Define the connection
Review existing products and systems, then define the fields, direction of exchange, and update timing.
Connect hospital and patient data.
Give AI the context to understand it.
From partner products and hospital systems to records collected by patients.
Bring information together, organize it, and connect hospital-specific terminology and relationships to support analysis and real workflows.
Integration APIs
Your products and hospital systems.
One connected workflow.
Review hospital interfaces and data formats to design the required exchanges. Start by identifying where partner services and devices meet hospital and patient records, and which workflows those connections should support.
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Design the exchange
Assess APIs, files, and documents, and design field mapping and checks for missing data or errors.
Connect it with work
Shape the flow around actual usage, from staff review to delivery into the next system.
Data structuring
Go beyond collection.
Make records ready to compare and analyze.
Organize items, units, dates, sources, and relationships into a form AI can use. Preserve the clinical context needed to understand whose record it is and how it connects with previous results.
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Organize scattered data
Break records from different systems into the fields needed, review their formats and units, and reassemble them using shared definitions.
Store data with its relationships
Store organized fields in a database alongside their patient, encounter date, and source. Connect related records so relevant information can be retrieved together.
Support multiple uses
Provide connected data in the forms needed for AI analysis, partner products, and hospital workflows. Design ways to combine information for different services and tasks.
Ontology
Your hospital’s language and relationships.
Knowledge AI can work with.
An ontology defines the meaning of terms and the relationships between them. TESSER reviews clinical terminology, test items, and departmental workflows to build an ontology for each hospital.
Give hospital records a structure of meaning.
Preserve original terms while defining test concepts and linking each result to its patient and encounter. Define result properties and relationships to provide context for reviewing related prescriptions and supporting hospital-specific follow-up work.
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Preserve terms, connect meaning
Review hospital-specific names and codes and map them to the corresponding test concept. Preserve source terms and mapping rationale; similar names alone do not establish equivalence.
Define concepts, give records context
Distinguish test concepts from individual results and define their relationships to patients and encounters. Connect values, units where applicable, observation and reporting times, sources, and status to support interpretation.
Apply review and handoff conditions
Distinguish reviewer assignment from actual review status and define hospital-specific conditions for the next task. Use the defined meaning and relationships to retrieve relevant records and support review and follow-up work.
From data to practical use
Connected data supports
analysis and the next task.
Design connections, structure, and ontology together to support retrieval and comparison. Define what AI handles and where human review is needed, then apply it to partner products and hospital workflows in stages.
Start connecting your data
Which products and data
do you want to connect?
Tell us about your systems, the product you want to connect, and the workflow you want to improve.
We can explore the data, structuring scope, and ontology together.