deidentification.md

De-identification API

The deidentify() helper returns a typed DeidentificationResult with the redacted text, detected PIIEntity spans, result metadata, and a to_dict() representation for JSON-style workflows.

Entity Table Export

Use DeidentificationResult.to_dataframe() when you want to inspect the entities detected in a single de-identification result as a table:

from openmed import deidentify

result = deidentify("Patient John Doe called 555-1234", method="mask")
entities = result.to_dataframe()

The method imports pandas lazily, so importing openmed or openmed.core.pii does not import pandas. If pandas is not installed, calling to_dataframe() raises an actionable MissingExtraError with code missing_extra and the install command. It remains an ImportError for backward compatibility. See Structured public errors.

The returned DataFrame has one row per detected entity and always uses this column order:

Column	Description
text	Entity text span captured by the detector.
label	Detector label for the span.
entity_type	Normalized PII entity type stored on the result entity.
start	Character start offset in the original text.
end	Character end offset in the original text.
confidence	Detector confidence score.
action	De-identification policy action applied to the entity, when available.
result_id	Stable hash-derived identifier shared by every row from the result.

When no PII entities are present, to_dataframe() returns an empty DataFrame with the same columns.

India ABDM and ABHA identifiers

Enable the ABDM recognizer bundle for Indian clinical records to detect and replace ABHA numbers and addresses, Aadhaar numbers, PAN values, and contextual HPR/HFR registry identifiers:

from openmed import deidentify

result = deidentify(
    note,
    method="replace",
    lang="en",
    locale="en_IN",
    abdm=True,
)

The bundle also activates automatically for Hindi or Telugu, an India locale, or the india_dpdp_act policy profile. Pass abdm=False to opt out explicitly. It is inactive for other languages and locales by default. Recognized source labels (ABHA_NUMBER, ABHA_ADDRESS, AADHAAR, PAN, ABDM_HPR_ID, and ABDM_HFR_ID) normalize to ID_NUM and the DIRECT_IDENTIFIER policy class. Replacement mode produces synthetic values only; it does not call ABDM, verify an identifier, or store or resolve a real ABHA number. ABHA numbers are validated by their publicly documented 14-digit shape; the public NHA materials do not specify an offline checksum algorithm.

ABHA-linked record sharing requires the individual's informed consent. This mode de-identifies recognized identifiers, but it does not collect or record consent and does not decide whether a disclosure is permitted. Applications must enforce their own consent and disclosure workflow before sharing records. See the official ABDM FAQ for the ABHA identity and consent model.