEHR data instances. We have tools to help with that process. Also, a middleware like Mirth Connect (Open Integration Engine or BridgeLink flavors that are open source) can help you on the transformation task. Of course, from CaboLabs we can help with this process.
  4. Commit data instances to the Atomik to be persisted as part of each patient's EHR. Repeat until your current data is committed. At this stage this will be a batch process to load historical data from your current data sources, later it can be a real time process that records whatever data is newly generated. Now the data is ready for querying!
  5. Query and access the data from any external system, even from systems that are not part of the data sources! Create some basic queries over your data, like get all the vital signs from an EHR. That can be done easily using the Query Builder from the Web Console. The result of each query will be consistent, openEHR compliant, and ready for processing. You can do things like evaluate rules for clinical decision support that generate alerts and recommendations, data analysis and reporting, or just feed the data into a nice visualization for a user. If you don't want to query, you can get full clinical documents by their id in JSON format.
  6. Integrate this solution into your environment to synchronize data regularly, so you get current data when your systems and apps execute the queries. The first 'loading' phase is the heavy loading, when you are done with that, it's time to receive data in real time instead of from a batch process.

Why Clients Choose This Approach

Interoperability by Design

Using openEHR ensures long‑term semantic interoperability across vendors, regions, and evolving standards.

Vendor Independence

Data is no longer locked inside proprietary schemas — applications can be replaced without migrating clinical history.

Faster Innovation

New clinical use cases can be delivered by defining templates instead of redesigning databases.

Clinical and Demographic Data Together

Atomik Server manages patient identity and clinical content in a single, coherent model.

Compliance and Traceability

Full audit trails and version history support regulatory and medico‑legal requirements.

Integration Architecture

graph TB subgraph Sources direction TB EHR[EHR Systems] LIS[Labs and Imaging] DEV[Devices and Wearables] EXT[External Systems] end subgraph Integration ETL[ETL or Middleware] MAP[openEHR Models] end subgraph Atomik CDR[Clinical Data Repository openEHR] DDR[Demographic Repository] AUD[Versioning and Audit Trail] end subgraph Consumers direction TB CLIN[Clinical Applications] BI[Analytics and Population Health] CDS[Clinical Decision Support] PORT[Patient Portals] APP[Patient Apps] end Sources --> Integration ETL --> MAP Integration --> CDR Integration --> DDR Atomik --> Consumers

Open a world of possibilities

With a Shared Health Records solution you don't just load data into another database, you standardized and integrated data from heterogeneous, and maybe inconsistent / incompatible clinical systems, into a single standardized, vendor-neutral, Clinical Data Repository.

Sharing clinical data between systems is the foundation. Once it's in place, every new use case — an alert dashboard, a patient portal, a population health report, a CDS rule — is an API query away, not another integration project. Each new application draws from the same standardized store without rebuilding the data layer.

The platform also scales incrementally: start with the highest-value data (encounters, vitals, allergies), validate the integration, then extend the canonical model to include more clinical domains as your team is ready. Every expansion adds capabilities across all consuming applications simultaneously.

mindmap root((Shared Health Records)) Clinical Care Longitudinal Patient View Care Coordination Decision Support Analytics Population Health Quality Metrics Research Digital Health Patient Portals Mobile Applications Remote Monitoring Platform Benefits Vendor Independence openEHR Interoperability Audit and Compliance
Capability Map

In Summary

Atomik Server enables healthcare organizations to build shared health records that are interoperable, scalable, and reusable over time. By acting as a central openEHR‑compliant data backbone, it unlocks new clinical, analytical, and digital health capabilities — without locking you into a single vendor or application.

One patient. One record. Many possibilities.