Map each target field to a source field
Choose which source field (e.g. patient_first_name) feeds each target field (e.g. FirstName) from a dropdown — no code, no config file editing.
HEALTHTECH & HEALTHCARE MVP
HealthData Mapper
Map each target field to a source field with dropdowns and see live completion status, type-mismatch warnings, and required-field errors — the no-code workspace teams use to connect two healthcare applications.
- Live completion tracking and required-field validation
- Flags type mismatches between source and target
- Runs entirely in your browser
Field mappings
FirstName
LastName
DateOfBirth
MedicalRecordNumber
EncounterDate
ICD10Code
ActiveStatus
Validation
How it works
Completion and required-field status update live
A progress bar and stat tiles track how many fields are mapped, how many required fields are still unmapped, and whether the mapping is ready to export.
Type mismatches are flagged automatically
When a mapped source field's data type doesn't match its target (e.g. a string mapped to a date field), the mapping is flagged as a warning so you catch a conversion issue before go-live, not after.
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Frequently asked questions
What counts as "ready to export"?
A mapping is export-ready when every required target field has a mapped source field — type mismatches are surfaced as warnings but don't block export, since a conversion step can often resolve them.
Can I add my own source and target fields?
This demo uses a fixed representative set of patient-record fields so you can explore the validation mechanism. A production Health Data Mapper would let you import your own source and target schemas.
Is my field mapping uploaded anywhere?
No. All validation runs entirely client-side in your browser from the selections you make — nothing is sent to a server.
How does type-mismatch detection work?
Each source and target field has a declared type (string, number, date, boolean, or code). When a mapped pair's types differ, the tool flags it as a warning naming both types, so you know a conversion step is needed.
Does this replace a full integration engine?
No — this demonstrates the field-mapping and validation workspace. A production integration would execute the actual data transformation and load, not just validate the mapping definition.
How We Compare
| Feature | MVPHub | Hand-written transformation scripts | Generic ETL/iPaaS mapping tools |
|---|---|---|---|
| Healthcare-field-specific validation | Included | Not included | Limited |
| Live required-field and completion tracking | Included | Not included | Included |
| Type-mismatch detection between fields | Included | Not included | Limited |
| No-code, no setup required to explore | Included | Not included | Not included |
Hand-written scripts give full control but no live validation feedback; generic ETL/iPaaS tools are powerful but carry setup and licensing overhead. MVPHub demonstrates the mapping and validation mechanism instantly, no setup required.
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