Existing work

Analyze the outcomes already in your treatment records.

Your treatment history may already span years of records, spreadsheets, exports, or structured research datasets. That work doesn't have to remain separate from what comes next.

Prepare eligible historical records so they can become part of the same structured practice history as the treatments you document going forward.

As that history grows, each record gives you more context for understanding your work, comparing what you've documented over time, and creating reports from the record you've built.

Analyze your historical outcomes.

The work you've already documented and the work you do next can become part of one structured history.

Bring what you've already done and capture what you do next. Both paths converge into your structured practice history, then feed the knowledge loop: Know, Apply, Record, Understand, Learn, Share.
Bring

What you've already done

Prepare eligible historical records.

Capture

What you do next

Document new treatments as you work.

Your structured practice history

Every new and historical treatment record adds deeper context you can use.

Know Apply Record Understand Learn Share

Validation

See what needs attention before you import.

Validation checks required fields, supported values, relationships, duplicates, and other admission requirements. Records that need correction remain distinguishable from records ready to proceed.

Dataset readiness statuses
  • Ready Meets admission requirements for the requested import
  • Need attention Required fields, values, or relationships need correction
  • Excluded Outside the accepted structure for this import
Practice history

See more context with every record you add.

Add more records to give yourself more context for what you are seeing over time.

  1. Compare your own work as your practice history grows.

  2. Create professional reports from the same structured record you already built.

  3. Review your work without handing clinical judgment to the software.

Add structure without changing what the record says.

Preparing historical records isn't about treating your work like a pile of files. It is about preserving what each record represents while giving repeated work a consistent structure that can be reviewed and compared.

Validation checks the information against Arcametric's requirements before an accepted record becomes part of that history.

Identity boundary

Keep patient names and identifying details in your clinic.

Prepare source data before it enters Arcametric. Patient identity stays outside the hosted dataset while the information needed for supported analysis is mapped into the accepted structure.

Read the structural privacy architecture

Provenance

Keep the source attached to the record.

Imported information retains its origin, import batch, validation status, and other required provenance so externally sourced data doesn't become indistinguishable from information captured directly in Arcametric.

Provenance stays attached to the record
Origin
External import or direct capture
Import batch
Preserved when the record entered through Bring
Validation status
Admission result retained with the record
Source attachment
Externally sourced data stays distinguishable
Exports

Take your data with you.

Supported exports let you use structured Arcametric data outside the platform when needed.

See sample reports

Questions

Get answers to common questions about importing existing records.

Can I use data I already have?

Arcametric is designed to support eligible existing clinical and research data as a second path into the same structured history used for ongoing records. Existing data must meet defined preparation and validation requirements before accepted records enter the platform.

What is the minimum information Arcametric needs?

Requirements depend on what the dataset is intended to support. A record may need different fields for treatment history, outcomes analysis, safety summaries, cohort analysis, or comparison.

What if my data is messy or inconsistent?

Validation is designed to identify records and fields that need attention before acceptance. Arcametric does not promise to repair arbitrary source data.

Does AI decide whether my data is valid?

No. AI may assist mapping or preparation where approved, but deterministic Arcametric requirements govern acceptance.

Can I bring historical records in and keep collecting new information?

That is the intended Capture / Bring model: accepted historical records and newly captured records build the same structured history.

Are imported records distinguishable from records captured directly in Arcametric?

The end-state model preserves provenance and source so externally sourced data does not become indistinguishable from information captured directly in Arcametric.

Does Arcametric receive my original patient-identifiable source file?

Under the intended architecture, identity-bearing source data is prepared before it enters Arcametric. Patient identity stays under your control while accepted records use de-identified references.

Where is identifying information removed?

Under the intended architecture, preparation occurs under the data owner's control before the governed dataset enters Arcametric.

Does Arcametric need patient names to import historical records?

The intended hosted data model uses de-identified references rather than patient names.

Does Arcametric match the same patient across different organizations?

No. Arcametric does not infer that records held by separate organizations belong to the same patient. Shared research or clinical work must use an explicitly authorized project or subject identity model.

Can different practitioners contribute different parts of a treatment history?

Only within an explicitly authorized shared record or project model. Arcametric does not infer identity matches across separate organizations.

How does Arcametric preserve where each record came from?

The intended model preserves source and provenance for imported records, including origin and validation status required for analytical review.

Does importing a record automatically make it available for analysis?

No. Admission and analytical eligibility are separate.

Does imported data automatically become part of benchmarking?

No. Import, analytical eligibility, benchmark eligibility, and contribution authorization are separate decisions.

Why might one record qualify for one analysis but not another?

Different analyses require different fields, timepoints, provenance, completeness, and eligibility rules.

Do I have to replace my EHR?

No. Arcametric runs beside your existing EHR. Billing, scheduling, and general charting stay where they are while Arcametric holds the structured interventional treatment record.