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deidentify-a-dataset
De-identify selected free-text columns in a local CSV, JSONL, or Parquet dataset with OpenMed and produce a separate redacted dataset plus a PHI-free aggregate summary. Use when an agent must prepare a clinical dataset for analysis or sharing without overwriting the source or exposing cell values in logs.
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- 5,664
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- Docs & office
- License
- Apache-2.0
- Last commit
- Oct 13, 2026
skills/deidentify-a-dataset/SKILL.md
View on GitHubDe-identify a dataset
Keep the source local, name the free-text columns explicitly, and write to a different destination. Never infer columns or print source and redacted cell values.
Procedure
- Confirm that the input is CSV, JSONL/NDJSON, or Parquet.
- Confirm which columns contain free text. Do not scan or log values to guess.
- Choose a policy and language. Prefer
strict_no_leakwhen recall is the governing safety requirement. - Write to a new path; never overwrite the input.
- Inspect only
result.summary, which contains aggregate counts and rates. - Validate recall and residual leakage on representative synthetic or approved evaluation fixtures before releasing the output.
Runnable synthetic example
Install the model runtime first with python -m pip install "openmed[hf]".
import csv
from pathlib import Path
from openmed import redact_dataset
source = Path("synthetic-notes.csv")
destination = Path("synthetic-notes.redacted.csv")
with source.open("w", newline="", encoding="utf-8") as handle:
writer = csv.DictWriter(handle, fieldnames=["record_id", "note"])
writer.writeheader()
writer.writerows(
[
{
"record_id": "SYNTH-001",
"note": (
"Taylor Example called 212-555-0198 about a "
"metformin refill."
),
},
{
"record_id": "SYNTH-002",
"note": (
"Send the synthetic follow-up to "
"[email protected]."
),
},
]
)
result = redact_dataset(
source,
text_columns=["note"],
output_path=destination,
policy="strict_no_leak",
lang="en",
)
print(result.output_path)
print(result.summary.to_dict()) # Aggregate counts only; no cell contents.
Use the equivalent CLI for an existing dataset:
openmed redact-dataset notes.csv \
--text-columns note,comment \
--policy strict_no_leak \
--output notes.redacted.csv
Safety checks
- Keep model inference and files on infrastructure the user controls.
- Do not print input rows, detected entity surfaces, reversible mappings, or exception payloads that may contain source text.
- Keep source and output paths separate and access-controlled.
- Treat the aggregate summary as evidence, not as proof of compliance.
- Never commit real clinical data or restricted evaluation corpora.
Repository example
Read and run the offline dataset walkthrough when you need a bundled synthetic fixture and first-run download controls.
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