Data contracts, terminology mappings and reconciliation behaviour
Interoperability & Data Platforms
Design healthcare data storage and exchange across APIs, FHIR interfaces and event streams. We define record ownership, identifiers and terminology, map source information into receiving contracts and plan synchronisation for downstream analytics. The handover includes data and interface models, provenance and lifecycle rules, and handling for delayed, conflicting or failed exchanges.
- 01FHIR & source records
- 02API & event contracts
- 03Provenance & reconciliation
Your starting point
Who this is for
- Organisations connecting healthcare, device or enterprise systems
- Teams resolving inconsistent data definitions, identifiers or ownership
- Product leaders planning records that remain understandable across systems and over time
Customer value
What this helps you do
A shared implementation contract
Both sides receive explicit field meanings, identifiers, mappings and ownership rules.
Defined exception handling
Reconciliation and compatibility rules tell teams how to handle changes and conflicting records.
Where we can help
Service scope
Establish meaning and ownership
Identify the system of record, the medical-data storage model and how fields and identifiers are interpreted. Define producer and consumer ownership, including downstream analytics synchronisation, before selecting transport.
Define implementable contracts
Specify FHIR interfaces, other APIs, event streams or batch exchanges as appropriate to the integration. Map source fields, identifiers and terminology to the receiving contract. Select the FHIR version and profiles, or other conformance requirements, with the participating teams.
Preserve origin and lifecycle context
Describe how exchanged information retains its source, history and update context. Assign the systems responsible for maintaining records and exposing the provenance their consumers need.
Specify failure and reconciliation
Document expected handling of delayed updates, conflicting values, failed exchanges and contract changes. Define compatibility rules, reconciliation owners and conformance scenarios.
Tangible outcomes
What you receive
- Integration landscape and source-of-truth responsibility matrix
- FHIR, API, event or batch contracts with identifier and terminology mappings
- Provenance, history and information lifecycle model
- Failure, reconciliation, compatibility and conformance plan
Working with your team
How we work together
Map the records and consumers
Identify data meaning, source ownership and the normal and exceptional exchange paths.
Specify mappings and contracts
Review field mappings, terminology, transport and lifecycle responsibilities with participating teams.
Trace representative records
Follow synthetic records through normal delivery, delayed updates and conflicts to review the proposed handling and conformance checks.
Illustrative scenario
Data mapping scenario
Assumptions
- 20 data fields requiring initial mapping across systems.
- Assume 30 minutes per field for manual lookup and definition.
- Assume 5 minutes per field using a prepared terminology workshop; preparation and review time are additional.
20 fields × (30 − 5 minutes) / 60 = 8.33 hours.
8.33 hours difference in the assumed initial mapping effort.
Illustrative planning arithmetic, not measured performance or a promise. Pilot validation must include workshop preparation, mapping quality and review effort before estimating net time differences.
Illustrative engagement
Illustrative scenario: an API-based medical-data transfer needs a streaming design for downstream analytics. We map source storage and FHIR exchange responsibilities, define event contracts and provenance, and specify how delayed updates, duplicates and conflicting records should be reconciled. Where a stream processor supplies an ML inference pipeline, its input and output contracts are defined as separate boundaries. The handover is an integration design and conformance plan; predictive performance and clinical validation require their own evidence.
Make your next data exchange explicit
Tell us which systems need to exchange information, what the records mean and where inconsistencies arise. We can scope the contracts, mappings and reconciliation design.
Plan your data exchange