Researchers and evaluators

Capture comparable observations before you inherit a data-cleaning project.

Structure timing, context, measures, follow-up, and provenance before analysis begins. Arcametric organizes the input; researchers choose the methods, interpretation, and publication process.

Each structured record is research input, not evidence by itself.

See exactly what a structured treatment record contains.

Keep timing, intervention, context, measures, observations, and follow-up as explicit parts of the record instead of asking a future reviewer to recover them from one undifferentiated narrative.

Structured treatment record Seven explicit dimensions
  1. Timing When each event and observation occurred
  2. Intervention Substance, dose, and administration
  3. Context Clinical and situational context recorded with the event
  4. Observations What was observed or reported, kept distinct by source
  5. Measures Structured assessments and outcome measures
  6. Follow-up Assessments and observations recorded over time
  7. Provenance Where a value came from and when it was recorded

Separate the dimensions you will need to compare later.

Treat timing, intervention, context, measures, observations, and follow-up as distinct dimensions so later comparison does not depend on re-reading and reclassifying the original narrative.

The matrix shows which dimensions are captured, structured, exportable, and contextualized in the current system.

Current, verified record states. A dot marks a state we are not asserting here. It is not a claim that a capability is absent or planned.
Dimension CapturedStructuredExportableContextualized
Timing
Intervention ·
Context
Observations
Measures ·
Follow-up
Provenance ·

Provenance is preserved where the source of a value is captured.

See the structure in a real report.

Inspect how structured clinical information appears outside the application in governed outputs such as the Session Timeline, Progress Summary, Clinical Outcomes, and Follow-Up Completion reports.

The report is proof of the record structure, not proof of a research conclusion.

See sample reports

Preserve the context you will need to interpret an observation later.

Keep an observation tied to the timing and clinical context recorded with it. Where source or measure information is captured, carry that information with the record instead of reconstructing it later.

Missing information should remain visibly missing rather than being filled in by inference.

Illustrative observation Source kept with the value
Observation
Anxiety, patient-reported as moderate
Recorded
Session day, 00:45 after first administration
Phase
Treatment
Context
During the monitored session
Source
Patient report (kept distinct from clinician observation)

Structure the input. Keep the methodology downstream.

Arcametric structures the clinical record and provides governed reports and structured exports. Researchers choose the analysis environment, methodology, interpretation, and publication process.

That boundary keeps record structure and research method separate.

Arcametric structures the input
  1. Clinical workflow Documentation as care progresses
  2. Structured record Explicit dimensions, timing, and context
  3. Governed export De-identified structured export
Research handoff
Researchers choose the method
  1. Analysis environment The researcher's chosen tools and methods
  2. Interpretation and publication Findings, review, and reporting

Map what fits. Make the gaps explicit.

Use verified terminology mappings where they exist. When a clinically meaningful concept does not map cleanly to an existing code, make the gap visible instead of forcing a false equivalence.

A missing or partial mapping is useful information when it is labeled honestly.

Inspect the methods, standards, and source material.

Continue into the public materials that explain the record structure, coding work, privacy architecture, reports, and research context in more detail.